{ "cells": [ { "cell_type": "markdown", "id": "f06f558b-d98a-4425-b990-46713f6ed53e", "metadata": {}, "source": [ "# Tutorial 1: Salmonella dataset\n", "\n", "# 1. Background\n", "\n", "This tutorial consists of an index constructed from a *Salmonella enterica* dataset previously published in (https://doi.org/10.1128/jcm.02200-15). To prepare the data, the genomes were downloaded from NCBI and run through the provided analysis pipeline (`gdi analysis`) to identify SNVs, as well as [skesa](https://github.com/ncbi/SKESA), [SISTR](https://github.com/phac-nml/sistr_cmd) and [MLST](https://github.com/tseemann/mlst) for MLST analysis. A notebook describing how the index was constructed is available at [index-salmonella-data-tutorial-1.ipynb](https://github.com/apetkau/genomics-data-index-examples/blob/main/examples/create-index/index-salmonella-data-tutorial-1.ipynb).\n", "\n", "# 2. Getting data\n", "\n", "Let's first download the precomputed index for this tutorial. To do this please run the below commands:\n", "\n", "*Note: In a Jupyter Python notebook, prepending a command with `!` runs the command in a shell instead of the Python interpreter (e.g., `!unzip` runs the command `unzip`).*" ] }, { "cell_type": "code", "execution_count": 1, "id": "73c22f2e-0f52-469b-8119-e529f8b2ddff", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "--2022-12-15 15:34:43-- https://figshare.com/ndownloader/files/31555565?private_link=0405199820a13aedca42\n", "Resolving figshare.com (figshare.com)... 54.78.10.27, 52.51.22.31, 2a05:d018:1f4:d003:7186:f789:624a:fe25, ...\n", "Connecting to figshare.com (figshare.com)|54.78.10.27|:443... connected.\n", "HTTP request sent, awaiting response... 302 Found\n", "Location: https://s3-eu-west-1.amazonaws.com/pfigshare-u-files/31555565/salmonellaproject20211122.zip?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIYCQYOYV5JSSROOA/20221215/eu-west-1/s3/aws4_request&X-Amz-Date=20221215T213444Z&X-Amz-Expires=10&X-Amz-SignedHeaders=host&X-Amz-Signature=8c3656328dd2b4da2c34201e6fa383f2b949ff1f6d2c4a877defccfedb1a8456 [following]\n", "--2022-12-15 15:34:44-- https://s3-eu-west-1.amazonaws.com/pfigshare-u-files/31555565/salmonellaproject20211122.zip?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIYCQYOYV5JSSROOA/20221215/eu-west-1/s3/aws4_request&X-Amz-Date=20221215T213444Z&X-Amz-Expires=10&X-Amz-SignedHeaders=host&X-Amz-Signature=8c3656328dd2b4da2c34201e6fa383f2b949ff1f6d2c4a877defccfedb1a8456\n", "Resolving s3-eu-west-1.amazonaws.com (s3-eu-west-1.amazonaws.com)... 52.218.108.19, 52.218.88.203, 52.92.16.112, ...\n", "Connecting to s3-eu-west-1.amazonaws.com (s3-eu-west-1.amazonaws.com)|52.218.108.19|:443... connected.\n", "HTTP request sent, awaiting response... 200 OK\n", "Length: 10696541 (10M) [application/zip]\n", "Saving to: ‘salmonella-project.zip’\n", "\n", "salmonella-project. 100%[===================>] 10.20M 2.44MB/s in 4.4s \n", "\n", "2022-12-15 15:34:49 (2.31 MB/s) - ‘salmonella-project.zip’ saved [10696541/10696541]\n", "\n", "Archive: salmonella-project.zip\n", " creating: salmonella-project/\n", " creating: salmonella-project/.gdi-data/\n", "\n", "create-index\t\ttutorial-1-salmonella.ipynb\n", "salmonella-project\ttutorial-2-sars-cov-2.ipynb\n", "salmonella-project.zip\ttutorial-3-querying-overview.ipynb\n" ] } ], "source": [ "!wget -O salmonella-project.zip https://figshare.com/ndownloader/files/31555565?private_link=0405199820a13aedca42\n", "!unzip -n salmonella-project.zip | head -n 3\n", "!echo\n", "!ls" ] }, { "cell_type": "markdown", "id": "a315eb4d-ad8f-465b-b4b5-9c9035fbf663", "metadata": {}, "source": [ "Great. Now that we've got some data (in the `salmonella-project/` directory), let's explore the command-line interface to access this data.\n", "\n", "# 3. Command-line interface (`gdi`)\n", "\n", "Let's first print out the version of `gdi` being used." ] }, { "cell_type": "code", "execution_count": 2, "id": "e5ab20d8-881c-48a4-a4af-353b64cdcd27", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "gdi, version 0.9.2\n" ] } ], "source": [ "!gdi --version" ] }, { "cell_type": "markdown", "id": "a0dec935-0453-4d5a-a643-3c99f09514f9", "metadata": {}, "source": [ "## 3.1 List samples\n", "\n", "The below command lists the samples loaded in this index. Note that instead of passing the project with `--project-dir` you can change to the project directory and `gdi` will figure out which project you're in." ] }, { "cell_type": "code", "execution_count": 3, "id": "0f2e16fb-e012-480c-8978-10788947c1ce", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "SH12-012\n", "SH14-017\n", "SH12-004\n", "SH12-005\n", "SH12-013\n" ] } ], "source": [ "!gdi --project-dir salmonella-project list samples | head -n 5" ] }, { "cell_type": "markdown", "id": "146a37d6-9924-4ec2-ba42-b67ca8840514", "metadata": {}, "source": [ "## 3.2 List reference genomes\n", "\n", "This lists all the loaded reference genomes in this genomics index. This can be useful for commands later which require you to pass the name of the reference genome." ] }, { "cell_type": "code", "execution_count": 4, "id": "613518c9-86a8-4af3-98c9-fdfb777751cf", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "NC_011083\n" ] } ], "source": [ "!gdi --project-dir salmonella-project list genomes" ] }, { "cell_type": "markdown", "id": "b62f3325-abb6-46ef-9de5-8a097f4c1a9b", "metadata": {}, "source": [ "## 3.3 Query for a particular mutation or MLST allele type\n", "\n", "This searches for a particular mutation (in this case a deletion of a `CG` at position 2865334 and an insertion of a `G`). If you are familiar with the VCF format, this is given in terms of `CHROM:POS:REF:ALT` format.\n", "\n", "Note, prefixing the feature string with `hasa:` (as in `hasa:NC_011083.1:4559277:C:T`) is what is used to query the database for this particular feature." ] }, { "cell_type": "code", "execution_count": 5, "id": "779c052b-3ec6-4072-a59c-bbb49096136b", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Query Sample Name Sample ID Status\n", "NC_011083.1:4559277:C:T SH12-004 3 Present\n", "NC_011083.1:4559277:C:T SH12-005 4 Present\n", "NC_011083.1:4559277:C:T SH10-001 7 Present\n", "NC_011083.1:4559277:C:T SH12-002 12 Present\n", "NC_011083.1:4559277:C:T SH12-007 15 Present\n", "NC_011083.1:4559277:C:T SH12-001 17 Present\n", "NC_011083.1:4559277:C:T SH12-003 19 Present\n", "NC_011083.1:4559277:C:T SH12-010 28 Present\n", "NC_011083.1:4559277:C:T SH11-001 36 Present\n", "NC_011083.1:4559277:C:T SH12-006 47 Present\n", "NC_011083.1:4559277:C:T SH12-009 53 Present\n", "NC_011083.1:4559277:C:T SH12-011 54 Present\n", "NC_011083.1:4559277:C:T SH12-008 56 Present\n" ] } ], "source": [ "!gdi --project-dir salmonella-project query 'hasa:NC_011083.1:4559277:C:T' | column -s$'\\t' -t" ] }, { "cell_type": "markdown", "id": "e21af945-ab83-4643-b1c6-f48d41fe6d21", "metadata": {}, "source": [ "Alternatively, you can search for samples with a particular MLST allele." ] }, { "cell_type": "code", "execution_count": 6, "id": "c114ec88-1a4b-457d-ab71-a8a45a423164", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Query Sample Name Sample ID Status\n", "mlst:senterica:aroC:2 SH12-012 1 Present\n", "mlst:senterica:aroC:2 SH14-017 2 Present\n", "mlst:senterica:aroC:2 SH12-004 3 Present\n", "mlst:senterica:aroC:2 SH12-005 4 Present\n" ] } ], "source": [ "!gdi --project-dir salmonella-project query 'hasa:mlst:senterica:aroC:2' | column -s$'\\t' -t | head -n 5" ] }, { "cell_type": "markdown", "id": "4997ac88-ab25-4121-8986-ac4367b5a7b6", "metadata": {}, "source": [ "## 3.4. Summarize features\n", "\n", "If you want to print a table summarizing all features within a query, you can use `--features-summary [FEATURES]`.\n", "\n", "For example, to print a table summarizing mutations alleles:" ] }, { "cell_type": "code", "execution_count": 7, "id": "18aaf1a4-c7ad-4d67-b931-46559986aa54", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Mutation Count Total Percent ID_HGVS_GN.p\n", "NC_011083.1:3190398:G:A 59 59 100 -\n", "NC_011083.1:542308:G:A 59 59 100 hgvs_gn:NC_011083.1:SEHA_RS03145:p.T5T\n", "NC_011083.1:2288294:A:G 59 59 100 hgvs_gn:NC_011083.1:thiD:p.P119P\n", "NC_011083.1:4888140:G:T 59 59 100 hgvs_gn:NC_011083.1:SEHA_RS24190:p.C28F\n", "cut: write error: Broken pipe\n" ] } ], "source": [ "!gdi --project-dir salmonella-project query --features-summary mutations |\\\n", " cut -f 1,7,10,11,25 |\\\n", " head -n 5 |\\\n", " column -s$'\\t' -t" ] }, { "cell_type": "markdown", "id": "ad24c494-28df-439a-bae9-d331be6e5fbe", "metadata": {}, "source": [ "This shows a small selection of the top mutations out of all genomes in the dataset. **Count** is the number of genomes with that particular mutation, **Total** is the total number of genomes in the query (all genomes in the database in this case, feel free to try different query strings here to select subsets of genomes).\n", "\n", "*Note: the commands `cut`, `head`, and `column` are just used to clean up the output for Jupyter. There is more information included in this full table.*" ] }, { "cell_type": "markdown", "id": "cd04735a-c064-4c5c-bebd-9cc1e952a389", "metadata": {}, "source": [ "## 3.5. Query for a particular genome/sample\n", "\n", "You can also use the `isa:` prefix to query for a particular genome. As in:" ] }, { "cell_type": "code", "execution_count": 8, "id": "e8525c56-09a2-4628-804c-12eff2f11fd7", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Query Sample Name Sample ID Status\n", "isa_sample('SH14-002') SH14-002 30 Present\n" ] } ], "source": [ "!gdi --project-dir salmonella-project query 'isa:SH14-002' | column -s$'\\t' -t" ] }, { "cell_type": "markdown", "id": "8b7a9016-bd00-448c-a16e-31d9e835274b", "metadata": {}, "source": [ "You can combine this with the previous `--features-summary` command to summarize features in a particular genome." ] }, { "cell_type": "code", "execution_count": 9, "id": "1d79fa4c-60ea-44b4-bbe1-e6cd92c9a54e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Mutation Count Total Percent ID_HGVS_GN.p\n", "NC_011083.1:1947794:A:G 1 1 100 hgvs_gn:NC_011083.1:SEHA_RS10125:p.T61A\n", "NC_011083.1:4716545:T:C 1 1 100 hgvs_gn:NC_011083.1:SEHA_RS23395:p.I219I\n", "NC_011083.1:3945452:G:C 1 1 100 hgvs_gn:NC_011083.1:ligB:p.L134V\n", "NC_011083.1:3012412:C:T 1 1 100 hgvs_gn:NC_011083.1:invC:p.L25L\n", "cut: write error: Broken pipe\n" ] } ], "source": [ "!gdi --project-dir salmonella-project query 'isa:SH14-002' --features-summary mutations |\\\n", " cut -f 1,7,10,11,25 |\\\n", " head -n 5 |\\\n", " column -s$'\\t' -t" ] }, { "cell_type": "markdown", "id": "c375513b-3e66-43d6-a8cd-992948d4e795", "metadata": {}, "source": [ "## 3.6. Query based on phylogenetic distance\n", "\n", "You can also query based on the phylogenetic distance between samples using the `isin_[value]_[units]:` prefix to the query string. For example, use `isin_10_substitutions:SH12-013` to search for genomes within **5 substitutions** of genome **SH12-013**.\n", "\n", "The query is based on a stored phylogenetic tree built using mutations/deletions derived from alignment to a reference genome. You will also have to pass `--reference-name NC_011083` to specify the reference genome used to build the tree.\n", "\n", "*Note that **5 substitutions** here is derived from the branch lengths of the phylogenetic tree (multipled by the alignment length to convert substitutions/site to substitutions) and may not correspond to a count of the substitutions you get if you were to align genomes pairwise.*" ] }, { "cell_type": "code", "execution_count": 10, "id": "77eb8c07-b7c8-4f95-abac-5be4799effaa", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Query Sample Name Sample ID Status\n", "within(5.0 substitutions of 'SH14-002') SH14-017 2 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-025 6 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-021 8 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-027 10 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-005 11 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-007 13 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-023 18 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-003 20 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-028 21 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-006 24 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-024 26 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-009 27 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-011 29 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-002 30 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-022 31 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-014 33 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-020 39 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-018 40 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-008 43 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-015 44 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-019 46 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-016 48 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-010 50 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-004 52 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-001 55 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-026 57 Present\n", "within(5.0 substitutions of 'SH14-002') SH14-013 58 Present\n" ] } ], "source": [ "!gdi --project-dir salmonella-project query --reference-name NC_011083 'isin_5_substitutions:SH14-002' | column -s$'\\t' -t" ] }, { "cell_type": "markdown", "id": "a4ae4696-866c-40ac-aa5c-9b35ac0269d0", "metadata": {}, "source": [ "Combine this with `--features-summary mutations` to summarize the top mutations (and indels) in this set of selected genomes." ] }, { "cell_type": "code", "execution_count": 11, "id": "3363f5ee-2606-45d7-9d4f-75b63bb255c9", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Mutation Count Total Percent ID_HGVS_GN.p\n", "NC_011083.1:4465400:GGCCGAA:G 27 27 100 hgvs_gn:NC_011083.1:tyrB:p.E53_A54del\n", "NC_011083.1:3844892:G:T 27 27 100 hgvs_gn:NC_011083.1:SEHA_RS19240:p.T285K\n", "NC_011083.1:333057:T:G 27 27 100 hgvs_gn:NC_011083.1:tssM:p.L410R\n", "NC_011083.1:4636822:T:C 27 27 100 hgvs_gn:NC_011083.1:frdC:p.T91A\n", "cut: write error: Broken pipe\n" ] } ], "source": [ "!gdi --project-dir salmonella-project query --reference-name NC_011083 'isin_5_substitutions:SH14-002' --features-summary mutations |\\\n", " cut -f 1,7,10,11,25 |\\\n", " head -n 5 |\\\n", " column -s$'\\t' -t" ] }, { "cell_type": "markdown", "id": "df9caa41-8842-46f1-ad05-f8089e1e21cb", "metadata": {}, "source": [ "## 3.6 Build an alignment\n", "\n", "To build an alignment for use in further phylogenetics software you can do the following." ] }, { "cell_type": "code", "execution_count": 12, "id": "0beaf381-8b7f-44d4-abb5-1158c5d47d8b", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[32m2022-12-15 15:35:26\u001b[0m \u001b[1;30mINFO:\u001b[0m Started building alignment for 59 samples with include_variants=['SNP', 'MNP', 'DELETION']\n", "\u001b[32m2022-12-15 15:35:35\u001b[0m \u001b[1;30mINFO:\u001b[0m Finished building alignment for 59 samples. Took 8.65 seconds\n", "Wrote alignment to [out.aln]\n" ] } ], "source": [ "!gdi --project-dir salmonella-project build alignment --reference-name NC_011083 --align-type full --output-file out.aln" ] }, { "cell_type": "code", "execution_count": 13, "id": "2d8c2412-489a-4077-9399-11bd16142c09", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ ">NC_011083 [reference genome]\n", "AGAGATTACGTCTGGTTGCAAGAGATCATAACAGGGGGAATTAGTTGAAAATAAATATAT\n" ] } ], "source": [ "!head -n 2 out.aln" ] }, { "cell_type": "markdown", "id": "2c53b72d-450c-43b8-a083-b3b7fae8a311", "metadata": {}, "source": [ "This will produce an alignment with length equal to the reference genome, masking any missing data or gaps with `N`, and concatenating individual sequences (contigs) in the alignment together to construct a single, whole-genome alignment.\n", "\n", "You can pass in specific samples to include with `--sample`." ] }, { "cell_type": "markdown", "id": "51c56e91-3f23-49fc-9c08-8d8966874332", "metadata": {}, "source": [ "# 4. Python API (Genomics Data Index API)\n", "\n", "Now let's move on to the Python interface for loading, and querying data in this index. This is a much more powerful (and flexible) way to work with your data which attempts to provide seamless data flow between this index and Python [pandas](https://pandas.pydata.org/).\n", "\n", "We first start out by connecting to our project through `GenomicsDataIndex`." ] }, { "cell_type": "code", "execution_count": 14, "id": "cd88d725-228c-490a-922d-4faaaabf86a8", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import genomics_data_index.api as gdi\n", "\n", "db = gdi.GenomicsDataIndex.connect('salmonella-project')\n", "db" ] }, { "cell_type": "markdown", "id": "57f9fb8d-4d89-4648-ad9a-da2d38deeaf2", "metadata": {}, "source": [ "Great. We're connected. The `samples=59` tells us how many samples are in this database.\n", "\n", "You can run `db.sample_names()` or `db.reference_names()` to list the samples and reference genomes in this database." ] }, { "cell_type": "code", "execution_count": 15, "id": "b89b0b35-a805-4657-99b6-a2a230813ef4", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['SH12-012', 'SH14-017', 'SH12-004', 'SH12-005', 'SH12-013']" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "db.sample_names()[0:5]" ] }, { "cell_type": "code", "execution_count": 16, "id": "2f7dc469-5a7c-4e2f-b132-a5550b169abc", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['NC_011083']" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "db.reference_names()" ] }, { "cell_type": "markdown", "id": "ef44c72c-09e1-4bf4-adfa-d3e9f6867e6a", "metadata": {}, "source": [ "## 4.1 List all features (mutations)\n", "\n", "To list a summary of all indexed mutations we can do:" ] }, { "cell_type": "code", "execution_count": 17, "id": "4a4de449-1292-472f-9b42-b3b348cd9bb2", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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SequencePositionDeletionInsertionTypeCountUnknown CountPresent and Unknown CountTotalPercent...Gene_NameGene_IDFeature_TypeTranscript_BioTypeHGVS.cHGVS.pID_HGVS.cID_HGVS.pID_HGVS_GN.cID_HGVS_GN.p
Mutation
NC_011083.1:3190398:G:ANC_011083.13190398GASNP59NaNNaN59100.000000...idi-lysSSEHA_RS16035-SEHA_RS16040intergenic_region<NA>n.3190398G>A<NA>hgvs:NC_011083.1:n.3190398G>A<NA>hgvs_gn:NC_011083.1:n.3190398G>A<NA>
NC_011083.1:542308:G:ANC_011083.1542308GASNP59NaNNaN59100.000000...SEHA_RS03145SEHA_RS03145transcriptprotein_codingc.15C>Tp.T5Thgvs:NC_011083.1:SEHA_RS03145:c.15C>Thgvs:NC_011083.1:SEHA_RS03145:p.T5Thgvs_gn:NC_011083.1:SEHA_RS03145:c.15C>Thgvs_gn:NC_011083.1:SEHA_RS03145:p.T5T
NC_011083.1:2288294:A:GNC_011083.12288294AGSNP59NaNNaN59100.000000...thiDSEHA_RS11880transcriptprotein_codingc.357T>Cp.P119Phgvs:NC_011083.1:SEHA_RS11880:c.357T>Chgvs:NC_011083.1:SEHA_RS11880:p.P119Phgvs_gn:NC_011083.1:thiD:c.357T>Chgvs_gn:NC_011083.1:thiD:p.P119P
NC_011083.1:4888140:G:TNC_011083.14888140GTSNP59NaNNaN59100.000000...SEHA_RS24190SEHA_RS24190transcriptprotein_codingc.83G>Tp.C28Fhgvs:NC_011083.1:SEHA_RS24190:c.83G>Thgvs:NC_011083.1:SEHA_RS24190:p.C28Fhgvs_gn:NC_011083.1:SEHA_RS24190:c.83G>Thgvs_gn:NC_011083.1:SEHA_RS24190:p.C28F
NC_011083.1:4824790:T:CNC_011083.14824790TCSNP59NaNNaN59100.000000...SEHA_RS23860SEHA_RS23860transcriptprotein_codingc.1378T>Cp.*460Qext*?hgvs:NC_011083.1:SEHA_RS23860:c.1378T>Chgvs:NC_011083.1:SEHA_RS23860:p.*460Qext*?hgvs_gn:NC_011083.1:SEHA_RS23860:c.1378T>Chgvs_gn:NC_011083.1:SEHA_RS23860:p.*460Qext*?
..................................................................
NC_011083.1:863025:CCGGCGG:CNC_011083.1863025CCGGCGGCINDEL1NaNNaN591.694915...tolASEHA_RS04685transcriptprotein_codingc.135_140delCGGCGGp.G46_G47delhgvs:NC_011083.1:SEHA_RS04685:c.135_140delCGGCGGhgvs:NC_011083.1:SEHA_RS04685:p.G46_G47delhgvs_gn:NC_011083.1:tolA:c.135_140delCGGCGGhgvs_gn:NC_011083.1:tolA:p.G46_G47del
NC_011083.1:1819152:G:CNC_011083.11819152GCSNP1NaNNaN591.694915...SEHA_RS09510SEHA_RS09510transcriptprotein_codingc.369G>Cp.W123Chgvs:NC_011083.1:SEHA_RS09510:c.369G>Chgvs:NC_011083.1:SEHA_RS09510:p.W123Chgvs_gn:NC_011083.1:SEHA_RS09510:c.369G>Chgvs_gn:NC_011083.1:SEHA_RS09510:p.W123C
NC_011083.1:1427185:G:ANC_011083.11427185GASNP1NaNNaN591.694915...SEHA_RS07595SEHA_RS07595transcriptprotein_codingc.123G>Ap.Q41Qhgvs:NC_011083.1:SEHA_RS07595:c.123G>Ahgvs:NC_011083.1:SEHA_RS07595:p.Q41Qhgvs_gn:NC_011083.1:SEHA_RS07595:c.123G>Ahgvs_gn:NC_011083.1:SEHA_RS07595:p.Q41Q
NC_011083.1:3494198:G:ANC_011083.13494198GASNP1NaNNaN591.694915...mlaESEHA_RS17580transcriptprotein_codingc.56C>Tp.T19Mhgvs:NC_011083.1:SEHA_RS17580:c.56C>Thgvs:NC_011083.1:SEHA_RS17580:p.T19Mhgvs_gn:NC_011083.1:mlaE:c.56C>Thgvs_gn:NC_011083.1:mlaE:p.T19M
NC_011083.1:3255259:G:ANC_011083.13255259GASNP1NaNNaN591.694915...SEHA_RS16365SEHA_RS16365transcriptprotein_codingc.366G>Ap.L122Lhgvs:NC_011083.1:SEHA_RS16365:c.366G>Ahgvs:NC_011083.1:SEHA_RS16365:p.L122Lhgvs_gn:NC_011083.1:SEHA_RS16365:c.366G>Ahgvs_gn:NC_011083.1:SEHA_RS16365:p.L122L
\n", "

421 rows × 24 columns

\n", "
" ], "text/plain": [ " Sequence Position Deletion Insertion Type \\\n", "Mutation \n", "NC_011083.1:3190398:G:A NC_011083.1 3190398 G A SNP \n", "NC_011083.1:542308:G:A NC_011083.1 542308 G A SNP \n", "NC_011083.1:2288294:A:G NC_011083.1 2288294 A G SNP \n", "NC_011083.1:4888140:G:T NC_011083.1 4888140 G T SNP \n", "NC_011083.1:4824790:T:C NC_011083.1 4824790 T C SNP \n", "... ... ... ... ... ... \n", "NC_011083.1:863025:CCGGCGG:C NC_011083.1 863025 CCGGCGG C INDEL \n", "NC_011083.1:1819152:G:C NC_011083.1 1819152 G C SNP \n", "NC_011083.1:1427185:G:A NC_011083.1 1427185 G A SNP \n", "NC_011083.1:3494198:G:A NC_011083.1 3494198 G A SNP \n", "NC_011083.1:3255259:G:A NC_011083.1 3255259 G A SNP \n", "\n", " Count Unknown Count Present and Unknown Count \\\n", "Mutation \n", "NC_011083.1:3190398:G:A 59 NaN NaN \n", "NC_011083.1:542308:G:A 59 NaN NaN \n", "NC_011083.1:2288294:A:G 59 NaN NaN \n", "NC_011083.1:4888140:G:T 59 NaN NaN \n", "NC_011083.1:4824790:T:C 59 NaN NaN \n", "... ... ... ... \n", "NC_011083.1:863025:CCGGCGG:C 1 NaN NaN \n", "NC_011083.1:1819152:G:C 1 NaN NaN \n", "NC_011083.1:1427185:G:A 1 NaN NaN \n", "NC_011083.1:3494198:G:A 1 NaN NaN \n", "NC_011083.1:3255259:G:A 1 NaN NaN \n", "\n", " Total Percent ... Gene_Name \\\n", "Mutation ... \n", "NC_011083.1:3190398:G:A 59 100.000000 ... idi-lysS \n", "NC_011083.1:542308:G:A 59 100.000000 ... SEHA_RS03145 \n", "NC_011083.1:2288294:A:G 59 100.000000 ... thiD \n", "NC_011083.1:4888140:G:T 59 100.000000 ... SEHA_RS24190 \n", "NC_011083.1:4824790:T:C 59 100.000000 ... SEHA_RS23860 \n", "... ... ... ... ... \n", "NC_011083.1:863025:CCGGCGG:C 59 1.694915 ... tolA \n", "NC_011083.1:1819152:G:C 59 1.694915 ... SEHA_RS09510 \n", "NC_011083.1:1427185:G:A 59 1.694915 ... SEHA_RS07595 \n", "NC_011083.1:3494198:G:A 59 1.694915 ... mlaE \n", "NC_011083.1:3255259:G:A 59 1.694915 ... SEHA_RS16365 \n", "\n", " Gene_ID Feature_Type \\\n", "Mutation \n", "NC_011083.1:3190398:G:A SEHA_RS16035-SEHA_RS16040 intergenic_region \n", "NC_011083.1:542308:G:A SEHA_RS03145 transcript \n", "NC_011083.1:2288294:A:G SEHA_RS11880 transcript \n", "NC_011083.1:4888140:G:T SEHA_RS24190 transcript \n", "NC_011083.1:4824790:T:C SEHA_RS23860 transcript \n", "... ... ... \n", "NC_011083.1:863025:CCGGCGG:C SEHA_RS04685 transcript \n", "NC_011083.1:1819152:G:C SEHA_RS09510 transcript \n", "NC_011083.1:1427185:G:A SEHA_RS07595 transcript \n", "NC_011083.1:3494198:G:A SEHA_RS17580 transcript \n", "NC_011083.1:3255259:G:A SEHA_RS16365 transcript \n", "\n", " Transcript_BioType HGVS.c \\\n", "Mutation \n", "NC_011083.1:3190398:G:A n.3190398G>A \n", "NC_011083.1:542308:G:A protein_coding c.15C>T \n", "NC_011083.1:2288294:A:G protein_coding c.357T>C \n", "NC_011083.1:4888140:G:T protein_coding c.83G>T \n", "NC_011083.1:4824790:T:C protein_coding c.1378T>C \n", "... ... ... \n", "NC_011083.1:863025:CCGGCGG:C protein_coding c.135_140delCGGCGG \n", "NC_011083.1:1819152:G:C protein_coding c.369G>C \n", "NC_011083.1:1427185:G:A protein_coding c.123G>A \n", "NC_011083.1:3494198:G:A protein_coding c.56C>T \n", "NC_011083.1:3255259:G:A protein_coding c.366G>A \n", "\n", " HGVS.p \\\n", "Mutation \n", "NC_011083.1:3190398:G:A \n", "NC_011083.1:542308:G:A p.T5T \n", "NC_011083.1:2288294:A:G p.P119P \n", "NC_011083.1:4888140:G:T p.C28F \n", "NC_011083.1:4824790:T:C p.*460Qext*? \n", "... ... \n", "NC_011083.1:863025:CCGGCGG:C p.G46_G47del \n", "NC_011083.1:1819152:G:C p.W123C \n", "NC_011083.1:1427185:G:A p.Q41Q \n", "NC_011083.1:3494198:G:A p.T19M \n", "NC_011083.1:3255259:G:A p.L122L \n", "\n", " ID_HGVS.c \\\n", "Mutation \n", "NC_011083.1:3190398:G:A hgvs:NC_011083.1:n.3190398G>A \n", "NC_011083.1:542308:G:A hgvs:NC_011083.1:SEHA_RS03145:c.15C>T \n", "NC_011083.1:2288294:A:G hgvs:NC_011083.1:SEHA_RS11880:c.357T>C \n", "NC_011083.1:4888140:G:T hgvs:NC_011083.1:SEHA_RS24190:c.83G>T \n", "NC_011083.1:4824790:T:C hgvs:NC_011083.1:SEHA_RS23860:c.1378T>C \n", "... ... \n", "NC_011083.1:863025:CCGGCGG:C hgvs:NC_011083.1:SEHA_RS04685:c.135_140delCGGCGG \n", "NC_011083.1:1819152:G:C hgvs:NC_011083.1:SEHA_RS09510:c.369G>C \n", "NC_011083.1:1427185:G:A hgvs:NC_011083.1:SEHA_RS07595:c.123G>A \n", "NC_011083.1:3494198:G:A hgvs:NC_011083.1:SEHA_RS17580:c.56C>T \n", "NC_011083.1:3255259:G:A hgvs:NC_011083.1:SEHA_RS16365:c.366G>A \n", "\n", " ID_HGVS.p \\\n", "Mutation \n", "NC_011083.1:3190398:G:A \n", "NC_011083.1:542308:G:A hgvs:NC_011083.1:SEHA_RS03145:p.T5T \n", "NC_011083.1:2288294:A:G hgvs:NC_011083.1:SEHA_RS11880:p.P119P \n", "NC_011083.1:4888140:G:T hgvs:NC_011083.1:SEHA_RS24190:p.C28F \n", "NC_011083.1:4824790:T:C hgvs:NC_011083.1:SEHA_RS23860:p.*460Qext*? \n", "... ... \n", "NC_011083.1:863025:CCGGCGG:C hgvs:NC_011083.1:SEHA_RS04685:p.G46_G47del \n", "NC_011083.1:1819152:G:C hgvs:NC_011083.1:SEHA_RS09510:p.W123C \n", "NC_011083.1:1427185:G:A hgvs:NC_011083.1:SEHA_RS07595:p.Q41Q \n", "NC_011083.1:3494198:G:A hgvs:NC_011083.1:SEHA_RS17580:p.T19M \n", "NC_011083.1:3255259:G:A hgvs:NC_011083.1:SEHA_RS16365:p.L122L \n", "\n", " ID_HGVS_GN.c \\\n", "Mutation \n", "NC_011083.1:3190398:G:A hgvs_gn:NC_011083.1:n.3190398G>A \n", "NC_011083.1:542308:G:A hgvs_gn:NC_011083.1:SEHA_RS03145:c.15C>T \n", "NC_011083.1:2288294:A:G hgvs_gn:NC_011083.1:thiD:c.357T>C \n", "NC_011083.1:4888140:G:T hgvs_gn:NC_011083.1:SEHA_RS24190:c.83G>T \n", "NC_011083.1:4824790:T:C hgvs_gn:NC_011083.1:SEHA_RS23860:c.1378T>C \n", "... ... \n", "NC_011083.1:863025:CCGGCGG:C hgvs_gn:NC_011083.1:tolA:c.135_140delCGGCGG \n", "NC_011083.1:1819152:G:C hgvs_gn:NC_011083.1:SEHA_RS09510:c.369G>C \n", "NC_011083.1:1427185:G:A hgvs_gn:NC_011083.1:SEHA_RS07595:c.123G>A \n", "NC_011083.1:3494198:G:A hgvs_gn:NC_011083.1:mlaE:c.56C>T \n", "NC_011083.1:3255259:G:A hgvs_gn:NC_011083.1:SEHA_RS16365:c.366G>A \n", "\n", " ID_HGVS_GN.p \n", "Mutation \n", "NC_011083.1:3190398:G:A \n", "NC_011083.1:542308:G:A hgvs_gn:NC_011083.1:SEHA_RS03145:p.T5T \n", "NC_011083.1:2288294:A:G hgvs_gn:NC_011083.1:thiD:p.P119P \n", "NC_011083.1:4888140:G:T hgvs_gn:NC_011083.1:SEHA_RS24190:p.C28F \n", "NC_011083.1:4824790:T:C hgvs_gn:NC_011083.1:SEHA_RS23860:p.*460Qext*? \n", "... ... \n", "NC_011083.1:863025:CCGGCGG:C hgvs_gn:NC_011083.1:tolA:p.G46_G47del \n", "NC_011083.1:1819152:G:C hgvs_gn:NC_011083.1:SEHA_RS09510:p.W123C \n", "NC_011083.1:1427185:G:A hgvs_gn:NC_011083.1:SEHA_RS07595:p.Q41Q \n", "NC_011083.1:3494198:G:A hgvs_gn:NC_011083.1:mlaE:p.T19M \n", "NC_011083.1:3255259:G:A hgvs_gn:NC_011083.1:SEHA_RS16365:p.L122L \n", "\n", "[421 rows x 24 columns]" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "summary_df = db.mutations_summary(reference_name='NC_011083').sort_values('Count', ascending=False)\n", "summary_df" ] }, { "cell_type": "markdown", "id": "7da3832e-266c-42f4-8def-14de4ae88406", "metadata": {}, "source": [ "This gives us back a DataFrame summarizing the mutations.\n", "\n", "The **Count**, **Total**, and **Percent** columns tell us how many samples have a particular mutation.\n", "\n", "The **Annotation** and beyond columns give us detailed information about the mutation's impact (as derived from [snpeff](https://pcingola.github.io/SnpEff/) if this was run on the genomes (VCF files) prior to indexing). The **ID_HGVS...** columns give us alternative identifiers we can use for querying based on the [HGVS](https://varnomen.hgvs.org/) notation (as derived from snpeff annotations).\n", "\n", "You may notice that **Unknown Count** and **Present and Unknown Count** have values of `NA`. These columns record the number of samples where this particular mutation is \"Unknown/Missing\" (either due to N's or missing data in the particular regions of the genome). Calculating this information can slow down generating the features table for large datasets and so it is disabled by default. To enabled it you can pass `include_unknown_samples=True` to `mutations_summary()`." ] }, { "cell_type": "code", "execution_count": 18, "id": "a6921568-c261-4d56-a194-ab106510249a", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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SequencePositionDeletionInsertionTypeCountUnknown CountPresent and Unknown CountTotalPercent...Gene_NameGene_IDFeature_TypeTranscript_BioTypeHGVS.cHGVS.pID_HGVS.cID_HGVS.pID_HGVS_GN.cID_HGVS_GN.p
Mutation
NC_011083.1:3190398:G:ANC_011083.13190398GASNP5905959100.000000...idi-lysSSEHA_RS16035-SEHA_RS16040intergenic_region<NA>n.3190398G>A<NA>hgvs:NC_011083.1:n.3190398G>A<NA>hgvs_gn:NC_011083.1:n.3190398G>A<NA>
NC_011083.1:542308:G:ANC_011083.1542308GASNP5905959100.000000...SEHA_RS03145SEHA_RS03145transcriptprotein_codingc.15C>Tp.T5Thgvs:NC_011083.1:SEHA_RS03145:c.15C>Thgvs:NC_011083.1:SEHA_RS03145:p.T5Thgvs_gn:NC_011083.1:SEHA_RS03145:c.15C>Thgvs_gn:NC_011083.1:SEHA_RS03145:p.T5T
NC_011083.1:2288294:A:GNC_011083.12288294AGSNP5905959100.000000...thiDSEHA_RS11880transcriptprotein_codingc.357T>Cp.P119Phgvs:NC_011083.1:SEHA_RS11880:c.357T>Chgvs:NC_011083.1:SEHA_RS11880:p.P119Phgvs_gn:NC_011083.1:thiD:c.357T>Chgvs_gn:NC_011083.1:thiD:p.P119P
NC_011083.1:4888140:G:TNC_011083.14888140GTSNP5905959100.000000...SEHA_RS24190SEHA_RS24190transcriptprotein_codingc.83G>Tp.C28Fhgvs:NC_011083.1:SEHA_RS24190:c.83G>Thgvs:NC_011083.1:SEHA_RS24190:p.C28Fhgvs_gn:NC_011083.1:SEHA_RS24190:c.83G>Thgvs_gn:NC_011083.1:SEHA_RS24190:p.C28F
NC_011083.1:4824790:T:CNC_011083.14824790TCSNP5905959100.000000...SEHA_RS23860SEHA_RS23860transcriptprotein_codingc.1378T>Cp.*460Qext*?hgvs:NC_011083.1:SEHA_RS23860:c.1378T>Chgvs:NC_011083.1:SEHA_RS23860:p.*460Qext*?hgvs_gn:NC_011083.1:SEHA_RS23860:c.1378T>Chgvs_gn:NC_011083.1:SEHA_RS23860:p.*460Qext*?
..................................................................
NC_011083.1:863025:CCGGCGG:CNC_011083.1863025CCGGCGGCINDEL112591.694915...tolASEHA_RS04685transcriptprotein_codingc.135_140delCGGCGGp.G46_G47delhgvs:NC_011083.1:SEHA_RS04685:c.135_140delCGGCGGhgvs:NC_011083.1:SEHA_RS04685:p.G46_G47delhgvs_gn:NC_011083.1:tolA:c.135_140delCGGCGGhgvs_gn:NC_011083.1:tolA:p.G46_G47del
NC_011083.1:1819152:G:CNC_011083.11819152GCSNP101591.694915...SEHA_RS09510SEHA_RS09510transcriptprotein_codingc.369G>Cp.W123Chgvs:NC_011083.1:SEHA_RS09510:c.369G>Chgvs:NC_011083.1:SEHA_RS09510:p.W123Chgvs_gn:NC_011083.1:SEHA_RS09510:c.369G>Chgvs_gn:NC_011083.1:SEHA_RS09510:p.W123C
NC_011083.1:1427185:G:ANC_011083.11427185GASNP101591.694915...SEHA_RS07595SEHA_RS07595transcriptprotein_codingc.123G>Ap.Q41Qhgvs:NC_011083.1:SEHA_RS07595:c.123G>Ahgvs:NC_011083.1:SEHA_RS07595:p.Q41Qhgvs_gn:NC_011083.1:SEHA_RS07595:c.123G>Ahgvs_gn:NC_011083.1:SEHA_RS07595:p.Q41Q
NC_011083.1:3494198:G:ANC_011083.13494198GASNP101591.694915...mlaESEHA_RS17580transcriptprotein_codingc.56C>Tp.T19Mhgvs:NC_011083.1:SEHA_RS17580:c.56C>Thgvs:NC_011083.1:SEHA_RS17580:p.T19Mhgvs_gn:NC_011083.1:mlaE:c.56C>Thgvs_gn:NC_011083.1:mlaE:p.T19M
NC_011083.1:3255259:G:ANC_011083.13255259GASNP101591.694915...SEHA_RS16365SEHA_RS16365transcriptprotein_codingc.366G>Ap.L122Lhgvs:NC_011083.1:SEHA_RS16365:c.366G>Ahgvs:NC_011083.1:SEHA_RS16365:p.L122Lhgvs_gn:NC_011083.1:SEHA_RS16365:c.366G>Ahgvs_gn:NC_011083.1:SEHA_RS16365:p.L122L
\n", "

421 rows × 24 columns

\n", "
" ], "text/plain": [ " Sequence Position Deletion Insertion Type \\\n", "Mutation \n", "NC_011083.1:3190398:G:A NC_011083.1 3190398 G A SNP \n", "NC_011083.1:542308:G:A NC_011083.1 542308 G A SNP \n", "NC_011083.1:2288294:A:G NC_011083.1 2288294 A G SNP \n", "NC_011083.1:4888140:G:T NC_011083.1 4888140 G T SNP \n", "NC_011083.1:4824790:T:C NC_011083.1 4824790 T C SNP \n", "... ... ... ... ... ... \n", "NC_011083.1:863025:CCGGCGG:C NC_011083.1 863025 CCGGCGG C INDEL \n", "NC_011083.1:1819152:G:C NC_011083.1 1819152 G C SNP \n", "NC_011083.1:1427185:G:A NC_011083.1 1427185 G A SNP \n", "NC_011083.1:3494198:G:A NC_011083.1 3494198 G A SNP \n", "NC_011083.1:3255259:G:A NC_011083.1 3255259 G A SNP \n", "\n", " Count Unknown Count Present and Unknown Count \\\n", "Mutation \n", "NC_011083.1:3190398:G:A 59 0 59 \n", "NC_011083.1:542308:G:A 59 0 59 \n", "NC_011083.1:2288294:A:G 59 0 59 \n", "NC_011083.1:4888140:G:T 59 0 59 \n", "NC_011083.1:4824790:T:C 59 0 59 \n", "... ... ... ... \n", "NC_011083.1:863025:CCGGCGG:C 1 1 2 \n", "NC_011083.1:1819152:G:C 1 0 1 \n", "NC_011083.1:1427185:G:A 1 0 1 \n", "NC_011083.1:3494198:G:A 1 0 1 \n", "NC_011083.1:3255259:G:A 1 0 1 \n", "\n", " Total Percent ... Gene_Name \\\n", "Mutation ... \n", "NC_011083.1:3190398:G:A 59 100.000000 ... idi-lysS \n", "NC_011083.1:542308:G:A 59 100.000000 ... SEHA_RS03145 \n", "NC_011083.1:2288294:A:G 59 100.000000 ... thiD \n", "NC_011083.1:4888140:G:T 59 100.000000 ... SEHA_RS24190 \n", "NC_011083.1:4824790:T:C 59 100.000000 ... SEHA_RS23860 \n", "... ... ... ... ... \n", "NC_011083.1:863025:CCGGCGG:C 59 1.694915 ... tolA \n", "NC_011083.1:1819152:G:C 59 1.694915 ... SEHA_RS09510 \n", "NC_011083.1:1427185:G:A 59 1.694915 ... SEHA_RS07595 \n", "NC_011083.1:3494198:G:A 59 1.694915 ... mlaE \n", "NC_011083.1:3255259:G:A 59 1.694915 ... SEHA_RS16365 \n", "\n", " Gene_ID Feature_Type \\\n", "Mutation \n", "NC_011083.1:3190398:G:A SEHA_RS16035-SEHA_RS16040 intergenic_region \n", "NC_011083.1:542308:G:A SEHA_RS03145 transcript \n", "NC_011083.1:2288294:A:G SEHA_RS11880 transcript \n", "NC_011083.1:4888140:G:T SEHA_RS24190 transcript \n", "NC_011083.1:4824790:T:C SEHA_RS23860 transcript \n", "... ... ... \n", "NC_011083.1:863025:CCGGCGG:C SEHA_RS04685 transcript \n", "NC_011083.1:1819152:G:C SEHA_RS09510 transcript \n", "NC_011083.1:1427185:G:A SEHA_RS07595 transcript \n", "NC_011083.1:3494198:G:A SEHA_RS17580 transcript \n", "NC_011083.1:3255259:G:A SEHA_RS16365 transcript \n", "\n", " Transcript_BioType HGVS.c \\\n", "Mutation \n", "NC_011083.1:3190398:G:A n.3190398G>A \n", "NC_011083.1:542308:G:A protein_coding c.15C>T \n", "NC_011083.1:2288294:A:G protein_coding c.357T>C \n", "NC_011083.1:4888140:G:T protein_coding c.83G>T \n", "NC_011083.1:4824790:T:C protein_coding c.1378T>C \n", "... ... ... \n", "NC_011083.1:863025:CCGGCGG:C protein_coding c.135_140delCGGCGG \n", "NC_011083.1:1819152:G:C protein_coding c.369G>C \n", "NC_011083.1:1427185:G:A protein_coding c.123G>A \n", "NC_011083.1:3494198:G:A protein_coding c.56C>T \n", "NC_011083.1:3255259:G:A protein_coding c.366G>A \n", "\n", " HGVS.p \\\n", "Mutation \n", "NC_011083.1:3190398:G:A \n", "NC_011083.1:542308:G:A p.T5T \n", "NC_011083.1:2288294:A:G p.P119P \n", "NC_011083.1:4888140:G:T p.C28F \n", "NC_011083.1:4824790:T:C p.*460Qext*? \n", "... ... \n", "NC_011083.1:863025:CCGGCGG:C p.G46_G47del \n", "NC_011083.1:1819152:G:C p.W123C \n", "NC_011083.1:1427185:G:A p.Q41Q \n", "NC_011083.1:3494198:G:A p.T19M \n", "NC_011083.1:3255259:G:A p.L122L \n", "\n", " ID_HGVS.c \\\n", "Mutation \n", "NC_011083.1:3190398:G:A hgvs:NC_011083.1:n.3190398G>A \n", "NC_011083.1:542308:G:A hgvs:NC_011083.1:SEHA_RS03145:c.15C>T \n", "NC_011083.1:2288294:A:G hgvs:NC_011083.1:SEHA_RS11880:c.357T>C \n", "NC_011083.1:4888140:G:T hgvs:NC_011083.1:SEHA_RS24190:c.83G>T \n", "NC_011083.1:4824790:T:C hgvs:NC_011083.1:SEHA_RS23860:c.1378T>C \n", "... ... \n", "NC_011083.1:863025:CCGGCGG:C hgvs:NC_011083.1:SEHA_RS04685:c.135_140delCGGCGG \n", "NC_011083.1:1819152:G:C hgvs:NC_011083.1:SEHA_RS09510:c.369G>C \n", "NC_011083.1:1427185:G:A hgvs:NC_011083.1:SEHA_RS07595:c.123G>A \n", "NC_011083.1:3494198:G:A hgvs:NC_011083.1:SEHA_RS17580:c.56C>T \n", "NC_011083.1:3255259:G:A hgvs:NC_011083.1:SEHA_RS16365:c.366G>A \n", "\n", " ID_HGVS.p \\\n", "Mutation \n", "NC_011083.1:3190398:G:A \n", "NC_011083.1:542308:G:A hgvs:NC_011083.1:SEHA_RS03145:p.T5T \n", "NC_011083.1:2288294:A:G hgvs:NC_011083.1:SEHA_RS11880:p.P119P \n", "NC_011083.1:4888140:G:T hgvs:NC_011083.1:SEHA_RS24190:p.C28F \n", "NC_011083.1:4824790:T:C hgvs:NC_011083.1:SEHA_RS23860:p.*460Qext*? \n", "... ... \n", "NC_011083.1:863025:CCGGCGG:C hgvs:NC_011083.1:SEHA_RS04685:p.G46_G47del \n", "NC_011083.1:1819152:G:C hgvs:NC_011083.1:SEHA_RS09510:p.W123C \n", "NC_011083.1:1427185:G:A hgvs:NC_011083.1:SEHA_RS07595:p.Q41Q \n", "NC_011083.1:3494198:G:A hgvs:NC_011083.1:SEHA_RS17580:p.T19M \n", "NC_011083.1:3255259:G:A hgvs:NC_011083.1:SEHA_RS16365:p.L122L \n", "\n", " ID_HGVS_GN.c \\\n", "Mutation \n", "NC_011083.1:3190398:G:A hgvs_gn:NC_011083.1:n.3190398G>A \n", "NC_011083.1:542308:G:A hgvs_gn:NC_011083.1:SEHA_RS03145:c.15C>T \n", "NC_011083.1:2288294:A:G hgvs_gn:NC_011083.1:thiD:c.357T>C \n", "NC_011083.1:4888140:G:T hgvs_gn:NC_011083.1:SEHA_RS24190:c.83G>T \n", "NC_011083.1:4824790:T:C hgvs_gn:NC_011083.1:SEHA_RS23860:c.1378T>C \n", "... ... \n", "NC_011083.1:863025:CCGGCGG:C hgvs_gn:NC_011083.1:tolA:c.135_140delCGGCGG \n", "NC_011083.1:1819152:G:C hgvs_gn:NC_011083.1:SEHA_RS09510:c.369G>C \n", "NC_011083.1:1427185:G:A hgvs_gn:NC_011083.1:SEHA_RS07595:c.123G>A \n", "NC_011083.1:3494198:G:A hgvs_gn:NC_011083.1:mlaE:c.56C>T \n", "NC_011083.1:3255259:G:A hgvs_gn:NC_011083.1:SEHA_RS16365:c.366G>A \n", "\n", " ID_HGVS_GN.p \n", "Mutation \n", "NC_011083.1:3190398:G:A \n", "NC_011083.1:542308:G:A hgvs_gn:NC_011083.1:SEHA_RS03145:p.T5T \n", "NC_011083.1:2288294:A:G hgvs_gn:NC_011083.1:thiD:p.P119P \n", "NC_011083.1:4888140:G:T hgvs_gn:NC_011083.1:SEHA_RS24190:p.C28F \n", "NC_011083.1:4824790:T:C hgvs_gn:NC_011083.1:SEHA_RS23860:p.*460Qext*? \n", "... ... \n", "NC_011083.1:863025:CCGGCGG:C hgvs_gn:NC_011083.1:tolA:p.G46_G47del \n", "NC_011083.1:1819152:G:C hgvs_gn:NC_011083.1:SEHA_RS09510:p.W123C \n", "NC_011083.1:1427185:G:A hgvs_gn:NC_011083.1:SEHA_RS07595:p.Q41Q \n", "NC_011083.1:3494198:G:A hgvs_gn:NC_011083.1:mlaE:p.T19M \n", "NC_011083.1:3255259:G:A hgvs_gn:NC_011083.1:SEHA_RS16365:p.L122L \n", "\n", "[421 rows x 24 columns]" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "summary_df = db.mutations_summary(reference_name='NC_011083', include_unknown_samples=True).sort_values('Count', ascending=False)\n", "summary_df" ] }, { "cell_type": "markdown", "id": "73b74967-43c1-4faa-8bfe-e614c43ba1eb", "metadata": {}, "source": [ "Now we can see the **Unknown Count** and **Present and Unknown Count** valued filled in (**Present and Unknown** means the number of samples where the mutation is present (the `Count` column) **plus** the number of samples where it is **Unknown** if a mutation is present (the `Unknown Count` column).\n", "\n", "Let's look for mutations where less than 1/3 of the genomic samples have a particular mutation." ] }, { "cell_type": "code", "execution_count": 19, "id": "e30bfbe8-8fe2-462d-8f7c-2f19e5bd0d52", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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SequencePositionDeletionInsertionTypeCountUnknown CountPresent and Unknown CountTotalPercent...Gene_NameGene_IDFeature_TypeTranscript_BioTypeHGVS.cHGVS.pID_HGVS.cID_HGVS.pID_HGVS_GN.cID_HGVS_GN.p
Mutation
NC_011083.1:4482211:C:ANC_011083.14482211CASNP1713305928.813559...siiESEHA_RS22245transcriptprotein_codingc.3787C>Ap.R1263Shgvs:NC_011083.1:SEHA_RS22245:c.3787C>Ahgvs:NC_011083.1:SEHA_RS22245:p.R1263Shgvs_gn:NC_011083.1:siiE:c.3787C>Ahgvs_gn:NC_011083.1:siiE:p.R1263S
NC_011083.1:3167187:AACCACGACCACGACCACGACCACGACCACGACCACGACCACG:ANC_011083.13167187AACCACGACCACGACCACGACCACGACCACGACCACGACCACGAINDEL1516315925.423729...SEHA_RS15905SEHA_RS15905transcriptprotein_codingc.423_464delCGACCACGACCACGACCACGACCACGACCACGAC...p.D142_H155delhgvs:NC_011083.1:SEHA_RS15905:c.423_464delCGAC...hgvs:NC_011083.1:SEHA_RS15905:p.D142_H155delhgvs_gn:NC_011083.1:SEHA_RS15905:c.423_464delC...hgvs_gn:NC_011083.1:SEHA_RS15905:p.D142_H155del
NC_011083.1:4789652:G:ANC_011083.14789652GASNP130135922.033898...SEHA_RS23695-SEHA_RS23700SEHA_RS23695-SEHA_RS23700intergenic_region<NA>n.4789652G>A<NA>hgvs:NC_011083.1:n.4789652G>A<NA>hgvs_gn:NC_011083.1:n.4789652G>A<NA>
NC_011083.1:4739756:ACGC:ANC_011083.14739756ACGCAINDEL130135922.033898...arcCSEHA_RS23510transcriptprotein_codingc.566_568delGCGp.G189delhgvs:NC_011083.1:SEHA_RS23510:c.566_568delGCGhgvs:NC_011083.1:SEHA_RS23510:p.G189delhgvs_gn:NC_011083.1:arcC:c.566_568delGCGhgvs_gn:NC_011083.1:arcC:p.G189del
NC_011083.1:4559277:C:TNC_011083.14559277CTSNP130135922.033898...SEHA_RS22545SEHA_RS22545transcriptprotein_codingc.474C>Tp.A158Ahgvs:NC_011083.1:SEHA_RS22545:c.474C>Thgvs:NC_011083.1:SEHA_RS22545:p.A158Ahgvs_gn:NC_011083.1:SEHA_RS22545:c.474C>Thgvs_gn:NC_011083.1:SEHA_RS22545:p.A158A
\n", "

5 rows × 24 columns

\n", "
" ], "text/plain": [ " Sequence Position \\\n", "Mutation \n", "NC_011083.1:4482211:C:A NC_011083.1 4482211 \n", "NC_011083.1:3167187:AACCACGACCACGACCACGACCACGAC... NC_011083.1 3167187 \n", "NC_011083.1:4789652:G:A NC_011083.1 4789652 \n", "NC_011083.1:4739756:ACGC:A NC_011083.1 4739756 \n", "NC_011083.1:4559277:C:T NC_011083.1 4559277 \n", "\n", " Deletion \\\n", "Mutation \n", "NC_011083.1:4482211:C:A C \n", "NC_011083.1:3167187:AACCACGACCACGACCACGACCACGAC... AACCACGACCACGACCACGACCACGACCACGACCACGACCACG \n", "NC_011083.1:4789652:G:A G \n", "NC_011083.1:4739756:ACGC:A ACGC \n", "NC_011083.1:4559277:C:T C \n", "\n", " Insertion Type Count \\\n", "Mutation \n", "NC_011083.1:4482211:C:A A SNP 17 \n", "NC_011083.1:3167187:AACCACGACCACGACCACGACCACGAC... A INDEL 15 \n", "NC_011083.1:4789652:G:A A SNP 13 \n", "NC_011083.1:4739756:ACGC:A A INDEL 13 \n", "NC_011083.1:4559277:C:T T SNP 13 \n", "\n", " Unknown Count \\\n", "Mutation \n", "NC_011083.1:4482211:C:A 13 \n", "NC_011083.1:3167187:AACCACGACCACGACCACGACCACGAC... 16 \n", "NC_011083.1:4789652:G:A 0 \n", "NC_011083.1:4739756:ACGC:A 0 \n", "NC_011083.1:4559277:C:T 0 \n", "\n", " Present and Unknown Count \\\n", "Mutation \n", "NC_011083.1:4482211:C:A 30 \n", "NC_011083.1:3167187:AACCACGACCACGACCACGACCACGAC... 31 \n", "NC_011083.1:4789652:G:A 13 \n", "NC_011083.1:4739756:ACGC:A 13 \n", "NC_011083.1:4559277:C:T 13 \n", "\n", " Total Percent ... \\\n", "Mutation ... \n", "NC_011083.1:4482211:C:A 59 28.813559 ... \n", "NC_011083.1:3167187:AACCACGACCACGACCACGACCACGAC... 59 25.423729 ... \n", "NC_011083.1:4789652:G:A 59 22.033898 ... \n", "NC_011083.1:4739756:ACGC:A 59 22.033898 ... \n", "NC_011083.1:4559277:C:T 59 22.033898 ... \n", "\n", " Gene_Name \\\n", "Mutation \n", "NC_011083.1:4482211:C:A siiE \n", "NC_011083.1:3167187:AACCACGACCACGACCACGACCACGAC... SEHA_RS15905 \n", "NC_011083.1:4789652:G:A SEHA_RS23695-SEHA_RS23700 \n", "NC_011083.1:4739756:ACGC:A arcC \n", "NC_011083.1:4559277:C:T SEHA_RS22545 \n", "\n", " Gene_ID \\\n", "Mutation \n", "NC_011083.1:4482211:C:A SEHA_RS22245 \n", "NC_011083.1:3167187:AACCACGACCACGACCACGACCACGAC... SEHA_RS15905 \n", "NC_011083.1:4789652:G:A SEHA_RS23695-SEHA_RS23700 \n", "NC_011083.1:4739756:ACGC:A SEHA_RS23510 \n", "NC_011083.1:4559277:C:T SEHA_RS22545 \n", "\n", " Feature_Type \\\n", "Mutation \n", "NC_011083.1:4482211:C:A transcript \n", "NC_011083.1:3167187:AACCACGACCACGACCACGACCACGAC... transcript \n", "NC_011083.1:4789652:G:A intergenic_region \n", "NC_011083.1:4739756:ACGC:A transcript \n", "NC_011083.1:4559277:C:T transcript \n", "\n", " Transcript_BioType \\\n", "Mutation \n", "NC_011083.1:4482211:C:A protein_coding \n", "NC_011083.1:3167187:AACCACGACCACGACCACGACCACGAC... protein_coding \n", "NC_011083.1:4789652:G:A \n", "NC_011083.1:4739756:ACGC:A protein_coding \n", "NC_011083.1:4559277:C:T protein_coding \n", "\n", " HGVS.c \\\n", "Mutation \n", "NC_011083.1:4482211:C:A c.3787C>A \n", "NC_011083.1:3167187:AACCACGACCACGACCACGACCACGAC... c.423_464delCGACCACGACCACGACCACGACCACGACCACGAC... \n", "NC_011083.1:4789652:G:A n.4789652G>A \n", "NC_011083.1:4739756:ACGC:A c.566_568delGCG \n", "NC_011083.1:4559277:C:T c.474C>T \n", "\n", " HGVS.p \\\n", "Mutation \n", "NC_011083.1:4482211:C:A p.R1263S \n", "NC_011083.1:3167187:AACCACGACCACGACCACGACCACGAC... p.D142_H155del \n", "NC_011083.1:4789652:G:A \n", "NC_011083.1:4739756:ACGC:A p.G189del \n", "NC_011083.1:4559277:C:T p.A158A \n", "\n", " ID_HGVS.c \\\n", "Mutation \n", "NC_011083.1:4482211:C:A hgvs:NC_011083.1:SEHA_RS22245:c.3787C>A \n", "NC_011083.1:3167187:AACCACGACCACGACCACGACCACGAC... hgvs:NC_011083.1:SEHA_RS15905:c.423_464delCGAC... \n", "NC_011083.1:4789652:G:A hgvs:NC_011083.1:n.4789652G>A \n", "NC_011083.1:4739756:ACGC:A hgvs:NC_011083.1:SEHA_RS23510:c.566_568delGCG \n", "NC_011083.1:4559277:C:T hgvs:NC_011083.1:SEHA_RS22545:c.474C>T \n", "\n", " ID_HGVS.p \\\n", "Mutation \n", "NC_011083.1:4482211:C:A hgvs:NC_011083.1:SEHA_RS22245:p.R1263S \n", "NC_011083.1:3167187:AACCACGACCACGACCACGACCACGAC... hgvs:NC_011083.1:SEHA_RS15905:p.D142_H155del \n", "NC_011083.1:4789652:G:A \n", "NC_011083.1:4739756:ACGC:A hgvs:NC_011083.1:SEHA_RS23510:p.G189del \n", "NC_011083.1:4559277:C:T hgvs:NC_011083.1:SEHA_RS22545:p.A158A \n", "\n", " ID_HGVS_GN.c \\\n", "Mutation \n", "NC_011083.1:4482211:C:A hgvs_gn:NC_011083.1:siiE:c.3787C>A \n", "NC_011083.1:3167187:AACCACGACCACGACCACGACCACGAC... hgvs_gn:NC_011083.1:SEHA_RS15905:c.423_464delC... \n", "NC_011083.1:4789652:G:A hgvs_gn:NC_011083.1:n.4789652G>A \n", "NC_011083.1:4739756:ACGC:A hgvs_gn:NC_011083.1:arcC:c.566_568delGCG \n", "NC_011083.1:4559277:C:T hgvs_gn:NC_011083.1:SEHA_RS22545:c.474C>T \n", "\n", " ID_HGVS_GN.p \n", "Mutation \n", "NC_011083.1:4482211:C:A hgvs_gn:NC_011083.1:siiE:p.R1263S \n", "NC_011083.1:3167187:AACCACGACCACGACCACGACCACGAC... hgvs_gn:NC_011083.1:SEHA_RS15905:p.D142_H155del \n", "NC_011083.1:4789652:G:A \n", "NC_011083.1:4739756:ACGC:A hgvs_gn:NC_011083.1:arcC:p.G189del \n", "NC_011083.1:4559277:C:T hgvs_gn:NC_011083.1:SEHA_RS22545:p.A158A \n", "\n", "[5 rows x 24 columns]" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "summary_df[summary_df['Percent'] < 33].sort_values(['Count', 'Position'], ascending=False).head(5)" ] }, { "cell_type": "markdown", "id": "b3952849-bd62-425d-848d-212669d2eaaa", "metadata": {}, "source": [ "Let's use this table to select a mutation to search for. We will select `NC_011083.1:4482211:C:A`." ] }, { "cell_type": "markdown", "id": "6b5cfae9-be1c-4151-87e4-889faa2896f4", "metadata": {}, "source": [ "## 4.2 Search for a particular mutation (`hasa()`)\n", "\n", "We can search for genomic samples containing particular mutation by starting a query and using the `hasa()` method." ] }, { "cell_type": "code", "execution_count": 20, "id": "efb66090-6244-4b1a-a3ad-8b25f39429a8", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q = db.samples_query().hasa('NC_011083.1:4482211:C:A')\n", "q" ] }, { "cell_type": "markdown", "id": "65f49754-5759-4cae-9683-3ad2539f84af", "metadata": {}, "source": [ "The `hasa()` method can be read as \"select samples that **have a** particular mutation\". The selected samples are printed above (17/59 have this particular mutation)." ] }, { "cell_type": "markdown", "id": "e381acef-5986-4f06-baf6-51bbee4b65c3", "metadata": {}, "source": [ "### 4.2.1. Select by HGVS id\n", "\n", "We can also select samples using the [HGVS](https://varnomen.hgvs.org/) identifier." ] }, { "cell_type": "code", "execution_count": 21, "id": "c0ed4a5d-d3bb-4d77-98c4-dc2f0407882b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q = db.samples_query().hasa('hgvs_gn:NC_011083.1:siiE:p.R1263S')\n", "q" ] }, { "cell_type": "markdown", "id": "5cce19c4-2a05-4b94-8d4a-9a1f3e0dab16", "metadata": {}, "source": [ "The HGVS identifier is given as `hgvs:sequence:gene_locus_id:variant` (or `hgvs_gn:sequence:gene_name:variant`, `hgvs_gn` is for specifying gene name instead of locus). You can find the corresponding HGVS identifiers from the `mutations_summary()` table shown above." ] }, { "cell_type": "code", "execution_count": 22, "id": "6b0b7037-f3b6-4eb9-a8fa-ca1c8b680955", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "ID_HGVS.c hgvs:NC_011083.1:SEHA_RS22245:c.3787C>A\n", "ID_HGVS.p hgvs:NC_011083.1:SEHA_RS22245:p.R1263S\n", "ID_HGVS_GN.c hgvs_gn:NC_011083.1:siiE:c.3787C>A\n", "ID_HGVS_GN.p hgvs_gn:NC_011083.1:siiE:p.R1263S\n", "Name: NC_011083.1:4482211:C:A, dtype: object" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "summary_df.loc['NC_011083.1:4482211:C:A'][['ID_HGVS.c', 'ID_HGVS.p', 'ID_HGVS_GN.c', 'ID_HGVS_GN.p']]" ] }, { "cell_type": "markdown", "id": "e7b26996-8b89-4418-8ef6-766fb411eda7", "metadata": {}, "source": [ "*Note: As of right now, HGVS identifiers are derived when using SnpEff, so this option will only work if SnpEff was run on the VCF files and corresponding HGVS identifiers were stored in the index.*" ] }, { "cell_type": "markdown", "id": "dabceb51-7ec1-4aae-9738-1659747249b0", "metadata": {}, "source": [ "### 4.2.3. Unknown samples\n", "\n", "You may notice that in the results of the query we find `unknown=22% (13/59) samples`." ] }, { "cell_type": "code", "execution_count": 23, "id": "93d96508-0a39-4f71-a10e-d9fff1c904fd", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "db.samples_query().hasa('hgvs_gn:NC_011083.1:siiE:p.R1263S')" ] }, { "cell_type": "markdown", "id": "93cadf9f-0c83-430e-a699-9e5fd208d9e4", "metadata": {}, "source": [ "This shows us that there exists 1 sample where it is unknown whether or not it has a `hgvs_gn:NC_011083.1:siiE:p.R1263S` mutation. This could be either that this particular region of the genome had no reads align to it or there exists ambiguous characters (`N`), in this region, hence it cannot be determined whether or not the mutation in question exists.\n", "\n", "Samples where the result of a query is `unknown` are tracked and can be printed out using the commands shown below on accessing more details about a query." ] }, { "cell_type": "markdown", "id": "ae4debd6-1f39-404d-8df9-9e0b8cd30164", "metadata": {}, "source": [ "### 4.2.4. Details about query\n", "\n", "Once we have a query/selection of samples the specific samples can be shown with the `toframe()` method:" ] }, { "cell_type": "code", "execution_count": 24, "id": "19ee8645-9942-4e6a-8cd8-7d897c16b9d2", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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QuerySample NameSample IDStatus
0hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-0218Present
1hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-00511Present
2hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-00713Present
3hgvs_gn:NC_011083.1:siiE:p.R1263SSH10-3016Present
4hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-02318Present
5hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-00320Present
6hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-02821Present
7hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-00624Present
8hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-01225Present
9hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-00927Present
10hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-01129Present
11hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-00230Present
12hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-01433Present
13hgvs_gn:NC_011083.1:siiE:p.R1263SSH09-2935Present
14hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-00843Present
15hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-01946Present
16hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-00452Present
17hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-0172Unknown
18hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-0256Unknown
19hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-02710Unknown
20hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-02426Unknown
21hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-02231Unknown
22hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-02039Unknown
23hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-01840Unknown
24hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-01544Unknown
25hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-01648Unknown
26hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-01050Unknown
27hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-00155Unknown
28hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-02657Unknown
29hgvs_gn:NC_011083.1:siiE:p.R1263SSH14-01358Unknown
\n", "
" ], "text/plain": [ " Query Sample Name Sample ID Status\n", "0 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-021 8 Present\n", "1 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-005 11 Present\n", "2 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-007 13 Present\n", "3 hgvs_gn:NC_011083.1:siiE:p.R1263S SH10-30 16 Present\n", "4 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-023 18 Present\n", "5 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-003 20 Present\n", "6 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-028 21 Present\n", "7 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-006 24 Present\n", "8 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-012 25 Present\n", "9 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-009 27 Present\n", "10 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-011 29 Present\n", "11 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-002 30 Present\n", "12 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-014 33 Present\n", "13 hgvs_gn:NC_011083.1:siiE:p.R1263S SH09-29 35 Present\n", "14 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-008 43 Present\n", "15 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-019 46 Present\n", "16 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-004 52 Present\n", "17 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-017 2 Unknown\n", "18 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-025 6 Unknown\n", "19 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-027 10 Unknown\n", "20 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-024 26 Unknown\n", "21 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-022 31 Unknown\n", "22 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-020 39 Unknown\n", "23 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-018 40 Unknown\n", "24 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-015 44 Unknown\n", "25 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-016 48 Unknown\n", "26 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-010 50 Unknown\n", "27 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-001 55 Unknown\n", "28 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-026 57 Unknown\n", "29 hgvs_gn:NC_011083.1:siiE:p.R1263S SH14-013 58 Unknown" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q.toframe(include_unknown=True)" ] }, { "cell_type": "markdown", "id": "34b55061-e318-4774-a51e-77f9e423789c", "metadata": {}, "source": [ "You can use `include_unknown=True` to include samples where the status of the query is **Unknown** (unknown whether it is True or False). By default unknowns are not included.\n", "\n", "To summarize, you can use `summary()`:" ] }, { "cell_type": "code", "execution_count": 25, "id": "2fd551c5-4a41-4af3-82cb-1bd45014e3be", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
QueryPresentAbsentUnknownTotal% Present% Absent% Unknown
0hgvs_gn:NC_011083.1:siiE:p.R1263S1729135928.81355949.15254222.033898
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" ], "text/plain": [ " Query Present Absent Unknown Total \\\n", "0 hgvs_gn:NC_011083.1:siiE:p.R1263S 17 29 13 59 \n", "\n", " % Present % Absent % Unknown \n", "0 28.813559 49.152542 22.033898 " ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q.summary()" ] }, { "cell_type": "markdown", "id": "29f0712c-75ae-4948-9633-b7e9209d09b7", "metadata": {}, "source": [ "Or you can use `tolist()` (by default unknowns are not included, you can use `include_unknown=True` to include them)." ] }, { "cell_type": "code", "execution_count": 26, "id": "592958d5-2a3c-4ccd-80ff-5e32e71b9cea", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['SH14-021',\n", " 'SH14-005',\n", " 'SH14-007',\n", " 'SH10-30',\n", " 'SH14-023',\n", " 'SH14-003',\n", " 'SH14-028',\n", " 'SH14-006',\n", " 'SH14-012',\n", " 'SH14-009',\n", " 'SH14-011',\n", " 'SH14-002',\n", " 'SH14-014',\n", " 'SH09-29',\n", " 'SH14-008',\n", " 'SH14-019',\n", " 'SH14-004']" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q.tolist()" ] }, { "cell_type": "markdown", "id": "25ee7693-a697-49a0-b48c-59dbc15bf112", "metadata": {}, "source": [ "## 4.3 Chaining queries\n", "\n", "Queries can be chained together to select samples that match every criteria given in the `has()` method." ] }, { "cell_type": "code", "execution_count": 27, "id": "87694b6c-9692-49e0-b1db-b1afe67d01c6", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q = db.samples_query() \\\n", " .hasa('hgvs_gn:NC_011083.1:siiE:p.R1263S') \\\n", " .hasa('NC_011083.1:3535635:A:G')\n", "q" ] }, { "cell_type": "markdown", "id": "7797000c-cf17-4dcd-ad8b-1051439fd570", "metadata": {}, "source": [ "This can be read as \"select all samples that **have a** `R1263S` mutation (amino acid) on gene `siiE` **AND** select all samples that **have an** `A to G` mutation on position `3535635` of sequence `NC_011083.1`\".\n", "\n", "### 4.3.1. Handling unknowns\n", "\n", "You may notice that the unknown's have increased to 46%. In the data model used by this software, both ambiguous characters (e.g., `N`) and regions with too low of coverage are considered as unknown (or missing). So, if genomes have a large deletion in a particular region overlapping a mutation being queried, then these would all show up as having an unknown status (small deletions represented in the VCF file won't be considered as unknown). I do not know if this is the case here (further investigation is required) but this is something to keep in mind.\n", "\n", "You can convert all those samples/genomes that have an Unknown status to be considered selected if you wish using some boolean logic on queries and `select_unknown()`. In particular:" ] }, { "cell_type": "code", "execution_count": 28, "id": "9f2b8ddd-9a06-4876-9439-4a6e183dad35", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Select everything that is \"present\" in query `q` OR everything that is \"unknown\" in query `q`\n", "r = q.select_present() | q.select_unknown()\n", "\n", "# Alternatively\n", "# r = q.select_present().or_(q.select_unknown())\n", "\n", "r" ] }, { "cell_type": "markdown", "id": "a1a28138-796a-4619-b722-e7d7c4b63586", "metadata": {}, "source": [ "Here, `q.select_unknown()` selects only the unknown samples and `q.select_present() | q.select_unknown()` means select everything that is present in `q.select_present()` OR in `q.select_unknown()`." ] }, { "cell_type": "markdown", "id": "f0ed8d72-56c8-462d-910e-3f86d69b8c0c", "metadata": {}, "source": [ "## 4.4 Searching for a particular sample (`isa()` and `isin()`)\n", "\n", "The `isa()` and `isin()` methods let us search for particular samples by name. The difference between the two is that:\n", "\n", "1. `isa()` is meant to be read \"select samples that **are** (**is a**) type matching the expression.\n", "2. `isin()` is meant to be read \"select samples that are **in** a set defined by the passed criteria.\n", "\n", "The differences between these become more apparent for more advanced queries later on. For now, we can use these to select samples by name." ] }, { "cell_type": "code", "execution_count": 29, "id": "5752c79a-cd7d-433f-8d5d-37db8a202b1f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q = db.samples_query().isa('SH12-001')\n", "q" ] }, { "cell_type": "code", "execution_count": 30, "id": "449065f1-be1a-455d-bb28-6a956b1b557a", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q = db.samples_query().isin(['SH12-001', 'SH13-001'])\n", "q" ] }, { "cell_type": "markdown", "id": "a2c1435d-a4a2-41a6-b875-f9b80c117926", "metadata": {}, "source": [ "## 4.5 Searching within a tree\n", "\n", "Queries are not limited to what mutations a sample has or by sample name. We can also use `isin()` to select samples that match criteria related to a phylogenetic tree.\n", "\n", "To do this, we must specify that our query has a tree attached to it. The example data for this tutorial does have such a tree (though it can be built on-the-fly if needed using `build_tree()`, or joined to an existing tree using `join_tree()`)." ] }, { "cell_type": "code", "execution_count": 31, "id": "e533f99c-c6f9-40aa-b855-998b89f963fd", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "t = db.samples_query(universe='mutations', reference_name='NC_011083')\n", "t" ] }, { "cell_type": "markdown", "id": "96ce9b8a-3545-4de4-b915-30078f0cd918", "metadata": {}, "source": [ "Here, the type of query is a `MutationTreeSamplesQuery` which means it has a tree attached to it (derived from mutations). You can access the underlying tree with the `tree` property (as an ete3 Tree object)." ] }, { "cell_type": "code", "execution_count": 32, "id": "3b5a8097-4ad6-4b36-8f01-07af1db6168b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Tree node '' (0x7effb6c89d9)" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "t.tree\n", "\n", "# Print as newick format\n", "#t.tree.write()" ] }, { "cell_type": "markdown", "id": "c042fbb2-9c75-44c3-a49d-42f207c74e0e", "metadata": {}, "source": [ "You can quickly visualize the tree in-line by using the `tree_styler()` method:" ] }, { "cell_type": "code", "execution_count": 33, "id": "31a58a80-c7b2-4ee3-9874-031dc3316d3a", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ "t.tree_styler(show_legend_type_labels=False).render(w=300)" ] }, { "cell_type": "markdown", "id": "99e50d53-2862-4f90-b8f5-d1c71d830843", "metadata": {}, "source": [ "### 4.5.1. Select by distance in a tree\n", "\n", "Now that we have a phylogenetic tree, we can search using this tree with `isin()`. To do this, let's search for samples within some distance from `SH14-001`." ] }, { "cell_type": "code", "execution_count": 34, "id": "985f1edb-e773-4ab6-b1b4-59c2c2a90973", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tdist = t.isin('SH14-002', kind='distance', distance=1e-7, units='substitutions/site')\n", "tdist" ] }, { "cell_type": "markdown", "id": "9454961c-560c-4af5-9c50-88a7eeb2fa2d", "metadata": {}, "source": [ "This selects a subset of samples within the above distance (given in `'substitutions/site'`, you can also use `units='substitutions'`).\n", "\n", "It can be hard to see what is going on, so we can combine our query with the tree visualization using the `highlight()` method to highlight the selected samples in the tree.\n", "\n", "*Note: Selecting by distance to `SH14-002`, won't necessarily select genomes belonging to the same clade.*" ] }, { "cell_type": "code", "execution_count": 35, "id": "2b8ed3ed-9d16-4d5e-89fa-6a58e2f15f16", "metadata": {}, "outputs": [ { "data": { "image/png": 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jRrHjx4/XyNheXl7MwMBAJOVaW1ubOTs7s7S0NK5feb+aExcXx3r37s0dW1NTk61du1Zs/y1btjAjIyOun1AoZN9//z17/vw5r/fBJ/lbnn4lZCWOVydKfiafhdGjR2PIkCE19lgDAKSnpyM1NRVaWloVugyUJjU1FZmZmWjYsGGZD4KmpaUhPT0dJiYmqFWrllxjMDmSv/n0+9xQkCohH+nq6oo9kV6ZDAwMYGBgILNfySd65SEQCLiHUiuj3+eK7mERQhQGFSxCiMKggkVqVMmXbgnhgwoWqVEBAQHcc0+EyEIFi9SogoIChb4JTKoXFSxCiMKggkUIURhUsAghCoMKFiFEYVDBIoQoDPpqDvlqJSYmYv/+/fj333/BGIORkRG6deuGQYMGQUdHBwBw4cIFBAYGYt26dRK/33fp0iUEBATAw8ND4ndsfX19cffuXWzcuJFboeFTV65cwalTp/Dq1SsYGRmhf//+YmGsZQkLC8OePXsQExMDY2NjTJs2DZ07d5bYt6CgAFu2bIG6ujpmz54ttj0/Px9Hjx7FtWvXkJmZicaNG2PChAlo37497/lUB1qtgdSYWrVqsX379lX7uPfu3WM6OjpMXV2d2drasr59+3IrGRw9epTr5+rqygCwzMxMicdZtmwZA8Devn0r0p6Tk8NmzpzJrYyQn58vsj0jI4MNGDCACYVC1qtXLzZt2jTWvXt3BoCNHTuW13s4d+4cEwqFrH379mzmzJnMwsKCKSsrs1OnTon1TUhI4I7fvXt3se0PHz5krVq1Ypqammzo0KFsypQprHnz5kwoFLJdu3bxmk9VoiBV8lmoqYJlY2PD9PX1WUxMjEh7dHS0yL/x8hSsFy9eMAsLC2ZsbMwlS5cuWIwx5ubmxu7evSvStnDhQgaAhYSElDn//Px8ZmJiwnr16sUdu7CwkA0cOJAZGhqKvIerV6+yevXqse7duzNLS0uJBSs9PZ05OTmxV69ecW15eXnM0tKS6ejoSEyHrk4UpEq+ak+fPoWFhQVMTU1F2ps1a1bh5ZP+/vtvCAQC3L17V2RN+NLWrl0rdvk2YsQIAEBkZGSZY9y4cQPx8fFYuHAht2SNUCjEokWLkJSUhMuXL3N9T548iQEDBuDq1atcIEVptWvXxrZt20SWSlZRUcGQIUPw7t07bgXUmkb3sMhXqUmTJggNDcW7d++4+1WVxdHRESNGjICSkpLcYaRv374FUByKUZbQ0FAAEAtHtbS0hFAoREhICJfcvH37di5rsDzzUVJS4rU8TnWggkVqlEAgwK+//oo9e/ZU25h//PEH3Nzc4ODggM6dO2PlypUYPnx4mYvm3bx5U2IUVkxMjMT+5Q0j3b9/PwwMDCTmIn4qISEBampqYtmFqqqqqFu3LhfUWpG55OTk4Pjx4+jXrx+0tbXLdYzKRgWL1Cg1NTVs374dWlpa1Tbm3r17sWbNGvj7+2P+/PkYM2YM6tati5kzZ8LFxQW1a9cW22fAgAFVPi8fHx+cPHkSBw8elJkTKC2oFSgOR62MYNQ5c+bgzZs3+PXXXyt8rMpCBYvUKIFAAAsLiypd8bO0ksuo3r174+HDh/D398e2bdvg4eGBI0eOICgoSOzeVlhYGJeS/KnNmzdj586dFZ6Tv78/pk6dCicnJ0ycOJFrv3fvHsLCwrifGzRogP79+0sNagWKH1+oaDDqypUrceDAAfzxxx9cws/ngAoW+aoJBALY29vD3t4e58+fx5AhQ7B8+XIcOnRIpF+TJk0kngXKiuHi48aNG/j+++8xYcIEbN26VWTb6dOnsWHDBu7n3r17o3///qhbty4yMzORl5cndin75s2bCgWjbtq0CWvWrMH+/fsxcuTIch+nKtCnhIR8NHDgQFhYWIic0VS1mzdvYuDAgRg/fjx2794tFgqxdu1akQDVkk//2rZtC8YYnjx5ItL/5cuXyM7O5oJa5bV582YsWbIEBw8eFDnT+1xQwSLko5ycHMTGxlZJco4kt27dwoABAzBx4kR4eXnJlWDTp08fqKqq4uTJkyLtvr6+EAgE6Nu3r9zz2bp1KxYtWoTDhw9j/Pjxcu9fHeiSkEiUm5uLLVu2VPk4BQUFVT5GacnJyZg0aRL69u2LJk2aoE6dOoiPj8eOHTuQlJRULZ9YhoWFoX///jAwMIC5uTm8vb1FtmtoaGDChAlS99fX18fs2bPx66+/on79+ujRowfu3buH1atXw9HREc2bN5drPvv378f8+fPRt29fvHv3Drt27RLZ3qxZM/Tp00euY1YFKlhEoqVLl+LRo0fo1KlTlY7DGMPWrVvx888/V+k4n1JTU8ObN2/g4uLC3bguufl/4cIF9OvXr8rncO/ePWRmZiIzMxM//fST2Pb69euXWbAAYP369cjOzsaCBQuQl5cHoVCI0aNHixU/PgIDAwEU3/z39/cX2+7o6PhZFCwKUiUSOTs7o1GjRpg/f36VjqOnp4cXL15U66eEJfLy8pCSkoIPHz7AxMREYf9dv3//HklJSWjQoEGFPx38XFGQKvnq1apVCw0aNKjpaVSYlpYWmjVrVtPTqBZ0050QojCoYBFCFAYVLEKIwqCCRQhRGFSwCCEKgwoWIURhUMEihCgMKliEEIVBBYsQojCoYBFCFAZ9NYd8Ffz8/HD27Fm8fv0aenp6aNq0KRwcHNChQwcAxSk6e/bswdSpUyWusBkdHQ1vb29MnjwZbdq0Edt+//59HD9+HDNnzpS4UkJubi52796NW7duIS8vDz169MCsWbN4f3/x9evX2L59OyIiIqChoYHvv/+eS9gpT7+IiAj4+Pjg6dOn0NHRQZcuXTB16lSoqqrymk9NoTMs8sUbO3YsHBwcEBQUhKKiIkRGRmLjxo1wdHTk+rx48QKenp54/vy5xGPExMTA09MT0dHRYtt2796N7t27w9PTU2IoRV5eHuzs7ODq6gqhUAhNTU2sWLECvXv3Rl5ensz5v3z5Eu3atcO+fftgYGCAjIwM/PDDD3BxcSlXv6VLl6JDhw64cOEC9PT0kJ6ejnnz5qFTp07IyMiQOZ+aRkGqRMz8+fPZ5s2bq3wcXV1dsdTkynT9+nUGgLm4uIi05+TksOjoaO7nixcvMgDs3LlzEo9z5coVBkAkVTkrK4tNmDCB1apVi82dO5cBYFeuXBHb18vLiwFgV69e5dpCQkKYUCjk9Tt2dHRkBgYGLCkpiWvbsGEDA8BCQ0Pl7nfgwAHm4+MjMsa5c+cYALZ+/XqZ86kJFKRKvgpPnz4FAAwbNkykXVVVtcIrHLx69Qq3b9/G1atXuQxASY4ePQoLCwvY2tpybZaWlrC2thZbO760Dx8+4K+//sKkSZNEsgqdnJygoaGBw4cPy9UPACZNmoSxY8eKjDNw4ECoq6vLDHCtaVSwyBetSZMmAIDr169X+rGbNWuGJ0+eoEePHlIDShljePDggVjgKQBYWVkhLCwM2dnZUsd49OgR8vPzxfZXV1dHhw4dEBISIlc/abKzs5GbmyszwLWm0U13UqMKCwuxYcOGKlk8z9raGra2trCysoK7uzvi4uLg7Oxc5vLB4eHhEtNxpAVTyAopzcjIQFZWFkxMTMS2NWzYEIwxxMbGwszMTOL+JRHx0vYvKcR8+0lz8OBBFBUVfXYpOaVRwSI1yt/fH5cuXQJjrNKPzRjjAlNdXV2xd+9eeHl5wdbWFu7u7hLTld3c3Cp1DiWBppJWAi3JOSwr9FTW/iXb+faTJDIyEkuXLsWkSZPQuXNnqf0+B1SwSI2ytLSUeLlUWUruG+3YsQPLly/Hnj17sGPHDtja2mLlypVia8nv3r1bYiG7fft2uWKvVFRUAEBi6GlJAIe6ujoKCwtx4MABke0ODg4y9y8pUHz7lRYXFwd7e3u0adMGv//+O9+3VWOoYJGvRv369eHu7o558+Zh+PDhWLVqFcaNG4emTZtyfYyMjCTejH/58mW5xtTX14eSkhLevHkjti01NZXrU1BQgB9//FFke6tWrVC3bl0AkLp/SWAq336fSkxMRO/evVGvXj1cuHBBYrL154ZuupOvjra2NhYsWADGGMLDw6t0LBUVFbRo0QKPHz8W2/b48WMYGBjAyMgIqqqqIoGpBQUF6N69O/eQqrT9SwJT+fYrkZSUhF69ekFPTw8BAQGVkmBdHahgka9SyeMO1RGaOmjQIAQEBIg8lJmVlYXz58/D3t6+zH3r16+Pzp07iwWm3r17FzExMdz+fPsBxU/DlxQrf3//GkksKi+6JCRfNA8PD6SlpaFTp04wMTFBYWEhgoODsWHDBlhaWqJLly5VPoe5c+fC29sbw4YNw8qVK6GkpIS1a9ciMzMTixYtkrm/u7s7hgwZAicnJ0yePBlJSUmYP38+GjduLPI8FZ9+79+/h62tLV6+fIlVq1bh+PHjYuONGjXqsy5i9KQ7EVNdT7pXNS8vL2ZgYMAAcC9tbW3m7OzM0tLSuH7ledJd0nZJT7ozxlhQUBBr1qwZNwdTU1OpY0myc+dOpqenx+3frVs39uTJE7n7RUdHi/wuJL0iIyN5z6u6lDzpTkGqRKLqClKtLunp6UhNTYWWlla1XAZKwhhDfHw8hEIhjI2NIRAI5No/Pz8fsbGx0NPTk3gTXd5+ioSCVMlXRVdXt8YvcwQCARo2bFju/VVUVEQ+0axoP0VEN90JIQqDChYhRGFQwSKEKAwqWIQQhUEFixCiMKhgEUIUBhUsQojCoIJFCFEYVLAIIQqDChYhRGHQV3MIAZCTk4PDhw8jKCgI79+/R/369dG2bVsMHTqU+zrNhQsXEBgYiHXr1qFWrVpix7h06RICAgLg4eEh8n1bvuGmqamp2LNnD0JDQ6GmpgZ7e3uMHj1a5rrxQPH3B48ePYpr164hMzMTjRs3xoQJE9C+fXuxvv7+/vjzzz+RmpqKFi1aYMaMGQrzVR46wyJfvbdv36Jz58748ccf8ezZM+Tn5+POnTtwdnbGmjVruH5BQUHw9PSUGn4aHBwMT09P5OTkcG18w01fvHiB9u3bY9OmTVBTU0NOTg6mTJkCBwcHbillacLDw9G+fXvMmTMH7969g56eHs6dO4dOnTrB29tbpK+bmxvs7e0RGRmJunXr4uzZs2jXrh2uXLki76+txtDyMkTMl7K8DB8rV65kAJifn59Ie2pqqsjfhqurKwPAMjMzJR5n2bJlDIBIMCzfcNMhQ4YwAwMD9urVK64tKCiIKSkpsd9++63M+aenpzMnJyeRffPy8pilpSXT0dFhubm5jDHGQkNDGQDm5ubG9cvPz2cDBgxgRkZG7P3792WOU5MoSJWQj54+fQpVVVUMGDBApL1OnToVWoqGb7hpQUEBLly4gHHjxsHIyIjr17NnT4wcORL79u0rc5zatWtj27ZtIvuqqKhgyJAhePfuHRcBdu7cOQDA4sWLuX7Kysr47bffkJiYiIsXL5b7vVYXKljkq9ekSRPk5ubizp07lXpcvuGm6enpyM/PR4MGDcSO0bVrV0RERCArK0vu8d++fQslJSUYGBgAAJKTk6GpqYnatWuL9GvZsiVq166Nv//+W+4xqhvddCdfvFevXuHFixcSt7Vu3RqzZs2Cl5cX+vfvDzc3N0ybNq3Mhe9u3rwpMTYrJiZG5Ge+4aYGBgbQ0tLCs2fPxPpFRUUBAFJSUqCpqSl1TqXl5OTg+PHj6NevH7S1tQEAjRo1QlZWFpKSkkTOHJOSkvD+/XukpKTwPn5NoYJFvngODg5QVVWFUCh+QWFmZoa9e/fin3/+wezZs+Hq6ooVK1bA0dERy5cvlxj5VfrSURp5wk1HjBiBw4cPY9iwYbCzs0NBQQH27NmDgwcPAoDcq/zOmTMHb968wa+//sq1DRkyBO7u7pg9ezb27dsHXV1dREdHY/LkyeUaoyZQwSJfvKioKCQmJkqMoC/RuHFjXLhwAY8ePcKOHTtw8OBBnDx5Ev/73//Qr18/kb5hYWESM/w2b96MnTt3cj/LE27q6emJpGYp9osAACAASURBVKQk2NvbQ0NDAwUFBejWrRtmzJiB7du3o27duoiPj8elS5e4fYRCIaZMmSJ27JUrV+LAgQP4448/0KpVK669RYsWOHDgAGbNmgV9fX3o6OigoKAA27dvx927d0Xus32uqGAR8om2bdti165dWLRoEb777jvMnDlT7FKvSZMmEotf6Ww/ecJN9fX1cfHiRTx79gzPnz+HsbExzM3NMXnyZBgaGkJJSQmPHz8WCVtVVlYWK1ibNm3CmjVrsH//fowcOVJs3DFjxsDBwQEPHz5Ebm4uvv32W+4emqRL188N3XQnRIKmTZti3LhxiI2NRXp6ermOIW+4KQA0a9YM9vb2MDc3R2FhIQIDA9GrVy8AQN++fUWCVj993gsoPsNbsmQJDh48iIkTJ0qdl7a2Nrp37w5bW1vUrl2bewbLxsamXO+zOlHBIkSKp0+fQlNTs8xLybLIE24qyebNmxEbG4tZs2bJHGvr1q1YtGgRDh8+jPHjx/OeY2pqKjw8PGBnZ4fmzZvz3q+m0CUh+eqNHj0arVu3hpmZGYyNjZGeno6TJ0/i9OnTWLx4MZSVy/9nwjcENT09HVFRUWjQoAHi4+Nx8OBBeHt7w8XFBVZWVmWOsX//fsyfPx99+/bFu3fvsGvXLpHtzZo1Q58+fQAA//77L7S1tSEQCHD79m2sXLkS2dnZYk/Ef87oSXci5kt60l1LS0vq0+mMMTZlyhSmrq4uEibasGFDtnXrVlZYWMj1K8+T7ozxC0G9d++eyPitWrVi+/bt4/X+xo4dW2YwqqOjI9d34MCBXLu6ujobPXo0i4uL4zVOTaIgVVKmLylIVVtbW+anhEVFRUhNTUV6ejrq168v9nBlRfEJN01ISEBWVhbq1q0rdgO/smRnZyM+Ph7q6uowNDTkPsn83FGQKiGfEAqFqFevHurVq1clx+cTbirpSffKpqGhgRYtWlT5OFWFbroTQhQGFSxCiMKggkUIURhUsAghCoMKFiFEYVDBIoQoDCpYhBCFQQWLEKIwqGARQhQGFSxCiMKggkUIURj0XUJCPuHn54ezZ8/i9evX0NPTQ9OmTeHg4IAOHToAKF7aeMmSJbCxscGgQYPE9i8qKsLixYthbW2NwYMHi21PTk7Gli1bYG1tLbb0cokzZ87g9OnTSE1NRZs2beDk5MTre4ZFRUW4ePEiLl26hLi4OOjq6sLc3BwzZ84U++J3bm4udu/ejVu3biEvLw89evTArFmzPvuFDegMi5CPxo4dCwcHBwQFBaGoqAiRkZHYuHEjHB0duT4FBQXw9PTkEm9KKyoqgqenJwIDA8W23b59G506dcL69esRHBwscX9XV1cMHToUiYmJMDY2xtGjR9GxY0epqT+fzsvS0hKDBw9GeHg4DA0NkZ2djWXLlqFNmzYiyzTn5eXBzs4Orq6uEAqF0NTUxIoVK9C7d2+pqdafE1oPi4j5mtbDYoyx69evMwDMxcVFpD0nJ4dFR0dzP3/48IEBYAsXLpR4nPz8fAaAzZs3T6R98+bNTEVFhc2ePZupqamxZcuWie37+PFjBoAtX76ca3vz5g1r0KABGzJkiMz36evry8LCwkTaQkJCGAC2YsUKrs3Ly4sBYFevXhXpJxQKP9v/5pT8TMgnnj59CgAYNmyYSLuqqqrEqC955Obm4tixY9i8eTO2bdsmthZ7iWPHjkFZWRkLFizg2vT19TF9+nT4+flJDLP41MiRI8XWibe0tISOjg6eP3/OtR09ehQWFhawtbUV6WdtbY1Dhw6V5y1WGypYhKA4CQeA1Eu9ilBVVUVISAhmz56NoqIiqf1CQ0NhZmYGXV1dkXYrKysUFhbi3r17co8dGhqKd+/eoX379gAAxhgePHgglkZdMk5YWBiys7PlHqe60E138sXLy8tD/fr1JQapAkCvXr1w+vRpWFlZwd3dHXFxcXB2di4zlCEuLk5icZOUQQgASkpKMueZkJAgNSUaAF6+fCnzGB8+fEBCQgLS09Nx9+5deHh4wMbGBnPmzAEAZGRkICsrS+o4jDHExsbCzMxM5lg1gQoW+eIVFBTgwoUL6Nq1q8TtysrKWLNmDfz9/eHq6oq9e/fCy8sLtra2cHd352K2PuXr6wtfX99Knef79++lpkSXbJfl1q1bsLOz434ePHgwNm3axB1XVho133FqChUs8lVQV1cvc033n3/+GQCwY8cOLF++HHv27MGOHTtga2uLlStXcttLTJ06FUuWLBE7TmFhYbnPTlRUVKSmRJe8BwA4e/YskpOTue0WFhbcYxfdunVDeHg4MjMz8eLFC+zfvx/m5ubw8fHBiBEjZKZRfzrO54gKFiGl1K9fH+7u7pg3bx6GDx+OVatWYdy4cSJrsuvq6kq8GV/yR18edevWlZoSDYALr9i4cSPu3LnDbV+9ejVXsDQ1NdG2bVsAxcXL0dER3bp1g7OzM0aMGAF9fX0oKSnxGudzRDfdCZFCW1sbCxYsAGMM4eHhVT5e27ZtERkZCcaYSHtJcnTJJ4DBwcEiCdBubm5Sj6mkpISOHTsiPj4eubm5UFFRQYsWLaSmURsYGMDIyKgS31XlooJFSBlKHnfgE4NXUYMGDUJaWhquXbsm0u7r6wtTU1O0atVK7mMWFhbizp07MDExgaqqKjdOQEAAMjIyuH5ZWVk4f/68zDTqmkaXhIQA8PDwQFpaGjp16gQTExMUFhYiODgYGzZsgKWlJbp06VLlc+jfvz8sLCwwZcoUbN26Faampjh+/DguXryIXbt2Sf2UEwAePXqEJUuWYMSIEWjRogV0dHQQGxuLnTt34uHDh9ixYwfXd+7cufD29sawYcOwcuVKKCkpYe3atcjMzMSiRYuq/H1WBBUsQgAYGBhg69at2Lx5M9emra2NH3/8EcuXLy+zWFQWgUCAU6dOYdKkSRg6dCiA4ntSa9euxcyZM8vc18DAAAUFBZg+fbrIfTQzMzPs3bsXU6dO5dpMTEzg5+eHKVOmwNraGgBgamqKkydPcs9rfa4o+ZlI9CUlPyspKeHmzZuwsrKS2Tc9PR2pqanQ0tKqlstAaVJTU5GZmYmGDRtCWZn/eUVOTg6Sk5ORk5MDAwODMm+gM8YQHx8PoVAIY2NjCASCyph6laDkZ0Ik0NXVFXvSvCYYGBjAwMBA7v3U1NRgamrKq69AIOAeSlUUdNOdEKIwqGARQhQGFSxCiMKggkUIURhUsAghCoMKFiFEYVDBIoQoDCpYhBCFQQWLEKIwqGARQhQGFSxCSvn333/h4uKC77//HmPGjMHixYtx5coV7kvFBQUFcHFxgZ+fn8T9i4qK4OLigrNnz0rcnpycDDc3N1y6dInXfK5evYpJkyYhKCiIV//c3Fxs374do0aNwrBhw/Dbb79JTeo5c+YMJk+eDAcHByxZsgQJCQlSjyvvvKsCFSxCPuHt7Y1vv/0WPj4+yM3NRXx8PA4fPox+/fohKSkJQNWHqX4qJSUFY8eOxaFDhxAVFSWzvzwhqfKEtso776pCBYuQj7KysrBw4UJYWVnh5cuXuHDhAoKCgpCYmIjw8HCJSTPy2LJlC2xsbDB06FDeK57MmDFDriVf9u/fj5s3b8LPzw/Hjh3DkSNHEBAQgDt37mDnzp1cv5JU6+XLl+PSpUvw9vZGWFgYatWqBWdn5wrPu6pQwSLko4SEBGRlZWHAgAEif5gCgQCtW7eu0LH5hql+at++ffD398eqVat4j8M3JJVvaGt55l2VqGAR8lHJ2lM3btyo9GPzDVMt8d9//2H+/Pn47bff8M033/AaQ56QVL6hrfLOu6rReliEAAgJCUHHjh3h4uKCX375BXZ2dlixYgV69uwpdZ+qCFMt2X/8+PHo1asXZs6cyd07k0WekFR5Qlv5zrs6UMEiBMC0adPwww8/YP369TA2NoaHhwesra3RqlUrLFy4EJMnTxZbJrkqwlQBYP369Xj27BlOnTol137yhKRWRmhrTaCCRQgAoVCI4cOHAwCcnJwwffp0HD9+HFu2bMG0adPg6+sLPz8/LogUqJow1fv372P16tX466+/UK9ePan9JIWplsRz8QlJ5Rva+rmhgkWIBGpqapg8eTImTZoEd3d3rFu3Dj4+Ppg8eTLXp7LDVHNzczFu3DhYWVlBV1eXe3wgLS0NAPDs2TMEBwejffv2EsNUFy1axDsklW9o6+eGChYhZRAIBFzBCgsLq9KxUlJS8OTJEzx58kTivbMNGzZgw4YNCAkJkfosFN+Q1LZt2+LEiRNgjImET5QObf3c0KeEhMhQ8sBmVafoGBoaIjIyUux18+ZNAMCaNWsQGRnJxdJLwjcktSpCW6sDnWER8tGNGzfw66+/okePHmjUqBHU1dURERGBX375BXp6ehg/fnyVjq+srCzx3lfJp4SGhoYy743xDUmtSGhrTaKCRchHenp6uH37Ng4fPsy1KSsrY/DgwfDw8ECDBg1qcHb88A1JrUhoa02igkXIR+3atUN0dDSysrKQkpICgUAAExMTseeQ1NTUwBiTehxlZeUKbS/N0NBQrv49e/ZEVFSUzJBUExMTBAQE8A5tlXfeVYEKFiGlaGpqQlNTs6anUSHyhKSWN7S1JnyeF6qEECIBFSxCiMKgS0JCPlWQD0j5LiCpAkrKQBn3zUqjgkVIifx8FFyWvIooqTrKA4YCEj4UkIQuCQn5iBXRmdXnjgoWIURhUMEihCgMKliEEIVBBYsQojCoYBFCFAY91kCIFOfv/oNzf99Dcno69LS00MTIEIO6WKB9k8YAgKj4BOy9fAVT+vaBWUPx9dGfvUrE7ouXMcmuN1qbin9NJvTZc/xx4yZm9LdHM2MjmfPx8ruIf6KfYf3kCainW1tm/9fp6fj93AU8jomDhlotDOlmieHdu4n1y83Px95LV3D7cSTyCgrQvU0r/DigP9RqqYj0exwbh6PXbiAqPgE6Ghro3KI5JvftDVUVFbFjVhU6wyJEggmbNmPo6nW4GfEYRYwhMi4em06ewugNnlyfF6+TsfnUWTxPlBwSEZOcgs2nziL61SuxbXsv+cN6kRs2nzqLmOQUmfMJehSB+d57cfjqNWR+yJbZ/+XrZHSa44wD/gGoU1sbGVnZGP3LJized1CkX15BAfq5r8LSA4eLg1fV1LDS5w/0XfYz8j5ZOXXZIR9867QAF+/dh66WFtKzsuC8ex86z3NBRpbs+VQWOsMipJSgRxE4fv0mFgwbgg1TJnLtufn5iP+4hHB5ZefmYs7v3jgRFIwZA+yx4+x5mftkZGVjsudW9O7QHlce/MtrnGUHj6CoiCF052bU/xjltel/p7D0wBGMsfkOHZoWnyUevHIVwRGP4b92FXq1NwcA/P0kCtaLlmLX+UuYO2QQAKBlA2Psc3bCGBtrbozzd//B0NXr4H3hEhaPHCbX76G86AyLkFKi4hMAAN9bieb7qaqooKmR7Eu3siSmpeF25FP4r1uFwV278Npn3q490NbQwPjevXj1/5CXh1MhdzChTy+uWAHAbIeB0FBVxZHA/19l9Ni1IHzbvClXrACgq1kL9GzbBoev/n+/CX1sRYoVAAzo/C3Ua9XCk7h4XvOqDFSwCCml8celkG+EP6r0Yzc1MkKE93Z0b90KRTzWljoZfBsng2/jyCJnCIX8vr4SEROL/IJCdG3ZQqRdvVYttG/SGHeeFC/5zBjDv/+9QNeWLcWO0a1VSzx88RLZublSx8nOzUVufj7q6elK7VPZ6JKQkE+8z8lBr/bm6NbKDCsOH0NcyhvMH+pQ5k3xRzEx0FJXE2t/+OKlxP5KPJcfTniThtm/78KaCWNh/k0jPI6N47lfcRqOiUEdsW0NDergRngEACAjOxtZOTmS+9U1AGMMcSmpaGkieaXVwwHXUMQYRvSw4jWvykAFi5CP3r17h67zF2HMtOm4uGYFlh48gv2XA+B94RJ6tTeHm+NI2LRrK7af+6GjlT4XxhimbdmO9k0aY/5QB7n2ff8hBwCgrqoqtk1dVRXvc3JE+9WqJbHfp31KexIXj2WHfDChjy0smotHnVUVKliEfFTEGN5kvMMyi+KIq20/TseyUSOx79IV7PS7CDu3FVgxxhHLxziK7LfL6SeJhex25FNM+W1bueay49x53I9+jtAdmyUubwwAhUVFOHQlUKRtYFcLqHxcrqWwsEjCPoVcgVJRVuKOI9bv4xI76qrixSwuNRUDlq9G60YNsf2n6XK8q4qjgkVIGerr6sJt1Eg4DRmEH9ZtxJrjvhjb6zs0Mfr/yC9DPT2JN+Nfvpb9uIIkUfEJcDt4BDP62yMmORkxHxOeSz4MuP/sPySnZ6BTs6aY9fsukX0DG3qgro4OAOBNZqbYsVPfZUJPWwsAoK+lDSWhUEq/dwAAPS0tkfbEtLfo6/Yz6urWxrmV7tCQcBZXlahgEcKDtro65g8djIAHYQiPiREpWJXtXvQz5OTlY9sZP2w7I74+19gNnlBVUcH7UyeQc/ak2PbX6ekAgMjYOPTuIBqIGhkbx13CqSgroXkDY0RKuDcWGRsPAx0dGOnrcW1Jb9PRx20F9LS0cGHNCujWwLr3VLAI4SkqofgMx1BXT0bPinHo2hmPdm0Xa7/4z30s2nsQF9aswDf16kndv76uLiyaN8P/boVgzuCBXPu9qGjEJKfAzXEk1zawiwV2X7iMjKxs1NbUAABk5eTgwr376Nvp/wNbX6eno8/S5dDT0sT5VSu4vtWNChYhpaz740+kvX+Pjk2bwMSgDgqLinArIhK/njyFrmYt0Lll8yodX0dDAzoa4gXh3/9eAACaGNaX+TyY26iRGLZmPebt2otJdrZIepuOBbv34Zv69TG61/8/TzXHYSD2XPTHyHUbsGKMI5SEQqw/cRKZHz5g4fDivML3OTmwc/sZMcnJmGQ3CieCboqN94N1j2o546KCRUgpBrV1sP3seWw9fY5r01ZXx4wB9lg2aiSEPJfzrUkOXTtjx6wZWH74GHb6XQAAWJq1xL75c0Q+FTQxqIMzP7th2pbf0cvVHQBgWtcAJ5YuQrvG3wAAXr99y102Lj1wROJ435m3rZaCJQDAEhMTYWgo+5pcXV0db9++hZqa+DMn5Mvi7OyMRo0aYf78+TU9lQpTUlLCzZs3YWUl/Xkhc3Nz7Ny6Bd8P/R5Jxw8BANKzsvDm3TtoqqnDsBofjqxM+QWFiEtJga6WFvS1taT2Y4wh/s0bCAVCGOvrSf1ksirwWdM9KSkJRkZGdIZFiDS6mpo1cmO5MqkoK/H6gEAgEKChAoSp0ldzCCEKgwoWIURhUMEihCgMuodFyEdpKanILSjgHepJKgFjxS+ev3MqWIR8dDc0FLPnzi3+AyLVR47/QdAlISGf2PLbbzU9BVIGKliEEIVBBYsQojCoYBFCFAYVLEKIwqCCRQhRGPRYAyFSUPKz9ETnwqIiLN53EAKBAJumTZY5l8pCZ1iESEDJz6LJz6X94vs/bDvjh5M3b8mcS2WiMyxCSqHkZ/Hk50/dj36OdX/8id4d2lVriCpAZ1iEiKHkZ/Hk5xLZubmY4LkFE+1s0UJKXmFVooJFSCmU/Cw9+XnxvkMoLCzCr1MnoeBjFFh1oktCQj5SVa2Fjk2bICSfUfKzhOTnS/+EYt/lK7ixcS00a2jVYSpYhHykpKSEFg2M4d65PZzNW1Ly8yd9Ut+9w/StO+DmOAJdSp25VScqWIRIoKmmRsnP+P/k55+2e6FR/XpwGzVSrG91ooJFSBko+VkLRwKv48ydu9g7fw7uPHnK9Xn9Nh15BQW49TgSelpaEp81q2xUsAjh4WtOfr756DEYY5i6WTzcFQBsFi9D304dcH71Crnfq7yoYBHC09ea/Lx6/BgsHDZEbJzVR//AjfAIXP1lTbXdhKeCRUgplPwsmvxsqKcrMZextpYmlJWE3KeI1YEKFiGlUPKzaPLz54SSn4lEX2Py86gRwxF1Mwj7nJ0AUPJzdaHkZ0IqASU/f37oqzmEEIVBBYsQojCoYBFCFAbdwyKkhLIKULs2hI2b1vRMvg4MgKamXEGqVLAI+YRAuzaErdvJ7khqBF0SEkIUBhUsQojCoIJFCFEYVLAIIQqDChYhRGHQp4SEyOHff/+Fj48Pnj9/DnV1dZiYmMDOzg69evWCsrIyCgoKsGTJEtjY2GDQIPGIrKKiIixevBjW1tYYPHiw2Pbk5GRs2bIF1tbW6Nevn8z5XL16FUeOHMGUKVNgbW0ts39ubi52796NW7duIS8vDz169MCsWbMkfj/4zJkzOH36NFJTU9GmTRs4OTmhQQPRlRny8/Nx5MgRBAYGIjs7G02aNMHEiRNhbm4udrzKQGdYhPDk7e2Nb7/9Fj4+PsjNzUV8fDwOHz6Mfv36ISmpOEy1oKAAnp6euH79usRjFBUVwdPTE4GBgWLbbt++jU6dOmH9+vUIDg6WOZ+UlBSMHTsWhw4dQlRUlMz+eXl5sLOzg6ura3FoqqYmVqxYgd69eyMvL0+kr6urK4YOHYrExEQYGxvj6NGj6NixI168eCFyPGtra8yePRsCgQDffPMNbty4gfbt22PXrl2lh68UVLAI4SErKwsLFy6ElZUVXr58iQsXLiAoKAiJiYkIDw+HiYl4VL08tmzZAhsbGwwdOpT3aigzZsxA+/bteY+xf/9+3Lx5E35+fjh27BiOHDmCgIAA3LlzBzt37uT6RUZGYuPGjVi+fDkuXboEb29vhIWFoVatWnB2dub6nTp1Cnfu3IGvry+OHDmC3377DXfv3kWvXr3g7u7O/83LgQoWITwkJCQgKysLAwYMECkoAoEArVu3rtCxc3NzcezYMWzevBnbtm1DzsdUm7Ls27cP/v7+WLVqFe9xjh49CgsLC9ja2nJtlpaWsLa2xqFDh7i2Y8eOQVlZGQsWLODa9PX1MX36dPj5+eHNxxixlJTiNeu7du3K9RMIBLCwsEBaWhoKyoi6Ly8qWITw0LBhQygrK+PGjRuVfmxVVVWEhIRg9uzZKJKQYFPaf//9h/nz5+O3337DN998w2sMxhgePHgAS0tLsW1WVlYICwtDdnY2ACA0NBRmZmbQ1dUV61dYWIh79+5xPwMQOTt7//49zp49C3t7eygrV/4tcipYhMhw+PBh5OXlwcXFBZcvX4adnR1u3rxZ5j5xcXG4fv262EtawVNSUuI1l8LCQowfPx69evXCzJkzeb+HjIwMZGVlSbx0bdiwIRhjiI2NBVB8NimtHwC8fPkSANCpUyesXr0aq1atwvDhw7F//358++230NLSgo+PD++5yYM+JSREho0bN+LFixdYv349jI2N4eHhAWtra7Rq1QoLFy7E5MmTISyV5uzr6wtfX99Kn8v69evx7NkznDp1Sq793r9/D6B41eDSND6uH1/S5/3797z6AYCbmxsiIiJw4sQJ/PXXX9DX18epU6dQp454mnRloDMsQmQQCAQYPnw4AMDJyQkxMTHYv38/VFRUMG3aNPTv3x/5+fki+0ydOhXR0dFirydPnpR7Hvfv38fq1auxb98+1CsjNefs2bPYu3cv9/r333+hoqIC4P8DUj9Vcq+ppEipqKjw6peTkwNbW1tcv34dx44dw+XLl2FmZoaOHTvixIkT5X6fZaEzLELkpKamhsmTJ2PSpElwd3fHunXr4OPjg8mTJ3N9dHV10axZM7F9y3sjOjc3F+PGjYOVlRV0dXW5xx7S0tIAAM+ePUNwcDDat2+PjRs34s6dO9y+q1evxqJFi6CkpMTdMP9UamoqgOIb6wBQt25dXv2WLFmC0NBQhIWFoUmTJgCAPn36YMaMGRg/fjzMzc0r/IFEaXSGRUg5CQQC7uP7sLCwKh0rJSUFT548wY0bN9CzZ0/uNWRIcV7ghg0b0LNnT0RERCA4OBgFBQXcy83NDSoqKmjRogUeP34sduzHjx/DwMAARh+jw9q2bYvIyEgwxsT6AUC7dsXL7/j7+8PGxoYrVgAgFArh6uqK/Px8qc+iVQQVLEIqoOSBTT6pUxVhaGiIyMhIsVfJzf81a9YgMjISHTp0kHqMQYMGISAgABkZGVxbVlYWzp8/D3t7e5F+aWlpuHbtmsj+vr6+MDU1RatWrQAAmpqaSExMFBsn4WPgrJ5e5QfO0iUhITzcuHEDv/76K3r06IFGjRpBXV0dERER+OWXX6Cnp4fx48dX6fjKysowMzMTay95wt7Q0FDi9k/NnTsX3t7eGDZsGFauXAklJSWsXbsWmZmZWLRoEdevf//+sLCwwJQpU7B161aYmpri+PHjuHjxInbt2sV9wDBu3DjMnz8f8+bNw+zZs6Gnp4fQ0FDuKzwDBw6UNpVyo4JFCA96enq4ffs2Dh8+zLUpKytj8ODB8PDwEPuO3efIxMQEfn5+It87NDU1xcmTJ0WemBcIBDh16hQmTZqEoUOL0581NTWxdu1akUcp5s2bB6D4cnTbtm0Aii8JhwwZgk2bNkFHR6fS3wMVLEJ4aNeuHaKjo5GVlYWUlBQIBAKYmJiIPT+lpqYmdu/nU8rKyhXaXpqhoaFc/Xv27ImoqCjEx8dDKBTC2NhYYmiqiYkJAgICkJqaiszMTO7B2dLmzZuHefPmIS0tDenp6TAxMUGtT5KlKxsVLELkoKmpCU0FD1cVCATcQ6CyGBgYwIBHwKq+vj736WFVopvuhBCFQQWLEKIwqGARIoM894hI1aKCRYgMsbGx+N///lfT0yCggkWITFlZWejfv39NT4OAChYhRIFQwSKEKAwqWIQQhUEFixCiMKhgEUIUBn01hxA5yQpTBYDt27ejqKiI+4Jwab///jvy8vJEYrNKFBQUYMuWLVBXV8fs2bNlzkfeMFWAX0hqCVnhrikpKTh48CDu378Pxhhat26Nn376qcxVUcuLzrAIkQOfMFWgOFLryJEjUo9z/PhxkWitEq9evYKNjQ0WLVqE48ePy5yPdvwdeAAAIABJREFUvGGqAL+Q1BKywl3//PNPtGzZElu2bIGysjJUVFSwdetWNG/eHPfv3+c1H3lQwSKEp6oOUw0MDETHjh0BQGIclyTyhqnyDUkF+IW7NmvWDE5OTnj+/Dl8fHzg4+ODhw8fQiAQYNmyZbznxRcVLEJ4qsowVQA4efIkBgwYgKtXr3KhEWUpT5gq35BUvuGuHTt2xKpVq0R+HyYmJrC0tERkZCTvefFF97AI4enTMNWlS5dW+vG3b9/Ora8lK1C1PGGqAL+Q1H79+nHhrkpKSuUKznj79i3q168v936yUMEihIft27fjyJEjcHFxwS+//AI7OzusWLECPXv2lLpPZmam1CCGjIwMscX/yhum+um9M1n4hqTKM5/SHj16hHv37mHjxo3l2r8sVLAIkUFNTQ1dunTBqlWr5ApTjYqKQq9evaQeV557T58qb5gqIF9IanlkZWVh3LhxMDMzw5w5cyp0LEmoYBEig1AoxOTJk6GlpQWgOEx1+vTpOH78OLZs2YJp06bB19cXfn5+Ivee2rZtK7WojBo1qlyXWiVhqn/99ZfMMNXk5GTuZwsLC3To0IF3SGp55OXlYdiwYUhISEBwcLDUG/UVQQWLkHLgE6aqqqoqMUy1ZH95z2YqGqbaoUMH3iGp8srPz4ejoyPu37+PgIAAtGzZslzHkYUKFiEVUBKmum7dumoLU33y5InEe2cbNmzAhg0bEBISIvGZKaD4rO/EiRNgjImET5QOSZVHQUEBRo8ejeDgYAQGBpbrGHzRYw2EVJCihanyCUnlq6RYBQUF4dq1a1VarAA6wyKENz8/P/z5558KHabKNySVrylTpuDkyZOYM2cOgoODxc7srK2tK+UZtRJUsAj56Nq1a9yN9RLv3r1DTk4OPD09YW9vr/BhqnxDUvkKDAwEAOzYsUPidi8vLypYhFSFiIgIzJgxQ6QtPz8fhYWFWLhwIbS0tHiFqQIQueEtibR7THy3f0reMFW+Iaklygp3jY+P5z1uZaCCRchHAoEADx48kNnvSwhTBfiHpH5O6KY7IURhUMEihCgMKliEEIVBBYsQojCoYBFCFAYVLEKIwqCCRQhRGFSwCCEKgwoWIURhUMEihCgM+moOIXLw8/PD2bNn8fr1a+jp6aFp06ZwcHDglnQpKCjAkiVLYGNjg0GDBontX1RUhMWLF8Pa2hqDBw8W2y4rtLS033//nVs/nU9waW5uLnbv3o1bt24hLy8PPXr0wKxZs8RWB42IiICPjw+ePn0KHR0ddOnSBVOnToWqqmq5jldZ6AyLEJ7Gjh0LBwcHBAUFoaioiMv4c3R05PoUFBTA09NTavhEUVERPD09uVUOPiUrtLS0GzduYO7cuTh06BDevXsns39eXh7s7Ozg6uoKoVAITU1NrFixAr1790ZeXh7Xb+nSpejQoQMuXLgAPT09pKenY968eejUqRMyMjLkPl5looJFCA/BwcE4duwYXFxc8OTJE5w7dw5///03UlNTcf78+Qofn09o6acyMjIwYcIE9OnTh/cY+/fvx82bN+Hn54djx47hyJEjCAgIwJ07d7Bz506uX8uWLXHw4EGEhYVh3759OH36NE6dOoXHjx/Dy8tL7uNVJipYhPAQHR0NABg2bJhIe1nrtvPFN7T0U3PmzIGOjg4mTpzIe5yjR4/CwsICtra2XJulpSWsra1x6NAhrm3SpEkYO3asyL4DBw6Eurq6SDgq3+NVJipYhPBQElYq7VKvIkpCS2fPni0zQBUA/vzzT/z55584evQo7xVCGWN48OABLC0txbZZWVkhLCwM2dnZUvfPzs5Gbm4uF45a0eOVF910J4SH7777DlZWVnB3d0dcXBycnZ3RvHlzqf3j4uIkFjdJEVsA/9DShIQE/Pjjj1i7di3atWvHhUfIkpGRgaysLKkhqowxxMbGSl1i+eDBgygqKsLIkSMr5XjlRQWLEBl0dHSwefNm+Pv7w9XVFXv37oWXlxdsbW3h7u4uMSzV19cXvr6+lToPxhgmT56MDh06YMGCBXLtWxIpVp4Q1cjISCxduhSTJk1C586dK3y8iqCCRYgMysrK+PnnnwEUr12+fPly7NmzBzt27ICtrS1WrlzJbS8xdepULFmyROxYhYWF5T7r2LZtG/755x88fPhQJKKr9PEPHDgg0ubg4MAFvMobohoXFwd7e3u0adMG/8fevcfFlP9/AH9N90SKLiq3wrq1LrksIbfo4pJlKfRNuZV1SyaF+MaWFENyZ8WG+LahJWHc07ovIiXsblKUinLpMtT8/lDza5qZ5kzNxOy+n4+HP5z5zGc+s4+H155zZubz2rp1q+B4XeerLwosQqSouZ+5sbExAgICsHDhQkyYMAGrVq2Cq6sr2rVrJxijp6cn9mZ8XdqeASA9PR3+/v7w8vJCRkYGMjIyBMeBz43Qr169Qq9eveDl5SX03M6dO6Nv375QVVWVqUT15cuXGD58OIyMjJCQkCA4c6oaK+t88kCBRUgtbt26he+//17sY02aNIGPjw/Onj2LBw8eCAWWItZRWlqK8PBwhIeHizzu4uICTU1NlJaWSgzFb775Ruw9r9TUVBgYGMDExERwLCcnB0OHDoW+vj7OnDkDPT09oeeoq6vLNJ+80KeEhNQiKysL+/fvl/h41RmOoktUx44dK7ZElcPhAADOnDmD+/fv1zrH6NGjce7cOaEvf3748AEnT56EnZ2d4Fhubq4grLhcrkhYyTqfPNEZFqmT/Px8iZ94/RMFBQXh9evXsLKyQsuWLVFeXo6kpCSEhoaiX79+6Nu3r0JfX1dXF7q6uiLH7927BwCwsLCQ+n2wBQsWYOfOnRg/fjwCAwOhqqqK4OBgvHv3Dr6+vgA+3ygfNmwYMjIysGrVKhw6dEhkHhcXF+jp6TGaT94osIjMrly5gqlTpyrs5xfyxufzsX//flhbW9d5DgMDA2zatAkbN24UHGvSpAm8vLywYsUKmRuTv4SWLVsiPj4e06dPh42NDQCgdevWiI2NRffu3QF8vhSsuszz8/MTO8+QIUOgp6fHaD55o8AiMktNTYWjoyN27NjxpZfCiKqqar1r5L28vODl5YXCwkLk5+ejcePGYi8DtbS0ai01ra2UlMnjNbm4uMDFxYXx+EGDBuHx48fIysqCiooKTE1NhT5xbN++vUyvL20+eaPAIkQGenp6Eu/pKAsWi4VWrVp9tfPV5us/jyWEkEoUWIQQpUGBRQhRGhRYhBClQYFFCFEaFFiEEKVBgUUIURoUWIQQpUGBRQhRGhRYhBClQYFFCFEaFFiEyCA+Ph6zZ8+Gk5MT3N3d8dNPPwm2eAE+74/FZrOF6rCqe/LkCdhsNh4+fCj28T/++ANsNltQKybN1q1b4e7ujlevXjEan5ubi4CAAHz//feYOnUqYmNjax3PZD08Hg8xMTHw8vLCuHHj8MMPPzAux5AVBRYhDDFpfv7777/B4XDw559/ip3j2bNn4HA4YgNg165dGDBgADgcDp49eyZ1PbI2P2dkZKBbt27Ys2cPDAwMUFRUhEmTJoHNZosdz2Q9mZmZ6NOnD9zc3JCdnQ1zc3M0a9YMJSUlUtdTF7RbAyEMXL58WdD8vG7dOsHxsrIyPH/+vF5zFxcXY86cOTh8+DC8vLwQEREh9TnVm5+5XC6j1/H390dFRQXu378v6BcMCwuDn58fpk6dip49e8q0nvLycowbNw7v379HSkpKvQtlmaAzLEIYqNoKWRHNzy9evMDVq1dx/vx5ODk5MXqOrM3PJSUlOHr0KNzd3QVhBQDz589Ho0aNEBUVJfN6jhw5grt37yIqKqpBwgqgwCKEEQsLCwCKaX5u3749Hj16hIEDByqs+TklJQUfP34UaWrW1tZGjx49cO3aNZnXc/ToUbRv3x4DBgxgtAZ5oEtCQmqhpaWFDh06ICkpSabm5wcPHqBx48Yix5OTk8WOV3Tzc3Z2NgBIbGquGcRM1pOSkoLu3bvjypUrWL9+Pf766y+0bt0abm5uQvf15IkCi5BaqKuro2PHjggMDISvry/j5udly5bJfS2KbH6uS0tzbm4uNDQ04ObmhhkzZsDBwQHnzp2Di4sLMjIyJO4JXx8UWITU4sSJE4L7Mzo6Ooybn3ft2iU2yK5evcr4vlNNimx+rktL8+vXr6GhoYF79+7B0NAQwOe97ydPnoxVq1Zh4cKF0NLSknne2lBgEVKLT58+IT4+HqGhoYJjTJqfTUxMxN6IrmpsllV9m5+rAkVSU3NdWpp1dHTg5OQkmLuKk5MTDh8+jCdPnuDbb7+Ved7aUGARUkfK1Pycm5sL4HPjka2trdBjqamp6NOnj8xrMjc3F9TSV1d1FldaWirznNLQp4SE1IOyND8bGxujT58+It9sv3nzJp49e1anpubRo0fj1KlTIt+yv3jxIjQ0NNC5c2eZ55SGzrAIYeCf0PwcEBAAJycnzJ8/Hx4eHsjJyYG3tzfMzc0xdepUmdfEZrMRGRkJe3t7rF27FoaGhvjtt9+wb98+zJ8/X+ynpPVFgUUIA/+E5uexY8di27ZtWL58ObZs2QIA6N+/P/bu3Vunm+76+vpITEzErFmzBGdo2traWLBggdA9P3miwCKEAabNz/b29rU2J9va2tbr8ZpkbX6eM2cOZs6ciczMTOjr60u92S5tPR06dMClS5fw+vVrFBQUoFWrVnL/ZLA6CixCZPBPaH5WV1eX+wcEzZo1q9MnjbL6+s9jCSGkEgUWIURpUGARQpQGBRYhRGlQYBFClAYFFiFEaVBgEVLp7du39d7umCgWBRYhlYqLixX+m0BSPxRYhBClQYFFCFEa9NMcQhgqLS1FVFQUEhMT8f79exgbG8PS0hLjxo1Dq1atAAAJCQm4cOEC1qxZAw0NDZE5Tp8+jXPnziEoKEjsb+5iYmJw8+ZNhIWFSf1BdXl5OdhsNlgsFjZs2MDoPSQnJ2P37t149uwZTE1NMXPmTLF7YTEdl5qaisjISPz5558wMjKCq6srBg0axGgtdUFnWIQw8ObNG/Tp0wdeXl54+vQpPn78iOvXr2PRokX46aefBOMSExPB4XDA4/HEzpOUlAQOhyOyuV1ZWRm8vLzg7OwMDofDqD1nzZo1CA8PR0xMDKP3EB8fDysrKyQlJcHMzAx37tyBtbU14uLi6jTu+PHjsLKywvHjx9G8eXM8fvwYNjY2CA4OZrSeuqAzLEIYiIiIQEpKCuLj4zFq1CjB8YKCAnz8+LFec2dkZGDixIl48eIFpkyZgujoaKnPuX37NoKCgmBra4u0tDSp4z99+oQ5c+Zg8ODB4HK5UFNTQ0VFBcaOHYs5c+bA3t4eWlpajMfxeDzMnDkT1tbWOH36tOBsMiQkBAEBAbCzs0Pv3r3r9d9FHDrDIoSB9PR0aGpqwtHRUeh48+bN6/3J4o0bN8BisXDz5k1GuygUFxfD1dUVHh4e6NixI6PXuHz5MrKysrB48WKoqX0+T1FRUYGvry9ycnJw5swZmcZdv34deXl5WLhwodCl75IlS2BiYoJ9+/bJ8p+AMQosQhiwsLBAWVkZrl+/Lve5nZ2dce3aNZiZmTG6FGSz2SgvLweHwxG7f7s4d+7cAQCRItV+/fpBRUVFUKTKdFzVtshmZmZC41RVVdG7d2/cuHGD0bpkRZeEhNSicePG0NPTw48//ojt27fDwcEBy5Ytw8yZM2vd/+nKlStid/F89uyZ2PFMi1RPnTqF3bt3IykpCTo6OszeBD4XqWppaaF58+ZCxzU1NWFoaCho4WE6rk2bNgCAp0+fCl368fl8PH36tE49h0xQYBFSicVi4fbt20JB8+nTJ/j7+8PU1BS3b9/G3Llz4efnh5UrV8LZ2RkrVqwQu5d6zUtHecjPz8f06dMREBCA7777Tqbnvn//XuI2yNWLVJmO6969O7755husWrUKVlZW+Oabb/DmzRv4+fnh8ePHsLCwkGl9TFFgEVLN//73P1hbWwv+Xn1vcnNzcyQkJCAlJQVbtmzBvn37EBsbiyNHjsDe3l5onuTkZDRq1Ehk/o0bN2Lbtm11Wtvs2bPRtm1bBAQESByTlZWF06dPC/6uoqKC6dOnQ11dXWyJKiBcpMp0nIaGBg4fPgwXFxd07NgRurq6KC4uhpeXFwYMGMDo0rYuKLAIqUZdXV3o+1FqamooKSkRGmNpaYkdO3bA19cXgwcPhqenp8ilnoWFhdjWGH19/TqtKyoqCnFxcdi7d6/gPhIA5OTkgMfjISkpCfr6+sjOzhYqUlVTU8P06dNhaGiId+/egcfjiXw/rKCgQHB5y3QcAPTs2RMpKSl4+PAhcnNz0aVLF7Rq1Qrm5uZCoS9PFFiE1FG7du3g6uqK0NBQFBYWKnSv98TERPD5fLi7u4t9fNCgQbCzs8Pp06fF3oi3tLQEn8/Ho0eP0K1bN8HxjIwMFBcXC44xHVdFXV0dPXr0EPz96dOnyMjIwPLly+vzdiWiTwkJqYf09HTo6OgopIOvuqCgILFFqs7OzjA2NkZaWhp+/vlnic+3tbWFpqamSJFqTEwMWCwWRo4cKdM4cSoqKuDj44NmzZrJ1OQjCzrDIoSByZMno0uXLujUqRNMTU1RWFiI2NhYxMXFYcmSJYLvLClKixYtxH7fS09PD2pqaujUqVOtz2/WrBnmzp2LdevWwdjYGAMHDsStW7ewevVqODs7o0OHDjKNA4C///4bHz58QNOmTZGamop169bh0qVLOHLkiMICnAKLEAYaNWqEkJAQoftZrVq1wqZNmzBv3rwvuDLmQkJCUFxcDB8fH/B4PKioqGDy5MnYuXNnncYdOXIEvr6+AD5/wjp48GBcvnwZAwYMUNh7YAHgv3z5ktG3dbW1tfHmzRuFFiWSr8OiRYvQpk0beHt7izy2c+dO3L17Fzt27PgCK5Odqqoqrly5UuuN4G+//Rapqam4dOmS0I93g4ODUVJSgqCgIFRUVCA/Px+FhYUwNjZG06ZNG2L5cvf+/Xvk5OTAzMys1sZnaeM+ffqE58+fg8/no0WLFmI/FZWXnJwcmJiY0BkWIUypqKjAyMgIRkZGX3op9dK4cWOx3x2TdZyamhrMzc3luTSp6KY7IURpUGARQpQGBRYhRGlQYBFClAYFFiFEaVBgEUKUBgUWIURpUGARQpQGBRYhRGlQYBFClAb9NIcQhl6+fInIyEjcu3cPfD4fJiYm6N+/P0aPHg1dXV0ADVukmp2djYCAAPTv3x+zZ89m9B6YFKR+/PgRBw8exMWLF/Hu3TuYm5vDzc0N3bt3F5nvzJkzOHr0KHJycmBqaorRo0cL1aDJG51hEcLA7du30alTJwQHB+P169d49+4dTp8+jalTpyI+Pl4wrqGKVKs289u3bx8SExMZvQcmBakPHjxA9+7dMW/ePLx9+xb6+vo4ceIErKysRHZr8PHxgb29PTIzM9GhQwdkZWVhzJgxmDJlCqP11AWdYRHCgK+vL9TU1PDgwQO0bt1acPzp06do2bJlveauS5Hqpk2b8PDhQ1haWjJ6DaYFqa1bt4atrS2WLl0KExMTAJ/PuGxsbLBkyRJ4eHhAQ0MDOTk5CA8Ph4+PDzgcjuB1Vq1ahcDAQCxduhTffvtt3f6D1ILOsAhhID09Hb179xYKKwBo3759vbdbkrVI9eHDh1i6dCk2bNgAPp/P6DWYFqQ2bdoUERERgrACPm+D7OTkhLdv3yI7OxvA5wYfPp8v0t7Tt29fAP/fWyhvFFiEMGBhYYE7d+7g7du3cp9bliJVHo8HV1dXjBs3Di4uLnIvUpXkzZs3UFVVhYGBAYDPQW1kZIQ9e/agrKxMMC46OhpGRkaC4JI3uiQkRIqysjIsW7YMY8aMQZ8+fRAYGIgJEyaIvaleRVFFqitWrEBBQQG2b9/ObPGVmBakilNaWopDhw7B3t4eTZo0AQBoaWkhKioK48ePR//+/bFgwQJER0fj/v37OHHihGCcvFFgEVKLZcuWYdmyZXB0dASXy4W3tzemTJkCQ0NDeHp6gs1mi915VBFFqomJidiwYQO4XK7MDT1MC1LFmTdvHgoKCrBu3Tqh43Z2dggNDcX8+fPh4eEBFouFgwcPKuzsCqDAIqRWLBYLISEhAIDhw4fj/v374HK5iIiIQFBQEPbv34/ExESRe1vyLlJ9+/Yt3Nzc4O3tjaFDh0ocd+vWLSQnJwv+bmZmBgcHB8YFqTUFBgZi7969OHz4MDp37iz02JIlSxAeHo7Vq1fD0dER4eHhmDJlCm7cuIHw8HCZ3yMTFFiEyIDFYsHOzg52dnY4efIknJycsGLFCvzyyy9C4+RdpOrt7Y3i4mI4ODggKSlJcLykpAR5eXlISkpC27ZtERcXJ9RWPXz4cDg4OMhUkFpl/fr1+OmnnxAZGYmJEycKPRYXF4d169YhJiZG8Nj+/fsxYsQITJs2DV27dsWsWbPq9F5rQzfdCamjUaNGoXfv3kJnNIqSmJiIvLw8DB8+HIMGDRL8yczMBJfLxaBBg3DgwAEEBwfj06dPgj9Vn/5VL0itTlJB6saNG+Hv7499+/Zh2rRpIuvhcrlo0qSJSJC5ubnB1NQUZ8+elfN/gc/oDIuQOiotLUVmZqbIP3ZF4HK5Yr+M6ujoCEtLS4SFhdVajlG9ILX6esUVpG7atAm+vr6IioqS+CVQHR0dFBcXizRef/jwAYWFhXU+k5SGAosQKV69egV3d3eMHDkSFhYWaN68ObKysrBlyxbk5ORg9+7dCl+DhYWF2OMaGhrQ1dWVW5FqZGQkvL29MXLkSLx9+1akyq19+/awtbXF5MmTsXHjRvzwww8ICQmBubk5MjMzsXz5cvB4PMyYMUM+b7wGCixCpNDS0kJBQQHYbLbgxjWLxULv3r2RkJAAe3v7L7xCZpgUpF64cAHA5zM6LpcrMoezszNsbW1hZWWFkydPwt/fX+hTwV69eoHL5Srsk0IqUiViUZGqKB6Ph7y8PJSUlKBly5ZK+++AaZEqUx8+fEBVhiiqop6KVAmppqKiAhUVFYiOjpYYWBoaGjAzM2vglckf0yJVpnR0dOQ6X23oU0JCAMFPYhS50wCpPwosQgC8ePHiSy+BMECBRQhQ609TyNeDAosQojQosAghSoMCixCiNCiwCCFKgwKLEKI0KLAIIUqDAosQojQosAgR4969e2Cz2fj+++8xZcoULFmyBGfPnhWUPnz69AlsNluok7C6iooKsNlsHD9+XOzjr169wrJly3D69GlG6zl//jzc3d0ZdxCWlZVh8+bNcHFxwfjx47FhwwaRLkRZ1vPx40dERkbC1dUVkyZNwrp161BUVMRoLfJEgUVIDTt37kSvXr1w4MABlJWVISsrC1FRUbC3t0dOTg6Az4HF4XBw6dIlsXNUVFSAw+EIdj+o7urVq7CyskJISIjQ7qGS5OXlYerUqfjll1/w+PFjqeN5PB5GjBgBPz8/qKioQEdHBytXrsTw4cPF7qklbT0fP36Era0tPD098f79ezRu3BhhYWHo1asXnj9/LnU98kSBRUg1paWlWLx4MaytrZGRkYGEhAQkJibi5cuXePDgQb1LU8PDwzFkyBCMGzeO8W4Ps2fPFlsTL0lkZCSuXLmC+Ph4REdHY//+/Th37hyuX78usp88k/Vs3boViYmJOHnyJOLi4hAZGYkHDx7g48ePmDdvHuN1yQMFFiHV5OXl4cOHD3B0dBT6B8xisdClS5d6zV1WVobo6Ghs3LgRERERtV6iVdmzZw+4XC5WrVrF+HUOHjyI3r17Y9iwYYJj/fr1g42NjdDe80zXc/z4cfTo0UNoV9IWLVpg2bJliI+PV1hpqjgUWIRUY2RkBDU1NVy+fFnuc2tqauLatWuYO3eu1MJUAPjrr7/g7e2NDRs2oG3btoxeg8/n4+7duyKFqQBgbW2N5ORkFBcXy7SeV69eid1W57vvvkNFRQVu3brFaG3yQPthEVKNpqYm2Gw21q5dixEjRmDlypUS98cCgOfPn4u9jyWpUotpYWp5eTn+85//YOjQofD09BTcO5OmqKgIHz58EHvp2qpVK/D5fGRmZgq2VGaynjZt2uDPP/8UOV51Py0vL4/R2uSBAouQSiwWCxcuXEBISAhMTU0RFBQEGxsbdO7cGYsXL4aHhwdUVIQvSmJiYhATEyP3tYSEhODp06c4duyYTM+r2nVC3E6iVT2Jsu5MMWnSJLi7u2Pt2rVYvHgx1NXVcf78ebDZbABo0J1XKbAIqWbhwoUAgPnz52PWrFk4dOgQwsPDMXPmTMTExCA+Ph7q6uqC8TNmzIC/v7/IPOXl5VKLIST5448/sHr1ahw9erTWJpzjx48L3T/q3bs3TExMBK9fU9VXMmTdFnnatGl48OABli9fjpUrV0JTUxPNmzeHj48PFi1aBGNjY5nmqw8KLEIk0NLSgoeHB9zd3REQEIA1a9bgwIED8PDwEIzR09MTuz1wVTjIqqysDK6urrC2toaenp7gawavX78GADx9+hRJSUno3r07wsLCcP36dcFzV69eDV9fX6iqqqKgoEBk7vz8fAAQW5oqzfr16+Hr64uUlBRoa2ujb9++OHjwIADU+5NTWVBgESIFi8USBJaiS1Pz8vLw6NEjPHr0SOy9s9DQUISGhuLatWsSv8P1zTffIDU1VeR4amoqDAwMBGdhsjI2NhY6mzp79izMzMwEFWENgQKLEAaqbjAzaZeqjxYtWiAtLU3keH5+PgYNGoSffvoJP/zwQ62fGo4ePRo7duxAUVERmjZtCuBzs83JkydhZ2cnl3Vev34dhw8fxurVq+UyH1MUWIRUc+bMGSQkJGDgwIFo06YNtLW18fDhQ6xduxb6+vr4z3/+o9DXV1NTE3vvq+pTwhYtWki9N7ZgwQLs3LkT48ePR2BgIFRVVREcHIx3797B19e3Tuu6cuUK2rZti7dv3+LkyZNvi3wDAAAgAElEQVQICgrCd999J7jx3lAosAippnnz5rh69SqioqIEx9TU1DB27FgEBQUpRc1Xy5YtER8fj+nTp8PGxgYA0Lp1a8TGxsr0jfnqHBwc8OHDBwCfv6s2b948rFy5EhoaGnJbNxMUWIRU07t3bzx58gQfPnxAXl4eWCwWWrZsKfJ9JS0tLfD5fInzqKmp1evxmlq0aCHT+EGDBuHx48fIysqCiooKTE1NwWKx6ryezMxM5OXlQU9PD4aGhiJf72goFFiEiKGjowMdHZ0vvYx6YbFYaNWqlVzmatasWZ0+XZQ3+mkOIURpUGARQpQGBRYhRGlQYBFClAYFFiFEaVBgEUKUBgUWIURpUGARQpQGBRYhlTQ1Nb/0EogUFFiEVGJSCkG+LAosQojSoN8SEiJGfHw8jh8/jtzcXOjr66Ndu3YYM2YMevToAeDzjqL+/v4YMmQIRo8eLfL8iooKLFmyBDY2Nhg7dqzI469evUJ4eDhsbGxgb28vdT1bt27FrVu3EBYWVuu2yVXKysqwa9cu/P777+DxeBg4cCB+/PFHkf3XHz58iAMHDiA9PR26urro27cvZsyYIfHy+I8//sChQ4fg6enZoBv3VaEzLEJqmDp1KsaMGYPExERUVFQgLS0NYWFhcHZ2FoxpyObny5cvY8GCBfjll1/w9u1bqeOZNj8vXboUPXr0QEJCAvT19VFYWIiFCxfCyspKbA39rl27MGDAAHA4HDx79kzqOhSBAouQan7//XdER0eDzWbj0aNHOHHiBG7cuIH8/HycPHmy3vPL2vxcVFQENzc32NraMn4Nps3PHTt2xL59+5CcnIw9e/YgLi4Ox44dQ2pqKrZv3y4YV1xcjGnTpmH+/Pnw9PSU7Q3LGQUWIdU8efIEADB+/Hih45qammLLJmRRl+bnefPmQVdXF9OmTWP8Okybn93d3TF16lSh544aNQra2tpC2zS/ePECV69exfnz5+Hk5MR4HYpAgUVINVV7pUu61KsPWZuff/31V/z66684ePAg4w3zZGl+Fqe4uBhlZWVCZRPt27fHo0ePMHDgQEbrViS66U5IJRaLhREjRsDa2hoBAQF4/vw5Fi1aVOvNZUU1P2dnZ8PLywvBwcHo1q2b2BYccWRtfq5p3759qKiowMSJE+u0bkWjwCKkEovFwvr168HlcuHn54eff/4Z27dvx7BhwxAQEIChQ4eKPEcRzc98Ph8eHh7o0aMHfHx8ZHpufZqf09LSsHTpUri7u6NPnz4yrrphUGARUs1///tfAMCWLVuwYsUK7N69G1u2bMGwYcMQGBgoeLyKIpqfIyIicPv2bdy/f1/iPuzl5eXYu3ev0LExY8YIWqllbX5+/vw57Ozs0LVrV2zdurVO624IFFiESGBsbIyAgAAsXLgQEyZMwKpVq+Dq6op27doJxsi7+Tk9PR3+/v7w8vJCRkYGMjIyBMeBz9+DevXqFXr16gUvLy+h53bu3Bl9+/aVufn55cuXGD58OIyMjJCQkCA4E/saUWARIkWTJk3g4+ODs2fP4sGDB0KBJW+3bt1CaWkpwsPDER4eLvK4i4sLNDU1UVpaKjEUZWl+zsnJwdChQ6Gvr48zZ85AT09Pfm9GASiwCGGg6gxH0c3PY8eOFdv8nJCQgMWLF+PMmTO1tj4DzJufc3NzBWF1+vRpwdivGQUWIdUEBQXh9evXsLKyQsuWLVFeXo6kpCSEhoaiX79+6Nu3r0JfX1dXF7q6uiLH7927BwCwsLCQ+n0wJs3P79+/x7Bhw5CRkYFVq1bh0KFDIvO4uLh8dWdcFFiEVGNgYIBNmzZh48aNgmNNmjSBl5cXVqxY8cUKRGXBpPk5JydHcNno5+cndp4hQ4ZQYBHyNfPy8oKXlxcKCwuRn5+Pxo0bi70MbOjmZxcXF7i4uDAeL635uX379jK9fhVbW9s6PU9eKLAIEUNPT++rO7uQlTybn78WX//5LSGEVKLAIoQoDQosQojSoMAihCgNCixCiNKgwCKEKA0KLEKI0qDAIoQoDQosQojSoMAihCgN+mkOIWJIK1JNT0/H7t27MWPGDHTu3Fnk+U+ePMHOnTvh4eGBrl27ijwuayGprEWqubm52Lx5Mx4+fIhGjRrh+++/xw8//CAyTpYiVR6Ph7i4OFy4cAE5OTlQU1PD6tWr0aVLF6nrkRc6wyKkUtWPepkUqf7999/gcDj4888/xc717NkzcDgcQW1YdbIWkspapJqRkYFu3bphz549MDAwQFFRESZNmgQ2my00TpYi1czMTPTp0wdubm7Izs6Gubk5mjVrhpKSEqnrkSc6wyIEn8NKU1MTly9fFhSprlu3TvB4WVkZnj9/Xq/XKC4uxpw5c3D48GF4eXkhIiJC6nOqF6lyuVxGr+Pv74+Kigrcv39fUNcVFhYGPz8/TJ06FT179gTw/0Wq1bsJ4+PjMWbMGGzfvl2wV315eTnGjRuH9+/fIyUlpd79jPVBZ1iEVCorKxPsLKqIItW6FJLKWqRaUlKCo0ePwt3dXahbcP78+WjUqBGioqIEx5gWqR45cgR3795FVFTUFw0rgAKLECEWFhYAFFOkKmshaV2KVFNSUvDx40eRIlVtbW306NED165dq/X54opUjx49ivbt22PAgAGM1qBIdElISCUWi4Vhw4bJVKT64MEDNG7cWOR4cnKy2PGKLlLNzs4GAIlFqtKCWFyRakpKCrp3744rV65g/fr1+Ouvv9C6dWu4ubkJ3ddrCBRYhFTS1tbGTz/9JFOR6rJly+S+DkUWqUoqUQUkF6nm5uZCQ0MDbm5umDFjBhwcHHDu3Dm4uLggIyND4hbLikCBRUg1shap7tq1S2yQXb16lfF9p5oUWaQqLsiA2otUX79+DQ0NDdy7dw+GhoYAPm8lPXnyZKxatQoLFy6ElpaWzO+zLiiwCJGASZGqiYmJ2BvRVQWosqpvkWpVoEgqUq1ZogpIL1LV0dGBk5OTYO4qTk5OOHz4MJ48eYJvv/22Tu9XVhRYhEihTEWqubm5AD6Xptra2go9lpqaKnSpBzArUjU3Nxe0RldXdRZXWlrK/A3WE31KSAgDDV2kWvMPh8MBAJw5cwb379+X+HxjY2P06dMHsbGxQsdv3ryJZ8+eSSxS5XK5Eks3Ro8ejVOnTuHVq1dCxy9evAgNDQ2x3/RXFDrDIqSaf0KRakBAAJycnDB//nx4eHggJycH3t7eMDc3F3zvSpYiVTabjcjISNjb22Pt2rUwNDTEb7/9hn379mH+/PliPyVVFAosQqr5JxSpjh07Ftu2bcPy5cuxZcsWAED//v2xd+9ewU13WYpU9fX1kZiYiFmzZgnO0LS1tbFgwQKEhoY2wDv6fywA/JcvXzI61dXW1sabN28a7BMB8uUsWrQIbdq0gbe3t8hjO3fuxN27d7Fjx44vsDLZqaqq4sqVK7C2tpY4RkVFRehjf2lFqsrg48ePyMzMhL6+vtib7XXx+vVrFBQUoFWrVg2aAzk5OTAxMaEzLELE+ScUqaqrq8v9A4JmzZrJLfzq4us/vyWEkEoUWIQQpUGBRQhRGhRYhBClQYFFCFEaFFiEEKVBgUUIURoUWIQQpUGBRQhRGhRYhBClQT/NIaSG0tJSREVFITExEe/fv4exsTEsLS0xbtw4tGrVCkDDFqmWl5eDzWaDxWJhw4YNjN4D0yLVKjExMbh58ybCwsJEfuBdtdaaqraUbmj8ly9f8pnQ0tLil5SUMBpLlJu3tzd/48aNYh/bsWMH39PTs4FXVHcqKir833//vdYxLBaLr6Ojw3/9+jXf0tKSz2Kx+N999x3f0dGR361bN76qqip/1qxZgvGnTp3iA+CfOHFC7Hxnz57lA+AfO3ZM5LGdO3fyNTU1+QD4Z8+elbr+1atX8wHwzczMpI7l8/n8v//+m29kZMRv0aIFf+bMmfxRo0bxWSwWf/HixSJjS0tL+Z6ennwAfAD8jx8/iozZtGkTn8Vi8du1ayf0p2fPnozWIw8vX77kA+DTGRYh1URERCAlJQXx8fEYNWqU4HhBQQE+fvxYr7nrUqR6+/ZtBAUFwdbWVqgrsDZMi1QzMjIwceJEvHjxAlOmTEF0dLTY+fLy8mBsbIynT58yfKeKQ/ewCKkmPT0dmpqacHR0FDrevHnzem8zI2uRanFxMVxdXeHh4YGOHTsyeg1ZilRv3LgBFouFmzdv1rqrQ15eHgwMDBi9vqJRYBFSjYWFBcrKynD9+nW5zy1rkSqbzUZ5eTk4HI7Y/dvFkaVI1dnZGdeuXYOZmVmt6/maAosuCQmpxOfz8eOPP2L79u1wcHDAsmXLMHPmzFr3f1JUkeqpU6ewe/duJCUlQUdHh9kbgOxFqkzWk5eXh5ycHMyYMQOFhYUwNTXFwIEDMWnSJIk1ZIpCZ1iEVJo3bx5MTU1x+/ZtWFtbw8/PD6amppg2bZrE+zfLli3D0KFDRf6w2ew6ryM/Px/Tp09HQEAAvvvuO5meW58iVUkGDhwIAwMDlJaWQltbG0lJSXBxcYG1tTXevn0r83z1QWdYhFSqugw0NzdHQkICUlJSsGXLFuzbtw+xsbE4cuQI7O3thZ6jiCLV2bNno23btggICJA4JisrC6dPnxb8XUVFBdOnT69zkWpt1qxZI3Jsx44dmDNnDsLCwhAUFCTznHVFgUWIBJaWltixYwd8fX0xePBgeHp64tmzZ0Jj5F2kGhUVhbi4OOzdu1foflNOTg54PB6SkpKgr6+P7OxsoSJVNTU1TJ8+vU5FqnXh5eWFNWvW4PLly3KZjykKLEKkaNeuHVxdXREaGorCwkKF7vWemJgIPp8Pd3d3sY8PGjQIdnZ2OH36tNgb8VVfUmVapFofTZo0AZ/Pl9t8TNA9LEIYSE9Ph46OjsI7+IKCgsQWqTo7O8PY2BhpaWn4+eefJT5fliLV+nj69CkeP34s1wBkgs6wCKlm8uTJ6NKlCzp16gRTU1MUFhYiNjYWcXFxWLJkCdTUFPtPpkWLFmK/76Wnpwc1NTV06tRJ6hxMilSZev78ORYtWgQnJydYWFhAU1MTd+/exZo1a9C0aVP4+PjINF99UWARUk2jRo0QEhKCkpISwbFWrVph06ZNmDdv3hdcGXNMilSZatKkCfLy8uDh4SG4ka+qqgpbW1uEh4cLflvZUKhIlYj1byxSHTRoEC5fvoyKigrk5+ejsLAQxsbGaNq0aQOuVn7kWaTK4/GQm5uL0tJSmJqayvTdMHmgIlVCJFBRUYGRkRGMjIy+9FLqRZ5FqhoaGg1+NiUO3XQnhCgNCixCiNKgwCKEKA0KLPKP17x5c8FPVohyo8Ai/3hmZmZISEiQOq6hf8hLZEeBRf4VmGyYV32HUfJ1osAipNIvv/zypZdApKDAIoQoDQosQojSoMAihCgNCixCiNKg3xISIkF8fDyOHz+O3Nxc6Ovro127dhgzZgx69OgB4POWw/7+/hgyZAhGjx4t8vyKigosWbIENjY2GDt2rMjjr169Qnh4OGxsbES2XhZn69atuHXrFsLCwhj9zrGsrAy7du3C77//Dh6Ph4EDB+LHH38U2bzg4cOHOHDgANLT06Grq4u+fftixowZ0NTUrNM4RaIzLELEmDp1KsaMGYPExERUVFQgLS0NYWFhcHZ2Foz59OkTOByOSBNNlYqKCnA4HFy4cEHksatXr8LKygohISFISkqSup7Lly9jwYIF+OWXXxh9X4zH42HEiBHw8/ODiooKdHR0sHLlSgwfPhw8Hk8wbunSpejRowcSEhKgr6+PwsJCLFy4EFZWVigqKpJ5nKJRYBFSw+XLlxEdHQ02m41Hjx7hxIkTuHHjBvLz83Hy5Ml6zx8eHo4hQ4Zg3LhxjLZqKioqgpubm8iWx7WJjIzElStXEB8fj+joaOzfvx/nzp3D9evXsW3bNsG4jh07Yt++fUhOTsaePXsQFxeHY8eOITU1Fdu3b5d5nKJRYBFSQ3p6OgBg/PjxQsc1NTXFFk7IoqysDNHR0di4cSMiIiJQWloq9Tnz5s2Drq6uTC08Bw8eRO/evTFs2DDBsX79+sHGxkbo+2bu7u4iu5COGjUK2traSEtLk3mcolFgEVJNeXk5LCwsAEDipV59aGpq4tq1a5g7dy6j9udff/0Vv/76Kw4ePAgVFWb/XPl8Pu7evSvS/gwA1tbWSE5ORnFxscTnFxcXo6ysTKjqvj7j5IluuhNSjZeXF8zMzGBtbY2AgADBnuYdOnSQ+Jznz5+LDTdx3YAA8/bnqiqv4OBgdOvWDampqYyeV1RUhA8fPkhsf+bz+cjMzJS4P/y+fftQUVGBiRMn1vo6TMfJEwUWIdXExcUhLS0Nvr6+8PPzw88//4zt27dj2LBhCAgIEFuaGhMTg5iYGLmug8/nw8PDAz169JC56EFa+3P1MTWlpaVh6dKlcHd3r7URh+k4eaPAIkQMHR0dbNmyBStWrMDu3buxZcsWDBs2DIGBgfjvf/8rNHbGjBnw9/cXmaO8vJxRy404ERERuH37Nu7fvw8WiyV2THl5Ofbu3St0bMyYMVLbnwHxYfb8+XPY2dmha9eu2Lp1q8S1MR2nCBRYhNTC2NgYAQEBWLhwISZMmIBVq1bB1dVVaK90PT09sTfjxRWdMpGeng5/f394eXkhIyND0CJd9WHAH3/8gVevXqFXr15C7c8A0LlzZ/Tt2xeqqqoS258BiJRSvHz5EsOHD4eRkRESEhIEZ2I1MR2nKBRYhDDQpEkT+Pj44OzZs3jw4IHcyh3EuXXrFkpLSxEeHo7w8HCRx11cXKCpqYnS0lKJofjNN9+IveeVmpoKAwMDmJiYCI7l5ORg6NCh0NfXx5kzZyQ2WzMdp0gUWAwcOHBA4g3Uf6r09HS0adPmSy/jq1J1hsOkEq8+xo4dK/arAgkJCVi8eDHOnDmDtm3b1jrH6NGjsWPHDhQVFQlqyj58+ICTJ08KtT/n5uYKQuj06dMSK82YjlM0CiwpduzYgcjISHTp0uVLL6VBZWdnN+g3mL8mGzZsQGlpKaysrNCyZUuUl5cjKSkJoaGh6NevH/r27avQ19fV1YWurq7I8Xv37gEALCwspH4fbMGCBdi5cyfGjx+PwMBAqKqqIjg4GO/evYOvry+Azzfehw0bhoyMDKxatQqHDh0SmcfFxQVqamqMxjXEGRcFlhRFRUUYNmwY1q5d+6WX0qAWLVqktAWi9dWsWTOEhoZi48aNgmNNmjSBl5cXVqxYwfj7UF9Sy5YtER8fj+nTp8PGxgYA0Lp1a8TGxqJ79+4APl/iVV02+vn5iZ1nyJAhUFNTYzSOAouQL8Dd3R1sNhuFhYXIz89H48aNxV4Gamlpgc/nS5xHTU2tXo/X5OLiAhcXF8bjBw0ahMePHyMrKwsqKiowNTUV+sSxffv2jF9flnUqEgUWIRLo6el9kRvL8sRisb6KxmZ5+frPbQkhpBIFFiFEadAlISGVSkpK6vxlT9Iw6AyLkEpFRUXg8/kN/nMTwhwFFiGVWCwWNDQ0MHfu3C+9FCIBBRYhRGlQYBFClAYFFiFEaVBgkX+9lJQUAGC0ZTH5siiwyL/ehw8fAEApfiP4b0ffwyJEAipSlVyQWl5eDjabDRaLhQ0bNkhdi7zQ/1IIEYOKVGsvSF2zZg3Cw8Plvpe9NBRYhNRw9epVKlKtpSD19u3bCAoKkmk98kKBRUgNT58+BUBFquJ2PS0uLoarqys8PDzQsWNHxuuRFwosQmqo2hqailRFC1LZbDbKy8vB4XC+yO8u6aY7IdXY2dnB1taWilTFFKSeOnUKu3fvRlJSEnR0dBitRd4osAipZu/evVizZg24XC4VqVYrSM3Pz8f06dMREBCA7777Tqb1yBMFFiHVqKurC4pSqUj1/82ePRtt27ZFQEBAnd6PvFBgEVILKlIFoqKiEBcXh7179+LatWuC4zk5OeDxeEhKSoK+vj66du1ap/crCwosQhj4NxepJiYmgs/nw93dXexrDRo0CHZ2djh9+rQM77JuKLAIYejfWqQaFBQENpstcjwwMBCXLl3CpUuX0LhxYxnfZd1QYBFSQ1BQEF6/fk1Fqvh8NteiRQuxIa2npwc1NbU636erCwosQiotXrwYAGBgYIBNmzZRkSoariCVKQosQvD5awQREREICQmBl5cXvLy8qEhVih07dtT5uXVFgUWIBFSk+vX5+s9tCSGkEgUWIURpUGARQpQGBRYhRGlQYBFClAYFFiFEaVBgEUKUBgUWIURpUGARQpQGBRYhRGnQT3MIqaG0tBRRUVFITEzE+/fvYWxsDEtLS4wbN07wM5f09HTs3r0bM2bMQOfOnUXmePLkCXbu3AkPDw+xG9v98ccfOHToEDw9PWvdLx6oW2lpbm4uNm/ejIcPH6JRo0b4/vvv8cMPP4iMO3v2LI4dO4YXL17AxMQEDg4OQqWvFy9erLXaTF1dHSEhIYzWJA90hkVINW/evEGfPn3g5eWFp0+f4uPHj7h+/ToWLVqEn376STDu77//BofDwZ9//il2nmfPnoHD4eDJkycij+3atQsDBgwAh8PBs2fPpK5J1tLSjIwMdOvWDXv27IGBgQGKioowadIkoT2t3r59i1GjRsHe3h6PHj2CoaEhHjx4ACcnJ7i6ugrGPX78GHFxcWL/bNu2TWJ3oaLQGRYh1URERCAlJQXx8fEYNWqU4HhBQQE+fvxYr7mLi4sxZ84cHD58GF5eXoiIiJD6nOqlpeI29RPH398fFRUVuH//vqCqKywsDH5+fpg6dSp69uwJXV1d9OjRA4GBgUJlE2w2GxwOB/PmzUO/fv3g6ekJT09Pkdd4+/YtWrVqJRRuDYHOsAipJj09HZqamnB0dBQ63rx583rvNPrixQtcvXoV58+fh5OTk9TxdSktLSkpwdGjR+Hu7i7UKzh//nw0atQIUVFRgmPBwcFCYQVAcNkoLRx37NiB9+/fw9vbm9G65IUCi5BqLCwsUFZWhuvXr8t97vbt2+PRo0cYOHAgoxLVupSWpqSk4OPHjyIlqtra2ujRo4dQiYQ4b968AQCxJapVeDweNm3ahLFjx9a7CVtWdElISCUWi4Uff/wR27dvh4ODA5YtW4aZM2eKNMxU9+DBA7H7mScnJ4sdz7REta6lpdnZ2QAgsURVWpt1ZGQkDAwMxPYvVjlw4ABevHgh2KG1IVFgEVJpwYIFMDU1xe3btzF37lz4+flh5cqVcHZ2xooVK8SeTSxbtkzu66hPaam0ElVJBarA5yCKjY3Fvn37xD4f+Lwz6/r169G3b18MHDhQprXJAwUWIZXOnj2LNWvWwNzcHAkJCUhJScGWLVuwb98+xMbG4siRI7C3txd6zq5du8SejVy9ehXTpk2r0zqYlJZmZWUJ1WqpqKhg+vTpUktUJQURl8vFjBkzMH/+/FrXffz4caSlpeF///sf07cjVxRYhEhgaWmJHTt2wNfXF4MHD4anp6fI1xBMTEzEnnlVlZ/KimlpaXZ2tlCJqpqaGqZPnw5DQ0MAkFiiKu7y9vLly/j+++/h5uaGTZs21bq+sLAwtGnTBhMmTKjT+6svCixCpGjXrh1cXV0RGhqKwsJChe7zLktpqbgb8VVfUk1NTYWtra3QY6mpqSKfCl65cgWjRo3Cf/7zH2zfvl2opKKmq1ev4urVq9iwYQPje3HyRp8SEsJAeno6dHR0FF4YGhQUhLS0NJE/zs7OMDY2RlpaGn7++WeJzzc2NkafPn0QGxsrdPzmzZt49uyZUInq77//DkdHR0ybNk1qWAFAaGgodHV1MXPmzPq9yXqgMyxCqpk8eTK6dOmCTp06wdTUFIWFhYiNjUVcXByWLFkCNTXF/pORR2lpQEAAnJycMH/+fHh4eCAnJwfe3t4wNzfH1KlTAXz+FNPBwQEGBgb49ttvsXPnTqE5GjVqBDc3N8HfHz16hBMnTmDx4sVo0qRJPd9l3VFgEVJNo0aNEBISgpKSEsGxVq1aYdOmTZg3b94XXBlzY8eOxbZt27B8+XJs2bIFANC/f3/s3btXcNP91q1bePfuHd69e4c5c+aIzGFsbCwUWOvWrYOqqioWLFjQMG9CAgosQqrZs2cPdu/ejfz8fBQWFsLY2BhNmzYVGWdvb19rCamtrW29Hq9J1tLSOXPmYObMmcjMzIS+vr7IzfaZM2fKdGm3Z88e7NmzR6Y1KAIFFiE1qKiowMjICEZGRl96KfWirq6Odu3afellyBXddCeEKA0KLEKI0qDAIoQoDQosQojSoMAihCgNCixCiNKgwCKEKA0KLEIqaWhofOklECkosAiplJeX96WXQKSgwCKEKA36aQ4hNbx8+RKRkZG4d+8e+Hw+TExM0L9/f4wePRq6uroAgISEBFy4cAFr1qwReyl5+vRpnDt3DkFBQdDS0hJ5PCYmBjdv3kRYWBhUVGo/b8jOzkZAQAD69++P2bNnM3oPycnJ2L17N549ewZTU1PMnDlTZC+sKp8+fUJ4eDi0tbUxd+5csWPOnDmDo0ePIicnB6amphg9erRQDVpDoTMsQqq5ffs2OnXqhODgYLx+/Rrv3r3D6dOnMXXqVMTHxwvGJSYmgsPhgMfjiZ0nKSkJHA4HpaWlQsfLysrg5eUFZ2dncDgcqe05VZv57du3D4mJiYzeQ3x8PKysrJCUlAQzMzPcuXMH1tbWiIuLExn74sULDBkyBL6+vjh06JDY+Xx8fGBvb4/MzEx06NABWVlZGDNmDKZMmcJoPfJEZ1iEVOPr6ws1NTU8ePAArVu3Fhx/+vSp2CYaWWRkZGDixIl48eIFpkyZgujoaKnP2bRpEx4+fAhLS0tGr/Hp0yfMmTMHgwcPBpfLhZqaGioqKjB27FjMmTMH9vb2gjO+CxcuYPLkyejQoYNILViVnJwchIeHw8fHBxwOR3B81apVCAwMxNKlS/Htt98yWps80BkWIdWkp6tisl4AACAASURBVKejd+/eQmEFfO4UFHdpJ4sbN26AxWLh5s2bjHZRePjwIZYuXYoNGzYw3orm8uXLyMrKwuLFiwWbDaqoqMDX1xc5OTk4c+aMYGxsbCwcHR1x/vx5QXlFTfn5+eDz+SLtPX379gUAvHr1itG65IUCi5BqLCwscOfOHbx9+1buczs7O+PatWswMzOTeinI4/Hg6uqKcePGwcXFhXGR6p07dwBA5IypX79+UFFRESq22Lx5M/bu3QtNTU2J62nfvj2MjIywZ88elJWVCY5HR0fDyMhIEFwNhS4JCanE5/OxbNkyjBkzBn369EFgYCAmTJhQ6/ezrly5IrY6q2a7ThWm5Q0rVqxAQUEBtm/fzmzxlbKzs6GlpYXmzZsLHdfU1IShoaFQmw+TtWhpaSEqKgrjx49H//79sWDBAkRHR+P+/fs4ceJEg2+XTIFFSCUnJyc4OjqCy+XC29sbU6ZMgaGhITw9PcFms8XuPOro6Cj3dSQmJmLDhg3gcrkyN/S8f/9eYvegtCJVSezs7BAaGirYI57FYuHgwYMNfnYFUGARIvDXX38BAIYPH4779++Dy+UiIiICQUFB2L9/PxITE0XubSUnJ6NRo0Yic23cuBHbtm2TeQ1v376Fm5sbvL29a62Lv3XrFpKTkwV/NzMzg4ODA9TV1cWWqAK1F6nWZsmSJQgPD8fq1avh6OiI8PBwTJkyBTdu3EB4eLjM89UHBRYhYrBYLNjZ2cHOzg4nT56Ek5MTVqxYgV9++UVonIWFhdjqL319/Tq9rre3N4qLi+Hg4ICkpCTB8ZKSEuTl5SEpKQlt27ZFXFwcQkNDBY8PHz4cDg4OMDQ0xLt378Dj8UQuZQsKCsQWqdYmLi4O69atQ0xMDCZOnAgA2L9/P0aMGIFp06aha9eumDVrVp3ea13QTXdCpBg1ahR69+4tdEajKImJicjLy8Pw4cMxaNAgwZ/MzExwuVwMGjQIBw4cQHBwMD59+iT4U/Xpn6WlJfh8Ph49eiQ0b0ZGBoqLi9GtWzeZ1sPlctGkSRNBWFVxc3ODqakpzp49W783LCM6wyJEitLSUmRmZsr8j70uuFyu2C+jOjo6wtLSEmFhYbWWY9ja2kJTUxOxsbFC642JiQGLxcLIkSNlWo+Ojg6Ki4tFGq8/fPiAwsLCOp9J1hUFFiGVysrK4OjoiJEjR8LCwgLNmzdHVlYWtmzZgpycHOzevVvha7CwsBB7XENDA7q6ulKLVJs1a4a5c+di3bp1MDY2xsCBA3Hr1i2sXr0azs7O6NChg0zrmTx5MjZu3IgffvgBISEhMDc3R2ZmJpYvXw4ej4cZM2bINF99UWARUklVVRW5ublgs9mCG9csFgu9e/dGQkIC7O3tv/AKmQkJCUFxcTF8fHzA4/GgoqKCyZMni7Q7M2FlZYWTJ0/C399f6FPBXr16gcvl0vewCPlS1NTUcOPGDfB4POTl5aGkpAQtW7YU+w33tWvXYu3atRLnCgoKQlBQUJ0fr6nmPanaaGhoYPv27Vi3bh1ycnJgZmYm9dPB6jf4a6r68OHDhw94+fIlWrRoIfaDhoZAgUVIDRoaGjAzM/vSy6i3xo0bo3379nKbT0dHR67z1QV9SkgIURoUWIQQpUGBRQhRGhRYhBClQYFFCFEaFFiEEKVBgUUIURoUWIQQpUGBRQhRGhRYhBClQYFFCFEa9FtCQipVlTIwaX7evHkzKioqsHDhQrFzbd26FTweD4sWLRJ5jEnTcnV1aX7+7bffEBcXh/z8fHTt2hXz58+X+PtIpuuRdd2KQGdY5F8vNzcXAFBcXMy4+fngwYPYv3+/xDkPHToksp0ywKxpubq6ND/7+flh3LhxePnyJUxNTXHw4EH07NkTf//9d53XI+u6FYUCi/zrcblcsFgsmJiYCJqfHz16hPPnz+PMmTN48uQJnjx5gvHjx9frdS5cuICePXsCEO0NlETW5ue0tDSEhYVhxYoVOH36NHbu3Ink5GRoaGiInO0xXU9d1q0oFFiEAIJmZUU2PzNpWq6uLs3P0dHRUFNTg4+Pj+BYs2bNMGvWLMTHx6OgoEDm9ci6bkWie1iEVFO9+bnqfpW8bN68WXCfTNbm58DAQEavcefOHXTq1Emkz9Da2hrl5eW4deuWYOdUpuuRZd2KRoFFSCVjY2OMHz+ecfPzu3fvcOnSJbGPFRUViTQrM219BurX/NyyZUuR461atQIAmZufZRnXECiwCKnUs2dPmZqfHz9+XGvZaffu3eu0DkU0P1eVvdal+flrQoFFSA1Mm58tLS1x7NgxsXO4uLjg06dPMr+2opqfq9ZSl+bnrwkFFiFiMGl+1tTUlLjHuZaWVp3OZuTR/Fz9xnqV/Px8AJC5+flrQ4FFiBRfqvm5pqr255CQEAQHByM4OFhkjKWlJf73v/+Bz+eDxWIJjqempgJAg5TBKhIFFiFSKFPz8+jRo7F9+3ZcvHgRw4YNExyPiYlB69at0blzZ4Wsu6FQYBFSqaioSOmbnx0cHNC7d29Mnz4dmzZtQuvWrXHo0CGcOnUKO3bsgIqKcn/1kgKLkEoaGhooKChQ6uZnFouFY8eOwd3dHePGjQPwuU8wODgYnp6eX3h19UeBRUglbW1txs3P169fr3Wu2pqUmTxekyzNzy1btsS5c+eQn5+Pd+/eoVWrVlBTq/2fOtP1yLpueaPAIqSGf0rzs4GBAQwMDL70MuRKuS9oCSH/KhRYhBClQYFFCFEaFFiEEKVBgUUIURoUWIQQpUGBRQhRGhRYhBClQYFFCFEaFFiEEKVBP80hRAwqUxWVnJyM3bt349mzZzA1NcXMmTPRp08fRmuRFzrDIqQGKlMVFR8fDysrKyQlJcHMzAx37tyBtbU14uLiGK1HXugMi5AaqspUHzx4ILSH+9OnT8U20sjiwoULmDx5Mjp06NAgZaqrV68GALx+/RrdunXDokWLhEKGyXo+ffqEOXPmYPDgweByuVBTU0NFRQXGjh2LOXPmwN7evt6djUzRGRYhNVCZqrDLly8jKysLixcvFmxTo6KiAl9fX+Tk5ODMmTOM1iUPFFiE1FC9TFXeNm/ejL1790JTU1PmMlWmLTxMylRlWc+dO3cAiNbU9+vXDyoqKrh27RqjdckDXRISUikkJAQjR47EsmXLqEy1xnxaWlpo3ry50HFNTU0YGhoKzadoFFhErE+fPuG3337Dn3/+KfJYSkqKxL3HlRWLxUJgYCDWr1+P1atXU5kqg/mq5mzIclYKLCLWw4cPkZ2djQkTJog8lp+fDxMTky+wKsUaOnQoxowZA4DKVKuTNF/VnA1ZzkqBRSQyNjbGvHnzRI6rq6vj7t27X2BFDYvKVD8zNDTEu3fvwOPxRC6NCwoKGrSclQKLEAb+zWWqlpaW4PP5ePTokdBzMzIyUFxc3KDlrPQpISEMVJWptmjRQuGvxeVykZaWJvLH3NwcY8aMQVpaWq3fdh89ejRev36NixcvCh2va5mqra0tNDU1ERsbKzIfi8XCyJEjZZqvPugMi5BqXr16BXd3dypTraZZs2aYO3cu1q1bB2NjYwwcOBC3bt3C6tWr4ezsjA4dOsg0X31QYBFSjZaWFpWpihESEoLi4mL4+PiAx+NBRUUFkydPxs6dO+W5dKkosAipRldXl8pUxdDQ0MD27duxbt065OTkwMzMrEE/HaxCgUWIGFSmKl7jxo0lfiraEOimOyFEaVBgEUKUBgUWIURpUGARQpQGBRYhRGlQYBFClAYFFiFEaVBgEUKUBgUWIURpUGARQpQG/TSHkBri4+Nx/Phx5ObmQl9fH+3atcOYMWPQo0cPAJ932fT398eQIUMwevRokedXVFRgyZIlsLGxwdixY0Uef/XqFcLDw2FjY8Pox9Rbt27FrVu3EBYWBiMjI6njy8rKsGvXLvz+++/g8XgYOHAgfvzxR5HfQzIZV1hYiKCgILGv4+PjA1NTU6nrkScKLEKqmTp1KqKjo9GxY0d06NABaWlpOHLkCA4cOID09HQAnwOLw+EAgMTA4nA4+PTpk0hgXb16FZMmTUJ2djZUVFSkBtbly5exYMECVFRUICAgQGpg8Xg8jBgxArdv38a4ceOgo6ODlStX4siRI7h48aJgx1Cm4zIzM8HhcNCyZUtoamoKvdaMGTMosAj5UpKSkhAdHQ02m41169YJjpeVleH58+f1nj88PBxLlizB7NmzsWfPHqnji4qK4ObmBltbW3C5XEavERkZiStXruD8+fMYNmwYgM+7SgwYMADbtm2Dt7e3TOPy8vIAAOfOnUPHjh1lfs/yRvewyL9e1b7rT548AQCMHz9e6PHa9m1nqqysDNHR0di4cSMiIiJQWloq9Tnz5s2Drq4upk2bxvh1Dh48iN69ewtCCPjcH2hjYyO0Fz3TcVWBJc8dH+qDAov861U1F7dt2xYAJPYM1oempiauXbuGuXPnSi1QBYBff/0Vv/76Kw4ePMh4h1A+n4+7d++KrZy3trZGcnIyiouLGY8DPgeWiooK9PX1Ga1B0eiSkPzrlZSUAAAGDx4Ma2trBAQE4Pnz51i0aFGt2/8+f/5cbLhJqsRiWqKanZ0NLy8vBAcHo1u3boLyCGmKiorw4cMHiSWqfD5fsC89k3GdOnVCXl4e1NXVMW/ePLx69Qp6enro1q0bpk+fjsaNGzNalzzRGRYhAJo3b46NGzeCy+Vizpw5iIyMxDfffIPhw4eLlDlUiYmJwdChQ0X+2Nra1nkdfD4fHh4e6NGjB3x8fGR6btWlrbQSVabjAKBnz57o2rUr8vPz0fj/2LvzuJry/w/gr3u7tJGipAVjmRlLQyhj+mJEaKEYTNmLTIVmorJN2aakTBSGYuzRTNOMkJA9WaORUFlmQiraKFrp/v4w3V/XvbfOrdtyuu/n49Hj8e2c9zn3c3y/vb/nnHvO59WmDR4/fixo5Hfu3JFqfLJAZ1iEAOByuVi1ahUAYOvWrfD29sbOnTuxdetWjBw5EqtXrxasrzJ37lwsW7ZMZF/v37+vNShCks2bN+PmzZu4c+eOUETXx/vfs2eP0LLx48ejVatWgvUfqx6iyrQOACZOnIiJEycK1SQmJmLYsGGYP3++1NM81xc1LELE0NbWhpeXF3744QdMmjQJa9aswYwZM9CjRw9Bjbq6utib8XVJewaAtLQ0LFu2DM7OzkhPT0d6erpgOQDcunULL1++xKBBg+Ds7Cy0be/evTF48GAoKCjUGqLavn17RnWSDBw4EJMmTUJYWBgqKioEDbAxUMMipAZt27bF4sWLcfr0aSQnJws1LFlLSEhAaWkpgoKCEBQUJLLezs4OioqKKC0tldgUP/vsM7H3vO7fvw9NTU3o6OhIVSdJ27ZtwefzmRyWTFHDIqQWVWc4DR2iam1tjZSUFJHlMTExcHd3x6lTpwTfZEoybtw4hISE4PXr12jXrh0A4O3btzh+/DjGjh0rdZ04paWlOHfuHAwNDRv17AqghkWIgI+PD/Lz8zFw4EDo6+vj/fv3iI+Ph7+/P4YMGYLBgwc36OerqalBTU1NZPnt27cBfAhYre15sO+//x6hoaH45ptvsHr1aigoKMDX1xdFRUXw9PSUus7Ozg7Dhg1D79690aFDB/zzzz/YtGkT0tLScOzYMRkdOXPUsAj5j6amJoKDg7Fp0ybBsrZt28LZ2Rne3t5SJyY3BX19fURHR2POnDkYPnw4AKBLly6IjIxE//79pa5r164dlixZInguCwD69euHY8eOwcrKqpGO6v9RwyLkP87OznB2dsarV68EX+OLuwxUUlKq8f4Nj8er1/qP2dnZwc7OjnH9sGHD8ODBA2RkZIDL5UJXV1fsN45M6kJDQ7F9+3bk5OTg1atX0NTURIcOHRiPRdaoYRHyEXV1dairqzf1MOqFw+Ggc+fOMqnjcrnQ1taGtra2rIZXZ83/HJcQQv5DDYsQwhrUsAghrEENixDCGtSwCCGsQQ2LEMIa1LAIIaxBDYsQwhrUsAghrEENixDCGvRqDiHVlJaWYv/+/YiLi8ObN2+gra0NAwMDTJgwQfAKS1paGnbu3Im5c+eid+/eIvt4+PAhQkND4eDggL59+4qsv3XrFsLDw+Hk5FTjnPHAh1lBPTw8wOFwsHHjRkbH8OLFC2zZsgX37t2DiooKJk6ciMmTJ0tdd/78eRw/flzi57Rq1Qp+fn6MxiQr1LAI+U9BQQGGDx+Oe/fuYfDgwejQoQOuXbuGXbt2ITk5GTt27AAA/PvvvwgMDMSIESPENqwnT54gMDAQQ4cOFWlYO3bswPfff4+ysjKYm5vX2rDWrVuHoKAg6OnpMWpY6enp+PLLL8HlcjFu3DhkZWXh22+/xeLFi/Hzzz9LVffgwQNERUWJ/ZzMzEy0bt2aGhYhTWXz5s24e/cuoqOjhaZOycvLQ0VFRb32XVxcDBcXF/z2229wdnbG5s2ba93m5s2b8PHxgZmZmdiJ/cRZtmwZKisrcefOHcHLygEBAVi6dCmmT5+OAQMGMK5zcnKCk5OTyGcUFhaic+fOmDFjBtPDlxm6h0XIf9LS0qCoqAhLS0uh5R06dKj3bKOZmZm4cuUKzp49Cxsbm1rri4uLMWPGDDg4ODBOXC4pKcFff/0Fe3t7oZkVXF1doaKigv3790tVJ0lISAjevHkjSIduTNSwCPlP9+7dUVZWhmvXrsl83z179kRqaiqGDh3KKEjVw8MD79+/R2BgIONQi7t376KiokIkIFVZWRmGhoa4evWqVHXilJeXIzg4GNbW1vVOw64LuiQkBB/yAOfPn4/t27fDwsICK1asgKOjY43pMcnJyWLDRJOSksTWMw1SPXHiBHbu3In4+HioqqoyOwB8CGAFIDEgtSr0lWmdOGFhYcjMzIS7uzvjcckSNSwi9xQUFDBjxgzo6uri5s2bWLBgAZYuXYqVK1fC1tYW3t7eYs8mVqxYIfOx5ObmYs6cOfDy8sKXX34p1ba1BaRWrWda9zE+n4+ff/4ZgwcPxtChQ6Uam6xQwyJyj8Ph4O3btwCAbt26ISYmBnfv3sXWrVuxd+9eREZG4s8//4S5ubnQdjt27ICpqanI/q5cuYLZs2fXaSzfffcdPvnkE3h5eUmsycjIwMmTJwW/c7lczJkzp9aA1KoGxbTuY0ePHkVKSgp+//135gckY9SwCBHDwMAAISEh8PT0xNdffw0nJyc8efJEqEZHR0fsmVdVAKq09u/fj6ioKOzZs0foPlJ2djbKy8sRHx8PDQ0NPH/+XChIlcfjYc6cOdDS0gIAiQGpVZe3TOs+FhAQgK5du2LSpEl1Oj5ZoIZFSA169OiBGTNmwN/fH69evWrQud7j4uLA5/Nhb28vdv2wYcMwduxYnDx5UuyN+Kpnvu7fvw8zMzOhdffv34exsbFUddVduXIFV65cwcaNGxnfi2sI9C0hIbVIS0uDqqqq2BvssuTj44OUlBSRH1tbW2hrayMlJQW//vqrxO21tbVhbGyMyMhIoeU3btzAkydPBAGpTOuq8/f3h5qaGhwdHWVwpHVHZ1iE/Gfq1Kno06cPevXqBV1dXbx69QqRkZGIiorCkiVLwOM17J9Lp06dxD7vpa6uDh6Ph169etW6Dy8vL9jY2MDV1RUODg7Izs6Gm5sbunXrhunTp0tdBwCpqak4duwY3N3d0bZt2/ofaD1QwyLkPyoqKvDz80NJSYlgWefOnREcHIyFCxc24ciYs7a2xrZt2/Djjz9i69atAICvvvoKe/bsEbqZzrQOADZs2AAFBQV8//33jXcgElDDIuQ/u3btws6dO5Gbm4tXr15BW1sb7dq1E6kzNzevMQjVzMysXus/FhISwrgWAFxcXODo6IinT59CQ0ND4k10pnW7du3Crl27pBpDQ6GGRUg1XC4XHTt2RMeOHZt6KPXSqlUr9OjRQ2Z1zQXddCeEsAY1LEIIa1DDInJPmvtJpGlRwyJyr6CgAPfv32/qYRAGqGERAoidOZQ0P9SwCCGsQQ2LEMIa1LAIIaxBDYsQwhrUsAghrEENixDCGvQuISEfYZL+HBMTg3PnzmHdunVo3bq1yD5OnjyJM2fOwMfHB0pKSiLrIyIicOPGDQQEBIDLrfm8oS7pz0lJSdi5cyeePHkCXV1dODo6ip2Yr7bxNMf0Z35WVhafCSUlJX5JSQmj2pZi/fr1/KVLlzb1MBqdqakpf+jQoWLXhYSE8J2cnBp5RHVnaGjI//vvvyWu53A4/Hnz5vH5fD4/Pz+fb2BgwOdwOPwvv/ySb2lpye/Xrx9fQUFBUMPn8/lLly7lA+AXFRWJ3eePP/7IB8AvKCgQWl5aWsp3cnLiA+AD4FdUVNQ6/rVr1/IB8PX09JgcLv/YsWN8LpfL79+/P9/JyYlvZGTE5/F4/MOHD4vU1jaekJAQfo8ePcT+KCsr89u1a8doTPWVlZXFB8CnMyxCqmnI9Of09HRMmTIFmZmZmDZtGg4dOlTrNtKmP7979w4uLi74+uuvERsbCx6Ph8rKSlhbW8PFxQXm5uaCMz4m42lu6c90D4uQahoy/fn69evgcDi4ceMGoyld6pL+fPHiRWRkZMDd3V0wQyqXy4Wnpyeys7Nx6tSpOo+nuqZKf6aGRUg1DZn+bGtri6tXr0JPT6/B0p8TExMBQCTVeciQIeByuUJpPNKOp0pTpj/TJSEhAP744w9MmTJF6vTnS5cuic3x+zgSrEpjpD8rKSmhQ4cOQssVFRWhpaUlEkFWlwScpkx/poZFCD58q3f8+HGMHj1aqvTnjy8dZaG+6c+SglBrSnVmit/E6c/UsAjBh2SatWvXApAu/TkpKQkqKioi+9u0aRO2bdtWp7HUN/1ZXKIzUHOqM1NNnf5MDYsQCZikP3fv3l1sXqGGhkadPlMW6c9FRUUoLy8XeT4sLy+vxstbJpo6/ZkaFiG1YFP6s4GBAfh8PlJTU9GvXz/B8vT0dBQXFwstk1ZzSH+mhkUIA42Z/uzh4SGyfPXq1bhw4QIuXLhQ4xjMzMygqKiIyMhIoeYUEREBDoeDMWPG1HlszSH9mRoWIdWwPf25ffv2WLBgATZs2ABtbW0MHToUCQkJWLt2LWxtbfHpp5/WaVzNJf2ZGhYh1bSE9Gc/Pz8UFxdj8eLFKC8vB5fLxdSpUxEaGlrnfTaX9GcOPrxLyOgpXmVlZRQUFIh9mbOl8vf3R0FBAdavX9/UQ2lUI0eOREVFBS5duiSyLjQ0FH///bfUicRNZcCAAdizZw8MDQ3FrudyuUhJSRE8TV5ZWVlr+jMbvHnzBtnZ2dDT06v3t4NNLTs7Gzo6OnSGRcjHWkr6c5s2bRr9SfSGRq/mEEJYgxoWIYQ1qGERQliDGhYhhDWoYRFCWIMaFiGENahhEUJYgxoWIYQ1qGERQliDGhaRa+np6eDz+XWebI80Lno1h8i1qtk558+fDwC4ffs2wsLC8PjxYygrK0NfXx+jR4+GqakpeDwe3r17h2XLlmHEiBEYN26cyP4qKyuxZMkSDB8+HNbW1iLrX758iaCgIAwfPlxk9lJxfvnlFyQkJCAgIIDRq0JlZWXYsWMHLl++jPLycgwdOhTz58+X+P7vrVu3EB4eDicnJ7EzOSQmJuLPP/9EWloaFBQU0LNnT8ybNw+ffPJJrWNpCHSGRch/QkNDMWjQIISFhaGsrAwZGRnYv38/zM3NkZ2dDeDDNMOBgYG4cOGC2H1UVlYiMDAQ586dE1l35coVDBw4EH5+foiPj691PBcvXsT333+Pffv2obCwsNb68vJyjB49GkuXLgWXy4WqqipWrlyJUaNGoby8XKR+x44d+N///ofAwECxoRmLFy/GoEGDcOTIEairq0NFRQW7du1Cr169cPny5VrH0xCoYRECoKSkBO7u7jAxMUF6ejpiYmIQFxeHrKwsJCcnQ19fv177DwoKwogRIzBhwgRGs528fv0as2bNgpmZGePP2L17Ny5duoTo6GgcOnQIBw4cwJkzZ3Dt2jWhS97i4mLMnj0brq6uYkNSq0ybNg1HjhzB3bt38euvv2LPnj24f/8+2rdvjxUrVjAelyxRwyIEwIsXL/D27VtYWloKNRQOh4M+ffrUa99lZWU4dOgQNm3ahM2bN6O0tLTWbRYuXAg1NTXMnj2b8eccPHgQRkZGGDlypGDZkCFDMHz4cOzbt0+wLDMzE1euXMHZs2dhY2MjcX9GRkYil7Xt27eHsbExHj9+zHhcskQNixB8mOmTx+Ph4sWLMt+3oqIirl69igULFjAKLP3jjz/wxx9/4ODBg+Bymf2J8vl8/P333yIBqgBgYmKCpKQkFBcXAwB69uyJ1NRUDB06VKoAVQAoKirCrVu30L9/f6m2kxW66U4IgLZt28LDwwPr16/H6NGjsXLlSgwbNkxi/bNnz8Tex5IUscU0tKEqDcfX1xf9+vXD/fv3GW33+vVrvH37Vuyla+fOncHn8/H06VPBFMvShEg8evQIJSUlSEtLg7+/P3g8HgIDAxlvL0vUsIjc43A4OHDgAPz8/KCrqwsfHx8MHz4cvXv3hru7OxwcHETOdCIiIhARESHTcfD5fDg4OMDQ0BCLFy+WatuqgFRxM4tW5SbWJUT13bt3Qt8eGhgY4Ndff611bvmGQg2LEAA//vgjAMDV1RXz5s1DeHg4goKC4OjoiIiICERHR6NVq1aC+rlz52LZsmUi+3n//n2d/5g3b96Mmzdv4s6dO+BwOBLrjh49ipcvXwp+NzIygo6OjuDzP1YVB1aXaZJ5PB6Sk5NRVlaGzMxMHD16FGPGjMGiRYua5CyLGhYhH1FSUoKDgwPs7e3h5eWFdevWISwsDA4ODoIadXV1sdMPi8sKZCItLQ3Lli2Ds7Mz0tPTkZ6eLlgOfHhe6uXLlzAxMUFAQACuXbsm2Hbt2rXw9PSEgoIC8vLyRPadm5sLAHUOUTUwMAAAcRjkVgAAIABJREFUDBo0COPHj4eamho2btwIFxeXRp+CmRoWIRJwOBxBw0pKSmrQz0pISEBpaSmCgoIQFBQkst7Ozg6KioooLS2V+AzXZ599Jvae1/3796GpqSk4C6svIyMjAMA///xDDYuQ5uTBgwcAwChVqj6sra2RkpIisjwmJgbu7u44depUrU+Xjxs3DiEhIXj9+rUg6eft27c4fvw4xo4dK7OxVjXM7t27y2yfTFHDIgTA8ePH8ddff2Ho0KHo2rUrlJWVce/ePaxfvx4aGhqYOXNmg36+mpoa1NTURJbfvn0bwIfmUNvZzPfff4/Q0FB88803WL16NRQUFODr64uioiJ4enpKPSYzMzNYWVmhf//+0NbWRm5uLqKiohASEoLJkyc3SSIPNSxCAGhqauLKlSvYv3+/YBmPx4O1tTV8fHygp6fXhKNjRl9fH9HR0ZgzZw6GDx8OAOjSpQsiIyPr9NxU9+7dsXr1aqHXgjp27AhPT0+sWrVKZuOWBjUsQgB8+eWXePjwId6+fYucnBxwOBzo6+uLPK+kpKQEPp8vcT88Hq9e6z9mZ2cHOzs7xvXDhg3DgwcPkJGRAS6XC11d3Rq/cTQzM5M4nh07dmDbtm3IyclBYWEh1NTU0KlTpxr319CoYRFSjaqqKlRVVZt6GPXC4XDQuXNnmeyLx+NBR0dHZjfs64tezSGEsAY1LEIIa1DDIoSwBjUsQghrUMMihLAGNSxCCGtQwyKEsAY1LEIIa1DDIoSwBjUsQghr0Ks5hFQTHR2No0eP4sWLF9DQ0ECPHj0wfvx4GBoaAkCLCVK9d+8ewsLCkJaWBjU1NQwePBhz586FoqKioObVq1fw8fER+zmLFy+Grq5ureORNTrDIuQ/06dPx/jx4xEXF4fKykqkpKQgICAAtra2gpqWEKS6fPlyGBoaIiYmBhoaGnj16hV++OEHDBw4EK9fvxbUPX36FIGBgfj9998RFRUl9FO9rjHRGRaRay9fvgSfz0dcXBwOHToEDw8PbNiwQbC+rKwMz549q/fnBAUFYcmSJfjuu++wa9euWuurB6nGxsYy+oyqINWzZ88KsgmvXbuG//3vf9i2bRvc3NwAAJ9//jn27t2L6dOnC7aNjo7G+PHjsX37dsFc9Tk5OQCAM2fO4PPPP5fqeBsKnWERuXb27FlwuVzBzKLffPON0HpFRcV6T1TX3IJU7e3thZoVAFhZWUFZWVlo1tOqhqWpqcl4DA2NGhaRe5WVlejWrRsASLzUq4/mFqQqTnFxMcrKyqCtrS1YlpOTAy6XCw0NDUZjaAx0SUgIAFNTU5iYmMDLywvPnj3DokWLhPL4Psb2INWP7d27F5WVlZgyZYpgWU5ODlq1aoWFCxfi5cuXUFdXR79+/TBnzhy0adOG0bhkjc6wiNxTVVWFn58fYmNj4eLigt27d+Ozzz7DqFGjcP78ebHbREREwNTUVOTHzMyszuNoqiDVlJQULF++HPb29jA2NhYsHzBgAPr27Yvc3Fy0adMGjx8/FjTyO3fuSDU+WaEzLCL3FBQUBHOUb926Fd7e3ti5cye2bt2KkSNHYvXq1SJzmDdVkOr79++xZ88eoWXjx48XhLxKG6T67NkzjB07Fn379sUvv/witG7ixImYOHGi0LLExEQMGzYM8+fPZ/RNp6xRwyLkI9ra2vDy8sIPP/yASZMmYc2aNZgxYwZ69OghqGmqINVBgwbB2dlZaNvevXtj8ODBUgepZmVlYdSoUejYsSNiYmIEZ2I1GThwICZNmoSwsDBUVFQIpWE3BmpYhEjQtm1bLF68GKdPn0ZycrJQw5I1aYJUJTVFaYJUs7OzYWpqCg0NDZw6dQrq6uqMx9q2bVupgjRkiRoWITWoOsNpSUGqL168EDSrkydPCmqZKC0txblz52BoaNjoZ1cANSxCAAA+Pj7Iz8/HwIEDoa+vj/fv3yM+Ph7+/v4YMmQIBg8e3KCf31hBqm/evMHIkSORnp6ONWvWIDw8XGQ/dnZ2UFdXh52dHYYNG4bevXujQ4cO+Oeff7Bp0yakpaXh2LFjMjhq6VHDIgQfHo4MDg7Gpk2bBMvatm0LZ2dneHt7M34eqikxCVLNzs4WXDYuXbpU7H5GjBgBdXV1tGvXDkuWLBF6fqtfv344duwYrKysGvhoxKOGRQgAZ2dnODs749WrV4Kv8cVdBrI9SLVnz56MPz80NBTbt29HTk4OXr16BU1NTXTo0IHxWBoCNSxCqlFXV5fqBnRzJMsgVS6XC21tbaEn4JtS8z/PJYSQ/1DDIoSwBjUsQghrUMMihLCG1A1L3PtIhBDSGKRuWCUlJQ0xDkIIqRVdEhJCWIMaFiGENahhEUJYgxoWIYQ1qGERQliD3iUkRIysrCzs3r0bt2/fBp/Ph46ODr766iuMGzdOMA3Mli1bUFlZiR9++EHsPn755ReUl5dj0aJFIuvevXuHoKAgKCsrY8GCBbWO5/nz5/Dy8sJXX32F7777jtExHDlyBFFRUcjNzUXfvn3h6uoKPT09sbXSjufs2bM4cOCA0MwQjYHOsAj5yM2bN9GrVy/4+voiPz8fRUVFOHnyJKZPn47o6GhB3cGDB3HgwAGJ+wkPDxfKA6ySmZmJESNGwNPTU+x8VB/j8/mwt7fH3r17ERcXx+gYli5digkTJiArKwu6uro4ePAgBgwYgH///bfe48nJycH06dOxb98+QZ5jY6GGRchHPD09wePxkJqairNnz+LUqVN4+PAhHj58KBK0Kq1z585hwIABACA2Q1Cc4OBg3Lt3DwYGBozqU1JSEBAQAG9vb5w8eRKhoaFISkpC69atRc726jKe7777TjC/VmOjhkXkWk5Ojki4aVpaGoyMjNClSxeh5T179oSSklK9Pi8yMhKWlpY4e/YsoymG7927h+XLl2Pjxo2M57E6dOgQeDyeUFRY+/btMW/ePERHRwsFVUg7nl27diE2NhZr1qxhNBZZo4ZF5Nrt27fB4/Hw4sULvHjxAnw+H927d0diYiIKCwtl/nlbtmzBnj17oKioWGsKdHl5OWbMmIEJEybAzs6OcSJPYmIievXqJTKvl4mJCd6/f4+EhIQ6jeeff/6Bm5sbNm7cWOv88g2FbroTuda6dWvw+XzBJY6joyNWrFiB8ePHw9jYGKtXr8akSZPQunVrsdsXFRVJjLd//fq1SOIz0wRoAPD29kZeXh62b9/OeBvgww16SQnQAAQRYtKM5/3795g5cyZMTU3h5OSE7OxsqcYkK9SwiFzj8Xjo1asXrl27JrQ8NjYWbm5umDZtGrS0tODk5AQPDw+RhJkHDx7A1NRU4v7req8nLi4OGzduRGxsrNQzoL5586ZOCdA18fPzw6NHj3D48GGpt5UlaliEiDFq1CjcuXMHsbGx2Lx5M3x8fHDgwAHExcUJ3dsyMDCQ+EcszWVcdYWFhZg1axbc3NxqbIYJCQlISkoS/K6npwcLCwu0atVK6gTomty6dQtr167FX3/9hY4dO0q1raxRwyJEAg6Hg7Fjx2Ls2LE4fvw4bGxs4O3tLfSogqKiosT4LSUlpTqdzbi5uaG4uBgWFhZCcfAlJSXIyclBfHw8PvnkE0RFRcHf31+wftSoUbCwsICWlpZUCdA1KSsrw4wZM2BiYgJ1dXXBePLz8wEAjx49Qnx8PPr374+2bdtKfazSooZFCANWVlYwMjISOqNpKHFxccjJycGoUaNE1j19+hSxsbHw8/ODr68vfH19RWoMDAzw+++/g8/nCyXmVMV79evXj/FYcnJykJqaitTUVAwbNkxkvb+/P/z9/XH16lXGj0XUBzUsQhgoLS3F06dPpfpjr6vY2FiUl5eLLLe0tISBgQECAgJqvDQbN24ctm/fjvPnz2PkyJGC5REREejSpQt69+7NeCydOnUSm0idm5uLYcOG4aeffsLkyZMb7VtDaliEVPPy5UvY29tjzJgx6N69Ozp06ICMjAxs3boV2dnZ2LlzZ4OPoXv37mKXt27dGmpqaujVq1eN21tYWMDIyAhz5sxBcHAwunTpgvDwcJw4cQIhISFShcJWfSnxsapvCTt16lTreGSJGhYh1SgpKSEvLw8eHh6CG9ccDgdGRkaIiYmBubl5E4+wdhwOB4cPH4a9vT0mTJgAAFBVVYWvry+cnJyaeHT1Qw2LkGrU1NRw/fp1lJeXIycnByUlJdDX1xf7hPvHj0J8rPoN87qs/1hqairjWn19fZw5cwa5ubkoKipC586dwePV/OcuzXg6deokVYK1rFDDIkSM1q1bS5zZgE00NTWhqanZ1MOQGXo1hxDCGtSwCCGsQQ2LEMIa1LAIIaxBDYsQwhrUsAghrEENixDCGtSwCCGsQQ2LEMIa1LAIIaxBr+YQ8h8m4akxMTE4d+4c1q1bJ3ae95MnT+LMmTPw8fER+/5hREQEbty4gYCAgFpnTahLeGpSUhJ27tyJJ0+eQFdXF46OjjA2NhaqqaiowMGDB3H+/HkUFRWhW7dumDVrlsh0zs+fP0d4eDgSExNRUlKCrl27YvLkyRg6dCijsTQEOsMiBMzDU+Pi4hAYGCh2virgwwvEgYGBKC0tFVpeVlYGZ2dn2NraIjAwsNaEmrqEp0ZHR2PgwIGIj4+Hnp4eEhMTYWJigqioKEFNcnIy+vfvj4ULF6KwsBAaGho4duwYBg4ciNDQUEFdZGQkunXrhsDAQHA4HHTs2BFnz57FsGHD8PPPPzMaT0OgMyxC8P/hqcnJyUJztj969EhsAo000tPTMWXKFGRmZmLatGk4dOhQrdtIG5767t07uLi44Ouvv0ZsbCx4PB4qKythbW0NFxcXmJubQ0lJCV26dIGZmRmWL18OHR0dAB/OuIYPH44lS5bAwcEBrVu3xqhRoxAUFIS5c+dCUVERwIcmamVlhR9//BGurq6C5Y2JzrAIQcOGp16/fh0cDgc3btxAjx49aq2vS3jqxYsXkZGRAXd3d8E0MlwuF56ensjOzsapU6cAAO3atcPmzZsFzQoAWrVqBRsbGxQWFuL58+cAAA0NDcyfP1+oKXE4HIwePRrl5eV49uwZ4+OXJWpYRK69efMG79+/b9DwVFtbW1y9ehV6enoNGp4KiMbNDxkyBFwuF1evXq1x+4KCAigoKNQ6Fc2FCxegrq4u0tgbC10SErmWnp6O3r17w83NjXF4KgBcunRJbFzWkydPxNYzDSytT3iqkpISOnToILRcUVERWlpaQuGpHystLUV4eDjMzc1Fkm+eP3+OoqIiPHv2DL/++itOnz6NsLCwGv9tGhI1LCLX2rZtiyFDhsDS0pJxeCrwIRBC1hoiPBX4EKBaU9zYwoULkZeXhw0bNoiss7W1xeXLlwF8mAxw06ZNsLGxkWpsskQNi8i9hw8fAmAengp8eHygKkm5uk2bNmHbtm1Sj6GhwlOBDzfkJTWz1atXY8+ePfjtt9/EpukcOHAAhYWFyMnJwaVLl7B06VLs27cP58+fb5Kb7tSwCKmGSXgq8CHZpk2bNiLba2ho1OlzZRGeWlRUhPLycpHLtby8PLHhqT///DN++ukn7N69G1OmTBE7rm7dugn+s5mZGYyMjGBtbY2wsDDMnTu3TsdaH9SwCJGAbeGpfD4fqampQtmJ6enpKC4uFslT3LRpE5YtW4a9e/di5syZjMdpZGQEAHj8+DHjbWSJGhYhErApPNXMzAyKioqIjIwUGm9ERAQ4HA7GjBkjWBYcHAxPT0/s378f06ZNk2qcVWd/TB7PaAjUsIjcKy0thaWlJavDU9u3b48FCxZgw4YN0NbWxtChQ5GQkIC1a9fC1tYWn376KQBg9+7dcHNzw5gxY1BYWIiQkBCh/fTs2RNmZmb4/vvvoaqqiuHDh0NfXx9v377F1atX4ePjg27duuHbb7+VzYFLiRoWkXsKCgqsD08FAD8/PxQXF2Px4sUoLy8Hl8vF1KlThV65OXfuHIAPZ3SxsbEi+7C1tYWZmRl69+4NPz8/rF+/XrBORUUF48ePx4YNG0Qef2gsHAD8rKwsdOrUqdZiZWVlFBQU1PvJXzbx9/dHQUGB0H9x8mDkyJGoqKjApUuXRNaFhobi77//Fvl/5+ZqwIAB2LNnDwwNDUXW9enTB/3790d4eDij8FQ2ePPmDbKzs6Gnpyfx20Em+Hw+8vLykJ+fDyUlJejo6KBVq1YyHClz2dnZ0NHRoTMsQqq0lPDUNm3aoGfPnvXeD4fDaXZBrPRqDiGENahhEUJYgxoWIYQ1qGERQliDGhYhhDWoYRFCWIMaFiGENahhEUJYgxoWIYQ1qGERQliDXs0h5D/yEqQqTR0APHjwAOHh4Xjw4AFev36NL7/8Et7e3ozGI2t0hkUI5CdIVZo6AAgMDESfPn0QFhYGFRUVfPbZZyLH1pjoDIsQyE+QKtM6APjrr7/g4eGB1atXw9vbu9YzwsbQ9CMgpBmQlyBVpnUA4OXlBTMzM6xatapZNCuAGhYhACA3QapM61JTU5GSkgJ7e3tGn99Y6JKQtHiDBw/GkCFDwOFwxK7v168fVqxYIRdBqkzr7t69CwD49NNPsXLlSpw4cQIcDgfGxsZYuXIltLW1pRqfrFDDIi3e9u3bERwcLHbdrFmz0LNnT7kJUmVa9+LFCwAfQla7deuG7777Di9evMDWrVtx+PBh3L9/X+oxygI1LNLicblcifehFBQUBDe25SFIlWldXl4eAGDChAlYsWKFoOabb75Bv379EBwcjFWrVkl3kDJADYuQalp6kCrTuqpjc3R0FKrp06cPevbsiTt37tTpOOuLGhYhErTEIFWmdVWJz7m5uSJ5iO/fv2+yZ7HoW0JCJKgKUmWSKFVfsbGxSElJEfnp1q0bxo8fj5SUlBqfdq8epFrdx0GqTOtGjRoFJSUlkTPL9PR0pKeni00gagx0hkXkXmFhodwEqTKtU1NTw8qVK+Hl5YW2bdti/PjxeP78OVasWAEVFRU4OTnJ9h+AIWpYRO61atVKboJUpalbvnw5FBQUsH79esG7g1988QVOnTol8iVEY6Eg1VpQkCr7g1RrMnXqVNjY2MDOzk7uglSZ1r179w5Pnz6FsrIydHR0GmLItaIgVUI+Im9BqkzreDyexEvWxkY33QkhrEENixDCGtSwCCGsQQ2LEMIa1LAIIaxBDYsQwhrUsAghrEENixDCGtSwCCGsQQ2LEMIa9GoOIf+5ffs2wsLC8PjxYygrK0NfXx+jR4+GqampIGFmy5YtqKysxA8//CB2H7/88gvKy8uxaNEikXXv3r1DUFAQlJWVsWDBglrHc/bsWRw4cABz5szB8OHDGR3DkSNHEBUVhdzcXPTt2xeurq5iXzdiUpeYmIg///wTaWlpUFBQQM+ePTFv3jx88sknjMbSEOgMixB8eKF70KBBCAsLQ1lZGTIyMrB//36Ym5sjOztbUHfw4EEcOHBA4n7Cw8NF5pACgMzMTIwYMQKenp4IDw+vdTw5OTmYPn069u3bhwcPHjA6hqVLl2LChAnIysqCrq4uDh48iAEDBuDff/+Vum7x4sUYNGgQjhw5AnV1daioqGDXrl3o1asXLl++zGg8DYHOsIjcKysrg7u7O0xMTHD69GnBLA18Ph8pKSn1DlI9d+4cpk6dik8//VQkXkuS7777Dv3790dsbCyj+pSUFAQEBMDb2xtr164FAOTn56Nfv35YtGiRINWZad20adMwYsQIWFtbCz4jPz8fBgYGWLFiBS5evMj4+GWJzrCI3MvPz8fbt29haWkpNKUMh8NBnz596r3/yMhIWFpa4uzZs2jVqlWt9bt27UJsbCzWrFnD+DMOHToEHo+HxYsXC5a1b98e8+bNQ3R0tCBUgmmdkZGRULOqqjM2Nsbjx48Zj0vWqGERudehQwfweLwGO2vYsmUL9uzZA0VFxVqDVP/55x+4ublh48aNUt0rSkxMRK9evUSit0xMTPD+/XskJCRIVSdOUVERbt26hf79+zMel6zRJSGRa+/fv0fr1q3h4eGB9evXY/To0Vi5ciWGDRsmcZuioiJcuHBB7LrXr1+LhKYyDVF9//49Zs6cCVNTUzg5OQndO6vN8+fPxV66du7cGQCEglSZ1FV59OgRSkpKkJaWBn9/f/B4PAQGBjIel6xRwyJyzc3NDadPn4afnx90dXXh4+OD4cOHo3fv3nB3d4eDgwO4XOELkQcPHtSYHVjXMxA/Pz88evQIhw8flnpbSQGpVdmJtQWpflwHfPhWs2qOd+BD4s6vv/5a6/zyDYkaFpFrJiYmMDExAQC4urpi3rx5CA8PR1BQEBwdHREREYHo6Gihe08GBgYSm4qdnR3evXsn9Thu3bqFtWvX4q+//hKJ1aru6NGjePnypeB3IyMjGBoaSgxIrRpLbUGqH9cBH2YaTU5ORllZGTIzM3H06FGMGTMGixYtarKzLGpYhFSjpKQEBwcH2Nvbw8vLC+vWrUNYWBgcHBwENYqKihKnFlZSUhI6S2GirKwMM2bMgImJCdTV1QVBqvn5+QA+XJbFx8ejf//+CAgIwLVr1wTbrl27FoaGhtDS0hLcMK8uNzcXAISCVJnUValKxR40aBDGjx8PNTU1bNy4ES4uLoymV5Y1aliEiMHhcAQNq6GDVHNycpCamorU1FSx9878/f3h7++Pq1evCqVCV2dgYIDff/8dfD4fHA5HsPz+/fsAIBSkyqROEiMjIwAfvhxoioZF3xISIkHVA5sNHaTaqVMnsSGqVYlFP/30E1JSUmoMLx03bhzy8/Nx/vx5oeURERHo0qULevfuLVWdJFUNs6lCKegMi8i96Oho/PHHHxg6dCi6du0KZWVl3Lt3D+vXr4eGhgZmzpzZoJ/P4/HE3siu+pawU6dOtd7otrCwgJGREebMmYPg4GB06dIF4eHhOHHiBEJCQgRfHDCtMzMzg5WVFfr37w9tbW3k5uYiKioKISEhmDx5cpOcXQHUsAiBpqYmrly5gv379wuW8Xg8WFtbw8fHhxXRXxwOB4cPH4a9vT0mTJgAAFBVVYWvr69QSjPTuu7du2P16tUoLCwULOvYsSM8PT2xatWqRjoqUdSwiNwbMmQIHj58iLdv3yInJwccDgf6+vpin5+qfsNbHEn3mJiur65Tp07g8/mM6/X19XHmzBnk5uaiqKgInTt3Fry0LW3djh07sG3bNuTk5KCwsBBqamro1KmT0H2vpkANi5D/qKqqQlVVtamHUW+amprQ1NSsdx2Px4OOjk6TpT2LQzfdCSGsQQ2LEMIa1LAIIaxBDYsQwhrUsAghrEENixDCGtSwCCGsQQ2LEMIa1LAIIaxBDYsQwhrUsAghrEHvEhK5kZWVhd27d+P27dvg8/nQ0dHBV199hXHjxkFNTQ0AEBMTg3PnzmHdunVo3bq1yD5OnjyJM2fOwMfHRygSrEpERARu3LiBgIAAkbngAeDFixfYsmUL7t27BxUVFUycOBGTJ09mfAxJSUnYuXMnnjx5Al1dXTg6OsLY2LjOdYD0idRNic6wiFy4efMmevXqBV9fX+Tn56OoqAgnT57E9OnTER0dLaiLi4tDYGAgysvLxe4nPj4egYGBKC0tFVpeVlYGZ2dn2NraIjAwUGycV3p6Ovr164ddu3ZBU1MTr1+/xrfffgsPDw9GxxAdHY2BAwciPj4eenp6SExMhImJiSD8VNo6QPpE6qZGZ1hELnh6egpCFbp06SJY/ujRo3onO6enp2PKlCnIzMzEtGnTcOjQIbF1y5YtQ2VlJe7cuQNtbW0AQEBAAJYuXYrp06djwIABEj/j3bt3cHFxwddff43Y2FjweDxUVlbC2toaLi4uMDc3h5KSEuM6oG6J1E2NzrCIXEhLS4ORkZFQswKAnj17ir20k8b169fB4XBw48YN9OjRQ2xNSUkJ/vrrL9jb2wuaFfAhqUdFRUVo8kBxLl68iIyMDLi7uwvmruJyufD09ER2djZOnTolVR0gfSJ1c0ANi8iF7t27IzExUWgGTVmxtbXF1atXoaenJzHZ+e7du6ioqBA5k1FWVoahoSGuXr1a42ckJiYCgMj2Q4YMAZfLFWzPtA6QLpG6uaBLQtIiODg4ICwsTOy6ixcvYsWKFRg/fjyMjY2xevVqTJo0SexN9SqXLl0SGzj65MkTsfW1pTs/f/4cACSmLktKkq6+vZKSEjp06CC0XFFREVpaWkLJzkzqmIy5OaKGRVqE+Ph43L17V+wlma+vL1atWoXY2Fi4ublh2rRp0NLSgpOTEzw8PNCuXTuRbSwtLWU6vqqsQkmpy7VlGUpKbP54e6Z1bEUNi7QYCgoKYucwrwpNGDVqFO7cuYPY2Fhs3rwZPj4+OHDgAOLi4kTubSUlJQni26vbtGkTtm3bJvXYqu4RSUpdrmoyCQkJQjmIenp6sLCwkJjY/PH2TOvYihoWkSscDgdjx47F2LFjcfz4cdjY2MDb2xv79u0TquvevTvatGkjsr2GhkadPldLSwsAJKYuVyUuR0VFwd/fX7Bu1KhRsLCwgJaWFoqKilBeXi5yKZuXlyeU7Mykjq3opjuRW1ZWVjAyMmrwZGcA6Nu3L4D/T1iu7v79+4LEZV9fX7x7907wU/WtnoGBAfh8PlJTU4W2TU9PR3FxsVCyM5M6tqKGReRWaWkpnj592uDJzgCgra0NY2NjREZGCi2/ceMGnjx5grFjx9a4vZmZGRQVFUW2j4iIAIfDwZgxY6SqYyu6JCQt3suXL2Fvb48xY8age/fu6NChAzIyMrB161ZkZ2dj586djTIOLy8v2NjYwNXVFQ4ODsjOzoabmxu6deuG6dOn17ht+/btsWDBAmzYsAHa2toYOnQoEhISsHbtWtja2uLTTz+Vqo6tqGGRFk9JSQl5eXnw8PAQ3JDmcDgwMjJCTEwMzM3NG2Uc1tbW2LZtG3788Uds3boVAPDVV19hz549jG6G+/n5obi4GIuLSbVoAAAgAElEQVQXL0Z5eTm4XC6mTp2K0NDQOtWxEQcAPysri9FpsbKyMgoKCur9ZDCb+Pv7o6CgAOvXr2/qoTSqkSNHoqKiApcuXRJZFxoair///hshISFNMDLxPv30U5w4cQI9e/aUWFNeXo6cnByUlJRAX1+/yf53XFFRgadPn0JDQ6NON8HfvHmD7Oxs6Onp1djomNaxQXZ2NnR0dOgMi8iP1q1bQ09Pr6mHgVatWkl8hYeJNm3a1NiYpa1jE7rpTghhDWpYhBDWoIZFWgS2vLxL6ocaFmkRMjIycPDgwaYeBmlg1LBIi1BRUQE7O7umHgZpYNSwCCGsQQ2LEMIa1LAIIaxBDYsQwhrUsAghrEGv5hC5wCREdcuWLaisrMQPP/wgdh+//PILysvLsWjRIpF1TMJIT58+jcOHDyMzMxM6OjqwsLCAtbU142M4cuQIoqKikJubi759+8LV1VXiq0ZMw1HZFKIK0BkWkQNMQ1QPHjyIAwcOSNxPeHi4yMykQO1hpIWFhbCysoK5uTlSU1OhpaWF5ORk2NjYYMaMGYyOYenSpZgwYQKysrKgq6uLgwcPYsCAAfj333+lHo+0dc0JNSzS4lWFqKampuLs2bM4deoUHj58iIcPH+Kbb76p177PnTsnCECVFEaqpqYGQ0NDXLt2DefOncPOnTsRHx8Pd3d3HDx4ENeuXavxM1JSUhAQEABvb2+cPHkSoaGhSEpKQuvWrUXO9piMR5q65oYaFmnxGjJElWkYqa+vL4yNjYWWTZ48GcCHhlSTQ4cOgcfjYfHixYJl7du3x7x58xAdHS00TzzT8bAxRBWge1hEDlQPUa26XyUrW7ZsEeT7Sfs+Y0FBAQAIJUGLk5iYiF69ekFdXV1ouYmJCd6/f4+EhATBJIRMx1OfcTclalikxXBychKZqO7w4cNShagWFRVJDDV9/fq1SPhofcJId+/eDU1NTZiamtZY9/z5c4kBrADqFI7KxhBVgBoWaSEUFBTg6ekp8ofo5+eHNWvWMA5RffDgQY0NpH///jIZb1hYGCIjI7F3795aZwOVFI5alZvI9nBUaVDDIi3G2LFjRYJUqy6VmIaoGhgY4PDhw2L3b2dnh3fv3tV7nLGxsZg7dy5cXV0xe/ZswXJpQ1SrxsL26Y+lQQ2LyA0mIaqKiooSpxVWUlKq99nMxYsXMXHiRMyaNQvBwcFC62oKUZUUwAqA9eGo0qBvCYlcaswQ1SqXLl2ClZUVZs6ciR07doDD4QitrylENSUlBXw+X6i+KpSV7eGo0qCGReRSY4aoAsDly5dhaWmJ2bNnY/v27SLNqibjxo1Dfn4+zp8/L7Q8IiICXbp0Qe/evWU93GaLLglJi9YcQlSTkpJgYWEBTU1NfPHFFyL5gCoqKpg1a5bE7S0sLGBkZIQ5c+YgODgYXbp0QXh4OE6cOIGQkBBwufJz3kENi7RozSFENSEhAUVFRSgqKoKLi4vIem1t7RobFofDweHDh2Fvb48JEyYAAFRVVeHr6wsnJ6cGG3dzRA2LtGhqamq4fv06oxDV2l6RiY+Pr9N6R0dHODo6Mh+0GPr6+jhz5gxyc3NRVFSEzp07i3wjynQ8da1rDqhhEbnQXEJU60tTUxOamppNPYwmIz8Xv4QQ1qOGRQhhDWpYhBDWoIZFCGENaliEENaghkUIYQ1qWIQQ1qCGRQhhDWpYhBDWoIZFCGENejWHtEi3b99GWFgYHj9+DGVlZejr62P06NEwNTUVvIPX0MGp0tSJwzQ4VZqA1ZcvXyIoKAjDhw9vlBe/ZY3OsEiLExoaikGDBiEsLAxlZWXIyMjA/v37YW5ujuzsbEFdQwWnSlsnDtPgVGkCVq9cuYKBAwfCz8+PVS88V0cNi7Qob9++hbu7O0xMTJCeno6YmBjExcUhKysLycnJYtNnpNEYQaVMg1OlCVgNCgrCiBEjMGHChHpnMTYlalikRXn+/Dnevn0LS0tLoT9MDoeDPn361Hv/jRFUyjQ4lWldWVkZDh06hE2bNmHz5s0oLS2VajzNCd3DIi1K1TxRFy9exPLly2W+/8YIKmUanMq0TlFREVevXoWCgoJMUn+aEjUs0iLw+Xzs3r0b3333HTw8PLB+/XqMHj0aK1euxLBhwyRu11DBqfUJKmUanNoQAavNHTUs0iJUVlbizp07WLNmDfz8/KCrqwsfHx8MHz4cvXv3hru7OxwcHETmP2+s4FRpMA1OlceAVWpYpMVwdXXF559/LvjP8+bNQ3h4OIKCguDo6IiIiAhER0cL3VNqjOBUSY4ePYqXL18KfjcyMoKhoSHj4FR5DFilhkVaLCUlJTg4OMDe3h5eXl5Yt24dwsLC4ODgIKhp6ODUmgQEBAjNI7927VoYGhoyDk6Vx4BV+paQtHgcDgdeXl4A0KjBqbWJj48XCk5dsWIFAObBqfIYsEoNi4jF5/NF/hDY7MGDBwDQaMGp9cE0OFUeA1bpkpCI9b///U/qr+Obg+joaPzxxx8YOnQounbtCmVlZdy7dw/r16+HhoYGZs6c2dRDrBXT4FR5DFilhkXE0tHRQUpKSlMPQ2qampq4cuUK9u/fL1jG4/FgbW0NHx8fVkR9MQ1OlceAVWpYpEUZMmQIHj58iLdv3yInJwccDgf6+vpin0NqqODUutZVxzQ4VdqAVR6Px+pLfWpYpEVSVVWFqqpqUw+j3pgGp8pLwGrLu8glhLRY1LAIIaxBDYsQwhrUsAghrEENixDCGtSwCCGsQQ2LEMIa1LAIIaxBDYsQwhrUsAghrEGv5hC5VFpaiv379yMuLg5v3ryBtrY2DAwMMGHCBMGc6DExMTh37hzWrVuH1q1bi+zj5MmTOHPmDHx8fMRGZ0VERODGjRsICAgQO3PC6dOncfjwYWRmZkJHRwcWFhawtrZmfAxJSUnYuXMnnjx5Al1dXTg6OsLY2LjOdUzH3ZSa12gIa1RUVOD169fN5kcaBQUFMDY2hrOzMx49eoSKigpcu3YNixYtwk8//SSoi4uLQ2BgIMrLy8XuJz4+HoGBgSKxWWVlZXB2doatrS0CAwNFpukpLCyElZUVzM3NkZqaCi0tLSQnJ8PGxgYzZsxgdAzR0dEYOHAg4uPjoaenh8TERJiYmCAqKqpOdUzG3RzQGRaRmomJCXx8fNC1a9emHooAn8/Htm3bEBwcXGvt5s2bcffuXURHR8PKykqwPC8vDxUVFfUaR3p6OqZMmYLMzExMmzYNhw4dEqlRU1ODoaEhVq9eLXSm4+HhgcDAQCxcuLDG8NV3797BxcUFX3/9NWJjY8Hj8VBZWQlra2u4uLjA3NwcSkpKjOuYjrs5oIZFpPbFF1/g2bNnTT0MIVwuF/Pnz2dUm5aWBkVFRVhaWgot79ChQ73Hcf36dXA4HNy4cQOhoaES63x9fUWWTZ48GYGBgUhJSamxYV28eBEZGRkICQkRTCXD5XLh6emJESNG4NSpU7CxsWFcJ824mxpdEhK50717d5SVldU6H1Zd2Nra4urVq9DT05P6kqqgoAAAoK2tXWNdYmIiAIg0tSFDhoDL5eLq1atS1dV33I2JzrCIXKmoqMD8+fOxfft2WFhYYMWKFXB0dKwxYebSpUtiI7OePHkitr6uoaW7d++GpqZmjTmJwIcAVSUlJZEzQkVFRWhpaQkFrTKpq++4GxM1LCI3Ll26hCNHjuDnn3/GzZs3sWDBAixduhQrV66Era0tvL29xUZ+fXzp2BDCwsIQGRmJvXv31ponKClAFfgQolpb0OrHdWxCDYvIjadPnyI7OxsA0K1bN8TExODu3bvYunUr9u7di8jISPz5558wNzcX2i4pKUmQplzdpk2bsG3btnqPKzY2FnPnzoWrqytmz54tWJ6RkYGTJ08KfudyuZgzZ47EAFXgww352oJWP65jE2pYRK4ZGBggJCQEnp6e+Prrr+Hk5CRyqde9e3e0adNGZFsNDY16f/7FixcxceJEzJo1S+Qbzvv378PZ2VnwO4/Hw5w5c6ClpYWioiKUl5eLPB+Wl5cnFLTKpI5N6KY7IQB69OiBGTNm4OnTp3j16lWjfOalS5dgZWWFmTNnYseOHeBwOELrx4wZIxS0WvW8l4GBAfh8PlJTU4Xq09PTUVxcLBS0yqSOTahhEfKftLQ0qKqqij2bkrXLly/D0tISs2fPxvbt20WaVU3MzMygqKiIyMhIoeURERHgcDgYM2aMVHVsQpeERO5MnToVffr0Qa9evaCrq4tXr14hMjISUVFRWLJkSY0xWbKQlJQECwsLaGpq4osvvhB57klFRQWzZs2SuH379u2xYMECbNiwAdra2hg6dCgSEhKwdu1a2Nra4tNPP5Wqjk2oYRG5o6KiAj8/P5SUlAiWde7cGcHBwVi4cGGDf35CQgKKiopQVFQEFxcXkfXa2to1NiwA8PPzQ3FxMRYvXozy8nJwuVxMnTpVpPkxrWMLDgB+VlYWOnXqVGuxsrIyCgoKxL7o2VL5+/ujoKAA69evb+qhNKpffvkFKSkp2Lp1a1MPhREul4uUlBR8/vnnEmsOHjyIEydOICwsDJWVlcjNzcWrV6+gra2Ndu3aNeJoZefNmzfIzs6Gnp5ejd/6Ma1rrrKzs6Gjo0NnWEQ+cblcdOzYER07dmzqodRLmzZtxD47Vte65o5uuhNCWIMaFiGENahhEUJYgxoWIYQ1qGERQliDGhYhhDWoYRFCWIMaFiGENahhEUJYgxoWIYQ1qGERQliD3iUkBM0jCfrevXsICwtDWloa1NTUMHjwYMydOxeKioqMjoFpwvOLFy+wZcsW3Lt3DyoqKpg4cSImT54sVPP27VtERETg0qVLyMvLg46ODoYNG4apU6c2aRo0nWERudfUSdAAsHz5chgaGiImJgYaGhp49eoVfvjhBwwcOJBRsjXThOf09HT069cPu3btgqamJl6/fo1vv/0WHh4egprHjx+jW7ducHV1RV5eHvT09PDo0SPMmDEDNjY24PP5tY6nodAZFpF7TZ0EDQCff/459u7di+nTpwuWRUdHY/z48di+fTuWLVsm8TOkSXhetmwZKisrcefOHUH+YUBAAJYuXYrp06djwIAB6NGjB1auXIlvv/1WaDaL9evXY/ny5bhw4UKtUWQNhc6wiNyrKQmayTxxNameqNyjRw+Jdfb29kLNCgCsrKygrKyMlJSUGj+jKuHZ3d1dJOE5Ozsbp06dAgCUlJTgr7/+gr29vVBYq6urK1RUVLB//37BsoULF4pMvTN27FgAH87Amgo1LCL3mmsSdHFxMcrKymSWBH337l1UVFSI1CkrK8PQ0FAoCVqc8+fPA0CThlfQJSGRO+np6Zg0aRJevnyJXbt2Ndsk6L1796KyshJTpkypsU6aJGgA0NfXF9lH586dceHCBaFl+fn5yMvLw4sXL3DixAkEBgZiyZIlGDx4cJ2ORxaoYRG5c+vWLejq6uLIkSMIDQ3FmDFjml0SdEpKCpYvXw57e3ux3/RVJ00SNACxteKSoDdu3AhfX18AHzIRFy1aVOO9tMZADYvIJUVFRejr6wu+BWxOSdDPnj3D2LFj0bdvX/zyyy+C5bJIggYgtlZcEvT3338PW1tbFBQUIDk5GZs3b0ZYWBguXLiAzz77rN7HWRfUsAippqmToLOysjBq1Ch07NgRMTExQo1RFknQVcs+lpubK3IZXH3O++HDh+Pbb79F586d8dNPP+HAgQP1Pta6oJvuhIjRFEnQ2dnZMDU1hYaGBs6cOSPSAOubBN23b18AHxrfx+7fv1/rzXQtLS107dqVviUkpDlqzCToFy9eCJpVbGws1NXVGW/LNOFZW1sbxsbGInU3btzAkydPBI8tSPL8+XP8+++/NT6e0dDokpDIvaZOgn7z5g1GjhyJ9PR0rFmzBuHh4SI1dnZ2EpuYNAnPXl5esLGxgaurKxwcHJCdnQ03Nzd069ZN8BzYnj17EB8fD0tLS3zyySfgcrm4f/8+1q1bBy6XCzc3t4b5h2CAGhaRe02dBJ2dnS24TFu6dKnYmhEjRtR41sU04dna2hrbtm3Djz/+KAjJ/eqrr7Bnzx7BTfcePXpgy5Yt2L17t2A7BQUFmJiYYMeOHRg0aFC9jrc+KPm5FpT83PKSnydOnIjw8HChSyN5S4KuqKjA06dPoaGhIfGZs8LCQuTk5IDD4UBbWxuqqqoNNexaUfIzIdXIWxJ0q1atar0XpaamBjU1NVkNTSbopjshhDWoYRFCWIMaFpErFRUVuH//vsQnw0nzRg2LyJUbN25g37596Nq1a1MPhdQBNSwiV0pKSjBr1ixkZGQ09VBIHUj1LSGfz8fevXsFL1HKg4SEhCZ9spcQ8v+kbljXr1+v8/w+bPT06VPBO1iEkKYlVcPicrnYvn27XD44SghpenQPixDCGtSwCCGsQa/mEFJNVlYWdu/ejdu3b4PP50NHRwdfffUVxo0bJ3hNpaEDVU+fPo3Dhw8jMzMTOjo6sLCwgLW1NeNjYBqoWlvdr7/+KjLHVnW9evWCo6Mj43HJAp1hEfKfmzdvolevXvD19UV+fj6Kiopw8uRJTJ8+HdHR0YK6hgpULSwshJWVFczNzZGamgotLS0kJyfDxsYGM2bMYHQMTANVmdRduXIFUVFRYn8CAwOF/k0aC51hEfIfT09P8Hg8JCcno0uXLoLljx49Eps0Iw0mgapqamowNDTE6tWrhc50PDw8EBgYiIULF4pEdFXHNFCVaV316WWqqwpSZdpEZYnOsAj5T1paGoyMjISaFQD07Nmz3t+MMw1U9fX1Fbl8mzx5MgDILFCVaZ0kAQEB+OSTTzBx4sSaD7oBUMMi5D/du3dHYmIiCgsLZb7v+gSqVj1WI6tAVaZ14ty9excnTpyAm5tbkzyPSZeERO4oKSkhPT0dDg4OgmU///wzVqxYgfHjx8PY2BirV6/GpEmTxN5Ur9JYgaq7d++GpqYmTE1Na6yTJlCVSZ04AQEBaNeuHebOnVunY6kvalhE7gwePBiff/650APBVaGhsbGxcHNzw7Rp06ClpQUnJyd4eHiInYG0MQJVw8LCEBkZib1799Y4gyggXaAqk7qPPXv2DL/99hsWLVrUKMEc4lDDInLJxsZG7PJRo0bhzp07iI2NxebNm+Hj44MDBw4gLi5O5N5WQweqxsbGYu7cuXB1dcXs2bMFyxMSEpCUlCT4XU9PDxYWFlIFqjKp+9jGjRsBAK6urnU6HlmghkXIRzgcDsaOHYuxY8fi+PHjsLGxgbe3N/bt2ydU15CBqhcvXsTEiRMxa9YsBAcHC62LioqCv7+/4PdRo0bBwsJCqkBVJnXVFRQU4Ndff8W3335b729M64NuuhNSAysrKxgZGQmd0TS0S5cuwcrKCjNnzsSOHTvA4XCE1vv6+goFqlZ9q8c0UJVpXXXbtm3DmzdvsHjxYlkeqtSoYZEWQVlZWeQPWxZKS0vx9OlTRqlSsnD58mVYWlpi9uzZ2L59u1THxDRQlWldldLSUmzZsgWmpqYYOHBgHY9MNuiSkLQIOjo6CA8Px6pVq2qs4/P5Ype/fPkS9vb2+D/27jyqiXv9H/g7GGRzAUUomy2oFZUqKngREHcRFXFr0QttAW0BlbqBuIDVCi54qaIo7iJFaSlWayl6qWiluLQWWypIEb3KJiCgICKrmd8ffpmfMQlMSADTPK9zOKfMPJl8hlOf85nJ5POeMmUKzMzM0Lt3bxQWFiIyMhIlJSU4dOhQewxbSEZGBpycnKCrq4v33ntPJFNQU1MTH330kcTXcw1UlSZ4FQCOHz+O0tJSHDlyRP4nLSVqWOQfgcfjscnFLamsrMTly5cxbtw4oe3q6uqoqKiAv78/e0Oax+PBysoKSUlJmDp1ansMW8iNGzdQXV2N6upq+Pr6iuzX19dvsWEB3ANVudYJBAKEh4fD3Ny8Qz4V5YIpLi5muFBXV2dqa2s51f5TbNu2jQkMDOzsYXS4yMhIZsmSJZ09DM769+/P5ObmtlgTGxvLdOnShYmLi5NYU19fzxQWFjK5ubkK/f96dXU1k5ubyzx//lwudZ2tuLiYAcDQDIuQV3Tt2hVGRkadPQyZcQ1U5Vr3pqCb7oQQhUENixCiMKhhEUIUBjUsojQkLbhHFAc1LKI0zp071y4Pl5KOQw2LKBVp16IibxZqWIQQhUENixCiMKhhEUIUBjUsQojCoK/mEKVXV1eHmJgYpKam4tmzZ9DX14eFhQVmzZoFExMTAC8TdQ4dOoSFCxdi0KBBIsfIzc3FgQMH4OnpiSFDhojsT09PR1xcHLy9vUVWQwCArKwsxMbGIicnBz169MCoUaOwcOFCqKmpcTqH0tJS7NmzB1lZWdDU1MTs2bPZtJ221GVlZSE6Ohq5ubnQ0dHB6NGj8fHHH3MeT3uhGRZRak+ePIG1tTV8fHxw9+5dNDY24vr161ixYgU2b97M1t2/fx/h4eG4d++e2OPk5eUhPDwcubm5IvsOHjwIOzs7hIeHiw2oWLt2LSwtLZGUlAQdHR1UVlZi2bJlGDFiBKqqqlo9hwcPHmDo0KE4cuQIdHV1UVVVhQ8++AD+/v5tqvvuu+8wbNgw/PTTTzAzM4NAIMDKlSthaWnJaTztiWZYRKnt3r0bmZmZSExMxPTp09ntFRUVaGxslOnYz58/h6+vL77++mv4+Phg9+7dYusGDhyI6OhooeVxEhMT4ezsjKioKKxZs6bF91mzZg0EAgH++usvNgosLCwMgYGBcHNzw/Dhw6WqW79+PUaMGIFr166xST9eXl4YN24cYmJiOnVNd5phEaWWk5MDNTU1kbWeevfuLfMqow8fPsTVq1eRkpIiMfQCADw8PETW8po+fTo0NDRaDU+tra3Fd999Bw8PD6HcQj8/P2hqaiImJkaqOgAoKyuDlZWVUCzZqFGjALxc6LAzUcMiSs3MzAz19fW4fv263I/dv39//P3337C3t5f6gdXnz5+jvr6+1fDUzMxMNDY2ioSiamhowNLSkg1F5VoHAHZ2dvjhhx9QWFjIbjtx4gRUVFTg5OQk1XnIG10SEqVz7do18Hg8DB8+HIsXL0ZUVBScnJywbt06LFq0SGxqTLNbt26JTcqRFFLR1vDU6OhoCAQCvP/++y3WFRUVAYDYJBsTExP8/PPPUtUBLy+TJ0yYAGtra6xduxY5OTk4evQo9u/fD1tb2zadj7xQwyJKRUVFBbm5uSgtLcUPP/yA2NhY/P7771iyZAkCAwOxYcMGuLq6Ijg4WOzCduvWrWv3MWZnZ2Pt2rXw8PCAtbV1i7XNoafisgRfD0/lUgcAb7/9Nr755hs4ODhg2bJlAIAlS5bAy8urbSckR9SwiFJRUVHBvn378M4777DbTE1NkZSUhMzMTERGRiI6OhoJCQk4deqUyFruBw8eFBsZf/XqVaGw07YqKCiAo6MjhgwZgr1797LbCwsLcf78eaHz8PLygqqqKgCIDUZ9PTyVSx0AnD59GvPnz8fcuXOxevVqnD59Gjt27MCff/6J8+fPd1rqM0ANixCWhYUF9u/fj4CAAIwdOxbe3t4ijyEYGBiInXk9ePBA5vcvLi7GxIkToaenh6SkJKFU6du3b8PHx4f9nc/nw8vLC3369AHw8lPN15WXlwuFp3Kpe/jwIdzc3LBo0SK2YVpaWmLevHmwt7eHt7c3Tpw4IfO5thXddCdKpampSSTB+XX9+vWDu7s78vPzUVlZ2SHjKikpwfjx46Gjo4MLFy6IpEdPmTJFKDy1rq4OANiHVG/fvi1yzNu3b7OhqFzr0tLSUFtbK3L5995772HGjBn46aefZDxT2VDDIkpFIBBwunTLycmBlpZWh1z+lJaWss0qOTkZ2tranF+rr68Pa2trkVDU3377DXl5eXB0dJSqTktLC8DL2d7rioqKRBppR6NLQqLUFixYgMGDB8Pc3ByGhoaorKxEQkICzpw5g9WrV4PPb99/Is+ePcOECRPw4MEDbNq0CXFxcSI18+fPb7GJBQUFwcXFBX5+fvD09ERJSQmWL18OU1NToee7uNSNHz8eRkZG+Oyzz6CiooKRI0eiuroaBw4cwOXLlxEeHi7/P4IUqGERpaapqYmtW7eitraW3WZiYoKIiAgsXbq03d+/pKSEvUwLDAwUWzNu3LgWG9bMmTOxb98+rF+/HpGRkQCA0aNH49ixY0I307nUaWpqIiUlBQEBAXB2dmafHzMyMkJUVJTQfbTOQA2LKLUjR47g0KFDKC8vR2VlJfT19dGzZ0+RuqlTp0qMuQeASZMmtWl///79W3wdV76+vli0aBHy8/Oho6Mj8VkyLnUDBw7E2bNn0djYiMLCQnTv3h26uroyj1EeqGERpaeiogI9PT3o6el19lBkoqqqin79+sm1ztTUVB5Dkxu66U4IURjUsAghCoMaFiFEYVDDIoQoDGpYhBCFQQ2LEKIwqGERQhQGNSxCiMKghkUIURjUsAghCoMaFiFEYdB3CYnS+vPPPxEbG4t79+5BQ0MDxsbGmDx5MsaPHw8+n4+mpiasWbMG48aNw4wZM0ReLxAIsHr1ajg4OGDmzJki+x89eoRdu3bBwcFBZKll4GWcVnR0NNLT08EwDAYPHgxfX1/O32msr6/HwYMHceXKFTQ0NMDe3h6LFy+Gurp6m+qapaam4syZMygoKEBDQwM+/vhjzJkzh9OY2hvNsIhSOnDgAEaOHInY2FjU19ejsLAQMTExmDp1KkpKSgC8XJ00PDxcKFHmVQKBAOHh4bh48aLIvqtXr2LEiBHYunUr0tLSRPZ/++23GDhwIHbt2gU+nw9VVVVERERgwIABSE9Pb3X8DQ0NmDx5MgIDA6GiogItLS1s2LABEydORENDg9R1zbWurq4YO3Ysfv31V+jr6+Ptt98WCqjobDTDIkrn+fPnWLVqFWxtbfHTTz+xMw2GYZCdnS02Cksau3btwg+jtg0AACAASURBVOrVq/Hpp5/iyJEjYmv69+8PPz8/rF27ln3/wsJCWFhYYP369UKBE+IcPXoUv/zyC1JSUjBhwgQAwPXr12FnZ4d9+/Zh+fLlUtUBgL+/P86ePYukpKROzx+UhGZYROmUlpaipqYG06ZNE7os4vF4GDx4sEzHrq+vx8mTJ7Fz507s3r2bXXv9dcOHD8emTZuE3t/Y2Bg2Njatpj0DL4NNrays2CYEADY2NnBwcBBas55rXVFREfbv34+goKA3tlkB1LCIEjIwMACfz8fly5flfmw1NTVcu3YNS5YskTrtGQCePHnSatozwzD4448/RFKcAcDW1hYZGRl4/vw55zoA+OGHH9DY2AgPDw+px9yR6JKQKJ1vvvkG/v7+2LZtGyZPnowNGzZgzJgxEusLCgrE3scSl/EHtD3tOTMzEzdu3EBYWFiLdVVVVaipqZGY4swwDPLz8/HWW29xqjM3N0dmZiZ69+6NFy9eYOHChfj999/Rq1cvTJ48Gf7+/ujatWubzkneqGERpfP5558DAAwNDRESEgIHBwcMGjQIq1atgqenJ1RUhC884uPjER8f365jqqmpgbu7O8zNzVtdS761FOfmGq51wMvLZA0NDYwfP54NqsjMzMSmTZuQlpaGpKSktp+cHFHDIkqjOUR006ZN+Pzzz+Hn54dPPvkEcXFx2LVrFxYtWoT4+HgkJiaySckAsHDhQqxZs0bkeC9evIC5ubnM42poaMCcOXNQVFSEtLQ0oftaZ8+exaNHj9jfraysYGBgwL7/65qamgC8bFKtpT031wEv/zZFRUVITU2Fvb09Wzdo0CD4+Pjg8uXLGDt2rKynKjO6h0WURnPYQ/MMCwDU1dXh6emJP//8E+vWrUNycjJiY2OFXqetrY3+/fuL/HBZF701jY2NcHV1RXp6On766ScMHDhQaH9YWBh8fHzYn6SkJPTq1QtdunSRmOIMAL169eJcBwDdunWDubm5ULMCABcXFwDAX3/9JfO5ygM1LELw8hPCoKAgAEBGRkaHvGdTUxMWLFiAtLQ0XLx4EZaWliI1aWlpQonP69atg6qqKt59912JKc66urowMDDgXAcApqamYhtb8+xM0qedHY0aFiH/586dOwCAt956q93fq7lZpaam4tKlS2xUPFczZszAhQsXUFVVxW6rqanBjz/+yKY4S1v36NEjnDt3Tuh9Ll26BABim2lnoHtYROkkJibi22+/hb29Pd5++21oaGggKysL27Ztg46ODj788MN2H4OXlxcSEhKwdOlSpKWliTwN7+Dg0OIzYZ999hkOHDiAOXPmYOPGjejSpQtCQ0NRXV2NgIAAqesmT54MR0dHfPTRR9i5cyeGDh2K9PR0BAQEYMSIEZg4caL8/whtQA2LKB1dXV1cvXoVMTEx7DY+n4+ZM2ciJCQERkZG7T6G5q/zNCcwvy4qKqrFhmVsbIzExER4eXnBwcEBANC3b18kJCRg2LBhUtcBwKlTp7B06VJ4eXmhsbERKioqcHJywuHDh0U+Oe0s1LCI0rGxsUFubi5qampQVlYGHo8HY2Njkeen1NXVW0xl5vP5bd5fWFjYtsG/YsyYMbhz5w4KCwuhoqICQ0ND8Hi8NtdpaWnh2LFj2Lt3L4qKitCnTx9oa2vLPE55ooZFlJaWlha0tLQ6exgy4fF4MDExkVsd8PIZrQEDBsg6tHbxZszzCCGEA2pYhBCFQQ2LEKIwqGERQhQGNSxCiMKghkUIURjUsAghCoMaFiFEYVDDIoQoDGpYhBCFQV/NIUorMTERZ8+eRWlpKXR0dNCvXz84OzuzS6koU5BqZWUlQkJCxL7PypUrYWhoyGlM7Y1mWEQpubm5wdnZGampqRAIBMjOzkZYWBhcXV3ZGmUKUs3Pz0d4eDi++eYbnDlzRujn1bW0OhvNsIjSuXz5Mk6ePAl/f3/s2LGD3V5fX4+CggKZj6+IQaplZWUAgAsXLogs0/wmoRkWUTo5OTkAgDlz5ghtV1NTQ//+/WU6tqIGqTY3LF1dXe4n2wmoYRGlY2ZmBgASL/VkoahBqmVlZVBRUYGOjo7UY+5IdElIlEqXLl0wYcIE2NraIigoCAUFBVixYkWL6z8pQ5BqWVkZVFVVsXTpUjx69Aja2toYOnQovLy80K1btzadT3ugGRZRGr1790aPHj2wefNmJCcnw9fXF0ePHsW7776LiRMnsoELr4uPj8f48eNFfiZNmiS3sXV2kOrw4cMxZMgQlJeXo1u3brh37x7byN+UiC+AZlhEiejo6GDZsmVsLmFkZCSCg4Nx6NAhREZGYsKECdi4caNQbiHQeUGqL168wLFjx4RqnZ2dOQekShOkOnv2bMyePVuo5ubNmxgzZgwWL14s9pPOzkANiyiVw4cPCzUkfX19BAUFYdmyZZg7dy42bdoEd3d3oZDU5iDV1zX/o5fFq0Gqr39C19TUBB8fH6H6QYMGYdSoUXIPUhVnxIgRmDt3LmJjY9HY2CiUht1Z6JKQEADdu3fHypUrwTAMbt261SHv2VqQqpqamlCIalNTE+zs7NolSFWS7t27txi00dGoYRHyf5ofd1DGIFVx6urq2Eb6JsyuALokJEooJCQEjx8/xogRI2BsbIwXL14gLS0N27dvh42NDUaNGtXuY3jTglTnz5+PMWPGYNCgQejduzf+97//YefOncjJycEPP/wg/z9AG1HDIkpHV1cXERER2LlzJ7ute/fu8PHxQXBwcIeEhr5pQao9e/bE6tWr2eeyAGDo0KH44YcfMH369LafqJxRwyJKx8fHBz4+PqisrGQ/xhd3GahMQaoHDhxAVFQUysrKUFlZCV1dXfTu3VvmMcobNSzyjyAQCFBUVNTivZbmZ46aaWtrv3HJxtKSZ5CqiooK9PX1W33SvjNRwyL/CO+//z4+/PDDFi/nKioq3vivnpCWUcMi/wjbtm3Dtm3bWqz59NNPce7cuQ4aEWkP9FgDIURhUMMihCgMaliEEIVBDYsQojCoYRFCFAY1LEKIwqCGRQhRGNSwCCEKgx4cJUqprq4OMTExSE1NxbNnz6Cvrw8LCwvMmjWL/QpLTk4ODh06hIULF2LQoEEix8jNzcWBAwfg6emJIUOGiOxPT09HXFwcvL29xa4Zn5WVhdjYWOTk5KBHjx4YNWoUFi5cCDU1NU7nUFpaij179iArKwuampqYPXs25s2b1+a627dv4+jRo7h37x709PTg7u6OMWPGcBpLR6EZFlE6T548gbW1NXx8fHD37l00Njbi+vXrWLFiBTZv3szW3b9/H+Hh4bh3757Y4+Tl5SE8PBy5ubki+w4ePAg7OzuEh4cjLy9PZP/atWthaWmJpKQk6OjooLKyEsuWLcOIESM4BZc+ePAAQ4cOxZEjR6Crq4uqqip88MEH8Pf3b1Pd2bNnMWLECJw9exa9e/fGnTt34ODggNDQ0FbH0pFohkWUzu7du5GZmYnExEShpVMqKirQ2Ngo07GfP38OX19ffP311/Dx8cHu3bvF1g0cOBDR0dFwc3NjtyUmJsLZ2RlRUVFi15B/1Zo1ayAQCPDXX3+xX1YOCwtDYGAg3NzcMHz4cM51DQ0NWLRoEWxtbXH+/Hl07doVALB161YEBQXB0dERVlZWMv1d5IVmWETp5OTkQE1NDdOmTRPa3rt3b5lXG3348CGuXr2KlJQUuLi4SKzz8PAQalYAMH36dGhoaLQapFpbW4vvvvsOHh4eQisr+Pn5QVNTEzExMVLVXb9+HWVlZVi2bBnbrABg9erVMDAwQHR0NOfzb2/UsIjSMTMzQ319Pa5fvy73Y/fv3x9///037O3tpQ5Sff78Oerr61td3iUzMxONjY0iAakaGhqwtLTEtWvXpKp79OgRAMDIyEiorkuXLrCyssKvv/4q1Xm0J7okJEqjedG6xYsXIyoqCk5OTli3bh0WLVrUYnrMrVu3xIaJZmRkiK1va5BqdHQ0BAIB3n///RbrioqKAEBiQGpz6CvXurfffhsAcPfuXaFLP4ZhcPfuXZF1xDoTNSyiNPr27Qt3d3cYGhri999/x5IlSxAYGIgNGzbA1dUVwcHBYuO81q1b1+5jy87Oxtq1a+Hh4QFra+sWa1sLSG3ez7Vu2LBhePfdd7Fp0yaMGDEC7777Lp48eYLAwEDcuXMHZmZmMp2bPNElIVEqzbMfU1NTJCUl4datW/Dw8MA333yDYcOG4fz58yKvOXjwIHJzc0V+jh8/LpcxFRQUwNHREUOGDMHevXvZ7YWFhTh8+DD7c/ToUQBoNSC1uUFxrevatSu+/vprCAQCDBw4ED179oSenh7U1NRgZ2f3Rq1ASjMsotQsLCywf/9+BAQEYOzYsfD29hZ5DMHAwEDszOvBgwcyv39xcTEmTpwIPT09JCUlsRHywMvnol4NUuXz+fDy8kKfPn0AQGJAavPlLdc64GVUfWZmJrKyslBaWorBgwfDxMQEpqamsLW1lfk85YVmWIQA6NevH9zd3ZGfn4/KysoOec+SkhKMHz8eOjo6uHDhgsjyzVOmTBEKUa2rqwMA9iFVSQGpzRmHXOuaqaqqwtLSEo6OjjAxMcHdu3fx4MEDjB8/XvaTlRNqWIT8n5ycHGhpaYm9wS5vpaWlbLNKTk6WKgxDX18f1tbWSEhIENr+22+/IS8vjw1I5VonjkAgwMqVK9GrVy/Mnz9fijNrX3RJSJTOggULMHjwYJibm8PQ0BCVlZVISEjAmTNnsHr1avD57fvP4tmzZ5gwYQIePHiATZs2IS4uTqRm/vz5LTaxoKAguLi4wM/PD56enigpKcHy5cthamoq9HwX17r79++jpqYGPXv2xO3bt7Fjxw78/PPPOHXqVIc0cK6oYRGlo6mpia1bt6K2tpbdZmJigoiICCxdurTd37+kpIS9TAsMDBRbM27cuBYb1syZM7Fv3z6sX7+eDWMdPXo0jh07JvSpINe6U6dOsUnQPB4PY8eOxeXLl2FnZyfbycoZDwBTXFzM6QlfDQ0NPHnyBOrq6u0/sjfE9u3b8eTJk1YTWf5p9u7di+zsbInJxIooNDQUtbW1CAkJgUAgQHl5OSorK6Gvr4+ePXt29vDapLGxEfn5+dDR0WnxWbLW6pqamlBQUACGYfDWW28J3fx/E5SUlMDAwIBmWEQ5qaioQE9PD3p6ep09FJmoqqqiX79+Mtfx+XyYmprKc2jtgm66E0IUBjUsQojCoIZFCFEY1LAIIQqDGhYhRGFQwyKEKAxqWIQQhUENixCiMKhhEUIUBjUsQojCoK/mEKX3559/IjY2Fvfu3YOGhgaMjY0xefJkjB8/nl25Yc+ePRAIBFi2bJnYY+zduxcNDQ1YsWKFyL6mpibs2rULGhoaWLJkicj+xsZGnDhxApcuXUJ1dTVMTU3x0UcfYdiwYZzP4fvvv8eZM2dQXl6OIUOGwM/PTyRUgmtdWVkZoqOjkZ6eDoZhMHjwYPj6+r4RX2OiGRZRagcOHMDIkSMRGxuL+vp6FBYWIiYmBlOnTkVJSQlbd+LECXz11VcSjxMXFyd2yeSHDx9i3LhxCAgIELuMzK1btzBs2DAsXboUT58+hY6ODn744QeMGDECBw4c4HQOgYGBmDVrFoqLi2FoaIgTJ05g+PDhuH//vtR13377LQYOHIhdu3aBz+dDVVUVERERGDBgANLT0zmNp70xxcXFDBfq6upMbW0tp9p/im3btjGBgYGdPYwOFxkZySxZsqSzhyFXISEhzPr169nfnz17xmhpaTH29vZC/18LBAImKytL6LX/+te/mJEjR0o8tp2dHTNs2DChbSkpKYyenh5jZ2fH2NjYMHZ2diKvq6ysZPz8/JiHDx+y2xoaGhgbGxumR48eTH19fYvndPv2bQYAExwczG6rqKhgjIyMGBcXF6nrbt68yWzYsEHo71FQUMD07NmTcXR0bHEs7am4uJgBwNAMiyitoqIi1NTUYNq0aUJLJvF4PAwePFjm4yckJGDatGlISUlhAyFe17NnT+zevRsGBgbsNlVVVbi4uODp06dsVJckJ0+eBJ/Px8qVK9ltvXr1wieffILExER2PXeudcOHD8emTZuE/h7GxsawsbFpNeC1I1DDIkrLxMQEfD4fly9fbpfj79mzB8eOHYOamprUoapPnjxBly5doKur22LdzZs3YW5uLrLYn62tLV68eIEbN25IVdfSeN6E9By66U6UyqNHj3D58mXw+XzY2dnB398f27Ztw+TJk7FhwwaMGTNG4murq6vZ8NHXVVVViQSotjVQta6uDnFxcZg6dSq6d+/eYm1RUZHEoFTg/yf7cK0TJzMzEzdu3EBYWBjHM2g/1LCI0igtLcXZs2dx584ddOvWDdbW1ti6dSsMDQ0REhICBwcHDBo0CKtWrYKnpydUVIQvQO7cudNigow0n+q1ZOnSpaioqMCOHTtarX327JnEoNTm/dLUva6mpgbu7u4wNzfvkOWjW0MNiyiNuro6qKqqisyS/Pz88MknnyAuLg67du3CokWLEB8fj8TERKF7TxYWFjh9+rTYY8+fPx9NTU0yj3Hjxo04duwYvv76awwaNIjdfvbsWTx69Ij93crKCpaWllBVVZUYlApAKFSVS92rGhoaMGfOHBQVFSEtLe2NWBqdGhYhANTV1eHp6QkPDw8EBQVhy5YtiI2NhaenJ1ujpqYmNlC1+fWSZilc/ec//8HmzZtx9OhRvP/++0L7wsLCcP36dfb3L774ApaWlujTp4/EoFQAQqGqXOqaNTY2wtXVFenp6bhw4QIGDhwo07nJC910J+QVPB4PQUFBAICMjIwOe9+dO3dizZo1iI6OxscffyyyPy0tTShUdd26dQBezvqys7PBMIxQfXMqT3NYKtc64OWsa8GCBUhLS8PFixdhaWkpvxOVETUsQl5z584dAOCUJCUPERERCAgIQExMDD788EOpXjtjxgw8fvwYly5dEtoeHx+Pvn37speVXOuam1VqaiouXbokkg7d2eiSkCitxMREfPvtt7C3t8fbb78NDQ0NZGVlYdu2bdDR0ZG6ebTF0aNHsXz5ckyZMgVPnz7F/v37hfb3798fkyZNkvh6JycnWFlZwcvLCxEREejbty/i4uJw7tw57N+/n/3ggGudl5cXEhISsHTpUqSlpSEtLU3o/RwcHOTyjFpbUcMiSktXVxdXr15FTEwMu43P52PmzJkICQkR+108ebt48SIAIDk5GcnJySL7XV1dW2xYPB4Pp0+fhoeHB2bNmgUA0NLSQmhoKLy9vaWuax6PpDzKqKgoaliEdAYbGxvk5uaipqYGZWVl4PF4MDY2Fvv81Ks3vMV5fSbCdX9sbCxiY2O5D1oMY2NjXLhwAeXl5aiurmYfiG1LXWFhoUxjaW/UsIjS09LSgpaWVmcPQ2a6urqtPhkvTd2biG66E0IUBjUsQojCoIZFCFEY1LCI0njx4oXYr6cQxUENiyiN+/fvC33VhigealhEqezatauzh0BkQA2LEKIwqGERQhQGNSxCiMKghkUIURjUsAghCoO+S0iUWmJiIs6ePYvS0lLo6OigX79+cHZ2Zhety8nJwaFDh7Bw4UKhJYub5ebm4sCBA/D09MSQIUNE9qenpyMuLg7e3t4YMGCAyH5ZU5ZLS0uxZ88eZGVlQVNTE7Nnz8a8efMk1sfHx+O3335DWFiYyJr1AFBfX4+DBw/iypUraGhogL29PRYvXvxGLI8M0AyLKDE3Nzc4OzsjNTUVAoEA2dnZCAsLg6urK1tz//59hIeH4969e2KPkZeXh/DwcOTm5orsO3jwIOzs7BAeHo68vDyR/bKmLD948ABDhw7FkSNHoKuri6qqKnzwwQfw9/cXqa2vr4ePjw9cXV0RHh4uNnasoaEBkydPRmBgIFRUVKClpYUNGzZg4sSJaGhoaHU8HYFmWEQpXb58GSdPnoS/v79QOk19fT0KCgpkOvbz58/h6+uLr7/+Gj4+Pti9e7fYuv79+8PPzw9r165lZzCFhYWwsLDA+vXrcf78+RbfZ82aNRAIBPjrr7/YzMCwsDAEBgbCzc0Nw4cPB/Cysb3//vt4+PAh/v3vf+PkyZNij3f06FH88ssvSElJwYQJEwC8XFbHzs4O+/btw/Lly9v095AnmmERpZSTkwMAmDNnjtD2loImuHr48CGuXr2KlJQUuLi4SKyTJWW5trYW3333HTw8PIQCTv38/KCpqSm0KOGvv/4KHo+H3377Df369ZN4zBMnTsDKyoptVsDLNcMcHBxw/PjxFsfTUahhEaVkZmYGABKDUWXRv39//P3337C3t5c68RnglrKcmZmJxsZG2NjYCG3X0NCApaUlrl27xm5zdXXFtWvXYGRkJHE8DMPgjz/+EDke8DIdOiMjA8+fP5f6XOSNLgmJ0tDU1IRAIEBwcDA2bdoEW1tbBAUFoaCgACtWrBB7U7zZrVu30K1bN5HtkpJ12pr6zDVluaioCAAkpjm/3ohbG09VVRVqamokHo9hGOTn58Pc3LyVM2hf1LCI0tDU1ES/fv3w+eefY/PmzUhOTkZgYCAOHz6MqKgoTJgwAUFBQWLTnZtjtdqTNCnLzRmIktKcpc1IbO14r9Z0JmpYRKnweDzw+Xx8/vnnAF6GLQQHB+PQoUOIjIzEhAkTsHHjRnZ/s4MHD4ptZFevXhWbIygtSSnLL168wLFjx4RqnZ2d2URqSWnO4hpPS1o7HiC+mXU0alhE6enr6yMoKAjLli3D3LlzsWnTJri7uwvdoDYwMBB7M/7Bgwcyv39LKctNTU3w8fERqh80aBD69OkDABLTnF9Pcm5Nr1690KVLF6nSoTsD3XQn5P90794dK1euBMMwuHXrVoe8Z2spy2pqakKJz01NTbCzs2MfUm1Obn7V7du3pQ5AVVVVxbvvvivxeLq6ujAwMJDqmO2BGhYhr2h+3KEjUp9lSVnW19eHtbU1EhIShLb/9ttvyMvLg6Ojo9TjmTFjBi5cuICqqip2W01NDX788cc2Ha890CUhURrdu3dnPy0LCQnB48ePMWLECBgbG+PFixdIS0vD9u3bYWNjg1GjRrX7eGRNWQ4KCoKLiwv8/Pzg6emJkpISLF++HKampnBzc5N6PJ999hkOHDiAOXPmYOPGjejSpQtCQ0NRXV2NgIAAqY/XHqhhEaUxYcIEduakq6uLiIgI7Ny5k93fvXt3+Pj4IDg4WOz37ORN1pTlmTNnYt++fVi/fj17jNGjR+PYsWNtukFubGyMxMREeHl5wcHBAQDQt29fJCQkYNiwYVIfrz3wADDFxcWcpsAaGhp48uTJG/NFyI6wfft2PHnyBNu2bevsoXSovXv3Ijs7W+I/JkV04sQJnDt3TihpubKyEuXl5ejWrVuHXAa2h8bGRuTn50NHR0cuN8YZhkFhYSFUVFRgaGgIHo8nh1HKpqSkBAYGBjTDIspNW1sb2tranT0Mmaiqqrb4lRtp8Xg8mJiYyO148kQ33QkhCoMaFiFEYVDDIoQoDGpYhBCFQQ2LEKIwqGERQhQGNSxCiMKghkUIURjUsAghCoMaFiFEYdBXc4hSqqurQ0xMDFJTU/Hs2TPo6+vDwsICs2bNYr+WkpSUhIsXL2LLli3o2rWryDHOnz+PCxcuICQkROz3a1sLLf3pp59w+vRpPHz4EAYGBnBycsLMmTM5n0NGRgYOHTqEvLw8GBoaYtGiRbC2tm5z3auKiooQFBSE0aNH49NPP+U8pvZGMyyidJ48eQJra2v4+Pjg7t27aGxsxPXr17FixQps3ryZrUtNTUV4eLjEENG0tDSEh4ejrq5OaHtroaVPnz7F9OnTMXXqVPz999/o06cPbt26BRcXF7i7u3M6h8TERIwYMQJpaWkwMjLCzZs3YWtrizNnzrSp7lUMw8DDwwPR0dFITU3lNJ6OQjMsonR2796NzMxMJCYmYvr06ez2iooKNDY2ynRsLqGlPXr0gKWlJTZu3Cg00/H390d4eDiWLl0qNm6rWVNTE3x9fTF27FgkJyeDz+dDIBBg5syZ8PX1xdSpU6Gurs657nURERHIysqChYWFTH+L9kAzLKJ0cnJyoKamhmnTpglt7927t8xLzHANLQ0NDRW5LJs3bx4AtBqievnyZRQWFmLVqlXg81/OOVRUVBAQEICSkhL897//laruVVlZWVi7di2+/PJLMAzD/cQ7CDUsonTMzMxQX1+P69evy/3YXEJLJXny5AkAtBqievPmTQAQmYXZ2NhARUWFDVHlWtesoaEB7u7umDVrFubPn8+m5bxJ6JKQKI1evXqhT58+WLx4MaKiouDk5IR169Zh0aJFLS5898svv4hdwTMvL09sfVtDVI8ePQpdXV2xcWKvKioqgrq6Onr37i20XU1NDX369GGTfLjWNQsODkZFRQWioqLaNP6OQA2LKA0nJydcuXIFhoaG+P3337FkyRIEBgZiw4YNcHV1RXBwsNgor9cvHdtDbGwsEhISEB0d3eryxs+ePZNY82qIKtc64OUHDF9++SWSk5Pf6AUNqWERpRISEgIAMDU1RVJSEjIzMxEZGYno6GgkJCTg1KlTmDp1qtBrMjIy2PTjV+3cuRP79u2TeUzJyclYuHAh/Pz8hEJZCwsLcf78efZ3FRUVeHl5QVVVVWzgKSAcosq17unTp/joo4+wfPnyVmd3nY0aFlFqFhYW2L9/PwICAjB27Fh4e3uLXOqZmZmhW7duIq/V0dGR+f0vX76M2bNn46OPPkJERITQvtu3bwuFqPL5fHh5eaFPnz6orq5GQ0ODyPNhFRUV7OUt17rly5fj+fPncHJyEkruqa2tRVlZGdLS0vDOO+/A2NhY5vOVFd10JwRAv3794O7ujvz8fFRWVnbIe/7yyy+YPn06PvzwQxw8eFAk7GHKlClCAarNz3tZWFiAYRj8/fffQvUPHjzA8+fP2XxDrnWpqako3y4HBwAAIABJREFUKyvDxIkTMWbMGPYnPz8fycnJGDNmjFBwR2eiGRYh/ycnJwdaWlpiZ1PyduXKFUybNg0ff/wxIiMjpUqmmTRpEtTU1JCQkCAUvhofHw8ej4cpU6ZIVZecnCz24dhp06bBwsICYWFh0NPTa+upyhU1LKJ0FixYgMGDB8Pc3ByGhoaorKxEQkICzpw5g9WrV7PPLLWXjIwMODk5QVdXF++99x4OHDggtF9TUxMfffSRxNf36tULS5YswY4dO6Cvrw97e3vcuHEDX3zxBVxdXTFgwACp6szMzMS+T9euXdGjRw+Ym5vL6cxlRw2LKB1NTU1s3boVtbW17DYTExNERERg6dKl7f7+N27cQHV1Naqrq+Hr6yuyX19fv8WGBQBbt27F8+fPsXLlSjQ0NEBFRQULFiwQaX5c6xQFBam2goJU/zlBqq8SCAQoLy9HZWUl9PX10bNnz84eUps8e/YMJSUlMDIyavFxCK51byoKUiVKTUVFBXp6em/MvZm26tatm9hnx9pa96ajTwkJIQqDGhYhRGFQwyKEKAxqWIQQhUENixCiMKhhEUIUBjUsQojCoIZFCFEY1LAIIQqDGhYhRGFQwyKkjYqLixEaGor3338f8+bNg5+fH06ePImnT5+yNUlJSfD395eYbXj+/Hn4+/uLZBs2i4+Ph7+/v8RAi9LSUgQFBWH27Nlwc3NDQkKCVOeQkZGBpUuXwtnZGd7e3rhx44bE2qamJvznP//B3r17OR07JSUFHh4ecs02pIZFSBv8/vvvMDc3R2hoKB4/fozq6mqcP38ebm5uSExMZOvaK4wVeLkQ39ChQ3HkyBHo6uqiqqoKH3zwAfz9/TmdgzQhqw8fPsS4ceMQEBCAuLi4Vo9dVlYGNzc3HD9+HHfu3OE0Hi7oy8+EtEFAQAD4fD5u3bqFvn37stvv3r0r81LCXMJYAWDNmjUQCAT466+/2GiwsLAwBAYGws3NDcOHD5f4HtKErF68eBELFizAgAEDWgx4fdWnn36KYcOGITk5WcqzbxnNsAhpg5ycHFhZWQk1KwDo37+/zMsvcQljra2txXfffQcPDw+hHEM/Pz9oamoiJiamxfeQJmQ1ISEB06ZNQ0pKClRVVVsd/5EjR5CcnIxNmzZxOV2p0AyLkDYwMzPDzZs38fTpU/To0UOux3Z1dcW8efPQpUsXifeuMjMz0djYKDLj0dDQgKWlpUhI6uu4hKy6uLgAAPbs2cNmLbYWDvu///0Py5cvx5dffol33nmnxdq2oIZFiATV1dViZypubm5Yt24dnJ2dYW1tjY0bN2Lu3LkiyTSvkncYa1FREQCIvfw0MTHBzz//3OrruYascg2GffHiBT788EOMHz8e3t7eKCkp4fQ6aVDDIkSCVatWIS8vj137vFloaCh27NiB5ORkLF++HP/+97/Rp08feHt7w9/fX+zqpfIOY20OQRXXBF8PSZX0eq4hq1xt3boVd+/exenTp6V+LVfUsAiRoLGxEQsWLICHh4fY/RMnTsRff/2F5ORk7N69GyEhIfjqq6+Qmpoqcm9L3mGszfeSxAWlvhqSeuPGDWRkZLD7jIyM4OTkxDlklav09HR88cUX+O6779p1FVdqWITIgMfjwdHREY6Ojvjxxx/h4uKC4OBgHD9+XKhO3mGsffr0AfAyEPV15eXlbEjqmTNnsH37dnbfxIkT4eTkxDlklYv6+nq4u7vD1tYW2trabBjr48ePAbz85DQtLQ3Dhg1D9+7dpTvR19CnhITIyfTp02FlZSU0o2kvQ4YMAfAyHfp1t2/fZnMIQ0NDhcJYmz/94xqyykVZWRn+/vtvXL58WSiItfmm/fbt2zFmzBhkZWW16VxfRQ2LEDmpq6tDfn4+pwQqWenr68Pa2lrkyfbffvsNeXl5cHR0bPH1r4asvur1kFUu3nrrLWRnZ4v8/PLLLwCAzZs3Izs7G5aWlpyPKQldEhIipUePHsHDwwNTpkyBmZkZevfujcLCQkRGRqKkpASHDh3qkHEEBQXBxcUFfn5+8PT0RElJCZYvXw5TU1O4ubm1+FquIatc8Pl8sWGrzZ8SvvXWW3ILY6WGRYiU1NXVUVFRAX9/f/bGNY/Hg5WVFZKSkjB16tQOGcfMmTOxb98+rF+/ns2PHD16NI4dO8bpprkihqxSkGorKEj1nxmkyoWnpyfGjh0r8VPChoYGlJWVoba2FsbGxp3276KxsRH5+fnQ0dGR6mZ5M0UIWaUgVUJk1LVrVxgZGXX2MKCqqirxKzxcKFLIKt10J4QoDGpYhBCFQQ2LEKIwqGERQhQGNSxCiMKghkUIURjUsAghCoMaFiFEYVDDIoQoDGpYhBCFQQ2LEKIw6LuEhHBQV1eHmJgYpKam4tmzZ9DX14eFhQVmzZoFExMTAC9Tni9evIgtW7aIDaQ4f/48Lly4gJCQELFflI6Pj8dvv/2GsLAwqKiIziVKS0uxZ88eZGVlQVNTE7Nnz8a8efM4n0NGRgYOHTqEvLw8GBoaYtGiRbC2thZb29TUhF27dkFDQwNLliwR2Z+eni42UFVDQwObN2/mPCZp0QyLkFY8efIE1tbW8PHxwd27d9HY2Ijr169jxYoVQv84lSnl+cqVK/jyyy9x5swZoZ8ff/yR03jaimZYhLRi9+7dyMzMRGJiIqZPn85ur6ioQGNjo0zHVtSU57KyMujr6+Pu3bsynL30aIZFSCtycnKgpqYmEtXVu3dvmZdDVtSU57KyMujq6kpzqnJBDYuQFggEApiZmaG+vh7Xr1+X+/FdXV1x7do1GBkZdWrKc7M9e/bg2LFjUFNTazHlubMaFl0SEiLBo0ePkJWVhVWrViEqKgpOTk5Yt24dFi1a1OLKnsqQ8lxWVoaSkhIsXLgQlZWVMDQ0hL29PT744APweDxOx2gLmmERIsGzZ89w7do1GBoa4vfff4etrS0CAwNhaGiIjz/+WOL9m2nTpmH8+PEiP7GxsW0eB/BmpTzb29tDV1cXdXV10NDQQFpaGubPnw9bW1s8ffpU6uNxRTMsQjgwNTVFUlISMjMzERkZiejoaCQkJODUqVMioROdlfJcWFiI8+fPs/tUVFTg5eUl95RnANiyZYvItv3798PX1xdhYWEICQmR+phcUMMiRAoWFhbYv38/AgICMHbsWHh7e4tc6nVWyvPt27fh4+PD7uPz+fDy8pJrynNLfHx8sGXLFly+fFkuxxOHLgkJaYN+/frB3d0d+fn5qKysbNf34pryPGXKFKGU5+bnveSZ8tya7t27g2EYuR3vddSwCGmjnJwcaGlpiZ1NydOblPLckrt37+LOnTsSn56XB7okJKQVCxYswODBg2Fubg5DQ0NUVlYiISEBZ86cwerVq9lnm9rTm5LyDAAFBQVYsWIFXFxcYGZmBjU1Nfzxxx/YsmULevbsiZUrV8pyqi2ihkVIKzQ1NbF161bU1tay20xMTBAREYGlS5d2yBjepJTn7t27o6ysDJ6enuzN/C5dumDSpEnYtWsX+93K9kDJz62g5GflTX4eO3YsGhsbcfXqVQgEApSXl6OyshL6+vro2bNnp4zpTUp5bmhoQGlpKerq6mBoaAgtLS2ZjtcSSn4mLRo5ciQ+//xzHDlypLOH0mlUVFQwbNgw9r/19PSgp6fXqWN6k1Keu3bt2q6zKXGoYRGxbGxsUFRU1K6f+LzpJk+e3K4PQRLpUcMiEqmpqXX2EDqViopKu17mEOnRYw2EEIVBDYsQojCoYRFCFAY1LEKIwqCGRQhRGNSwCCEKgxoWIURhUMMihCgMenCUECn9+eefiI2Nxb1796ChoQFjY2NMnjwZ48ePZ1du2LNnDwQCAZYtWyb2GHv37kVDQwNWrFghsq+1EFNp68T5/vvvcebMGZSXl2PIkCHw8/ODkZFRm+rKysoQHR2N9PR0MAyDwYMHw9fXt12+xkQzLEKkcODAAYwcORKxsbGor69HYWEhYmJiMHXqVJSUlLB1J06cwFdffSXxOHFxcTh+/LjIdi4hptLUiRMYGIhZs2ahuLgYhoaGOHHiBIYPH4779+9LXfftt99i4MCB2LVrF/h8PlRVVREREYEBAwYgPT1dqnFxxRQXFzNcqKurM7W1tZxq/ym2bdvGBAYGdvYwSCdwcHBgRo8ezf7+7NkzRktLi7G3txf6dyAQCJisrCyh1/7rX/9iRo4cKfHYdnZ2zLBhw4S2paSkMHp6eoydnR1jY2PD2NnZiX0t1zpxbt++zQBggoOD2W0VFRWMkZER4+LiInXdzZs3mQ0bNgj9PQoKCpiePXsyjo6OnMfVmuLiYgYAQzMsQjgqKipCTU0Npk2bJrTEEo/Hw+DBg2U+PtcQU6514pw8eRJ8Pl9okb1evXrhk08+QWJiIrtuPNe64cOHY9OmTUJ/D2NjY9jY2CA7O1uqsXFBDYsQjkxMTMDn89stZIFriCnXOnFu3rwJc3NzaGtrC223tbXFixcvcOPGDanqJHny5IlQSrW80E13Qlrx+eefIz4+HtnZ2fD398e2bdswefJkbNiwAWPGjJH4uurqaokhp1VVVSKhpVxDTLnWiVNUVCQxkBUAG6rKtU6czMxM3LhxA2FhYW0epyTUsAhpRUJCAnbv3o1NmzZh69atMDQ0REhICBwcHDBo0CCsWrUKnp6eUFERvmC5c+cOxo8fL/G4zYsDdiRJoarNOYrNoapc615XU1MDd3d3mJubt8vy0dSwCGmFiooKDAwM8PnnnwMA/Pz88MknnyAuLg67du3CokWLEB8fj8TERKF7ShYWFjh9+rTYY86fPx9NTU3tNuazZ8/i0aNH7O9WVlawtLSUGKraPJbmJsW17lUNDQ2YM2cOioqKkJaW1i5LqVPDIqQN1NXV4enpCQ8PDwQFBWHLli2IjY2Fp6cnW6OmpiZxOWJ1dfU2RcRzFRYWhuvXr7O/f/HFF7C0tESfPn0kBrICYNeJ51rXrLGxEa6urkhPT8eFCxcwcOBAuZ3Lq+imOyEy4PF4CAoKAvAyov5NkZaWJhSqum7dOgAvZ33Z2dkiS183h7Q2h6pyrQNezroWLFiAtLQ0XLx4EZaWlu12XtSwCJHRnTt3AIBT8lRnmzFjBh4/foxLly4JbY+Pj0ffvn0xaNAgqeqam1VqaiouXbok1xRpceiSkBCOEhMT8e2338Le3h5vv/02NDQ0kJWVhW3btkFHRwcffvhhZw+xVU5OTrCysoKXlxciIiLQt29fxMXF4dy5c9i/fz/7wQHXOi8vLyQkJGDp0qVIS0tDWlqa0Ps5ODjI5Rm1ZtSwCOFIV1cXV69eRUxMDLuNz+dj5syZCAkJEftdvDcNj8fD6dOn4eHhgVmzZgEAtLS0EBoaCm9vb6nrLl68CAAS8yujoqKoYRHSGWxsbJCbm4uamhqUlZWBx+PB2NhY7HNRr97wFuf1mYi0+6Wte5WxsTEuXLiA8vJyVFdXsw/EtqWusLBQ6veXBTUsQqSkpaX1j4j/0tXVha6urtzqOgLddCeEKAxqWIQQhUENixCiMKhhEUIUBjUsQojCoIZFCFEY1LAIIQqDGhYhRGFQwyJEguaVDsibgxoWIRJ4eHhgwoQJnT0M8gr6ag4hEmhqanL6rlxiYiLOnj2L0tJS6OjooF+/fnB2dmbXhWpqasKaNWswbtw4zJgxQ+T1AoEAq1evhoODA2bOnCmy/9GjR9i1axccHBwwdepUkf03b97EqVOnkJOTgy5duqB///745JNP8M4773A6z/r6ehw8eBBXrlxBQ0MD7O3tsXjxYpEVQ7nWNUtPT0dcXBy8vb0xYMAATmNpDc2wCJGBm5sbnJ2dkZqaCoFAgOzsbISFhcHV1ZWtaWpqQnh4uMRACoFAgPDwcHblg1ddvXoVI0aMwNatW8V+0XnlypUYOXIkvv/+e2hra0NTUxNHjhyBubk5rly50ur4GxoaMHnyZAQGBkJFRQVaWlrYsGEDJk6ciIaGBqnrmh08eBB2dnYIDw9HXl5eq+OQBgWptoCCVJVXbGws4+bmxlhYWDC3bt0S2f/zzz8zABh/f3+h7XV1dUxubi77e21tLQOAWbVqldj3aWxsZAAwy5YtE9q+c+dORlVVlVmyZAmjrq7OrF+/XuS1N27cYL7//nuhbRUVFYyBgQHj4ODQ6jlGRUUxAJiUlBR227Vr1xgVFRVm586dUtfV1NQwH330EdO1a1fms88+YwAwP/30U6vjaA0FqRIio5ycHADAnDlzhLa3tJY7V/X19Th58iR27tyJ3bt3o66uTmydlZWVyGVkr169YG1tjXv37rX6PidOnICVlZXQvTobGxs4ODjg+PHjUtc9fPgQV69eRUpKClxcXDifL1fUsAhpIzMzMwCQeKknCzU1NVy7dg1LliyROiy1uroa6enprcaIMQyDP/74AzY2NiL7bG1tkZGRgefPn3OuA4D+/fvj77//hr29vdTj5oJuuhPSBjk5OZgwYQJsbW0RFBSEgoICrFixosWbywUFBWKbm7g4LUC6wNS7d++itrYWOTk52L59O/h8PsLDw1t8TVVVFWpqaiQGpjIMg/z8fLz11luc6szNzaUet7SoYRHSBhYWFggKCkJycjICAwNx+PBhREVFYcKECQgKChIboBofH4/4+Hi5j6WpqUmoUVpYWODw4cNsA5GkOWastcBUrnUdgRoWIW20fv168Pl8REZGIjg4GIcOHUJkZCQmTJiAjRs3ssGrzRYuXIg1a9aIHOfFixetNpeW8Pl83Lp1C/X19Xj48CHOnj2LKVOmYMWKFQgPD8eLFy9w7Ngxodc4Ozuzoa+tBaZyresI1LAIkQN9fX0EBQVh2bJlmDt3LjZt2gR3d3f069ePrdHW1hZ7M14eT9NbWFgAAEaOHAlnZ2f06NEDX375JXx9fWFiYgIfHx+h+kGDBmHUqFHo0qVLq4GpvXr14lTXEeimOyFy1L17d6xcuRIMw+DWrVudNg4rKysAwP/+9z+oqakJhao2NTXBzs4OqqqqePfdd9lw1Ffdvn0burq6MDAw4FzXEahhESJnzY87dGawavNDps2fZEoyY8YMXLhwAVVVVey2mpoa/Pjjj3B0dJS6rr3RJSEhbbRlyxZUVlZixIgRMDY2xosXL5CWlobt27fDxsYGo0aNavcxTJo0CdOnT8ewYcOgr6+P8vJynDlzBvv378e8efNafR7ss88+w4EDBzBnzhxs3LgRXbp0QWhoKKqrqxEQECB1XXujhkVIG+nq6mLPnj3YuXMnu6179+7w8fFBcHAwm47cnszMzLBx40Y8ffqU3aanp4eAgACRm/7iGBsbIzExEV5eXnBwcAAA9O3bFwkJCULPcXGta2/UsAhpo08//RSLFy9GZWUlysvL0a1bN7GXgerq6mAYRuJx+Hx+m/cfPHgQ+/btQ1lZGZ4+fYoePXrgrbfeAo/H43weY8aMwZ07d1BYWAgVFRUYGhqKfT3XumaTJk1q8bzaghoWITLS1taGtrZ2p70/n8+HgYGBTDe+eTweTExM5FbXXuimOyFEYVDDIoQoDGpYhBCFQQ2LEKIwqGERQhQGNSxCiMKghkUIURjUsAghCoMaFiFEYVDDIoQoDPpqDiFyUFxcjKNHj+LPP/8EwzAwMDDA6NGjMWPGDPTo0QMAsGfPHggEAixbtkzsMfbu3YuGhgasWLFCZF9TUxN27doFDQ0NLFmyRGR/UVER4uLicPPmTdTW1uLtt9/GvHnzYG9vz/kcvv/+e5w5cwbl5eUYMmQI/Pz8YGRk1KY6eYxHHJphESKj33//Hebm5ggNDcXjx49RXV2N8+fPw83NDYmJiWzdiRMn8NVXX0k8TlxcnFBkVrOHDx9i3LhxCAgIQFxcnMj+hIQEmJqaIjw8HDweD3p6ekhJScGYMWPwn//8h9M5BAYGYtasWSguLoahoSFOnDiB4cOH4/79+1LXyWM8LaEg1RZQkKryailIlc/nM42NjQzDMMy4ceOYXr16MXl5eUI1ubm5Qv9e/vWvfzEjR46U+H52dnbMsGHDhLalpKQwenp6jJ2dHWNjY8PY2dmJvO7x48fM3r17mbq6OnabQCBgnJycmK5duwptF+f27dsMACY4OJjdVlFRwRgZGTEuLi5S18k6HnEoSJUQOcnJyYGVlRX69u0rtL1///5QV1eX6dgJCQmYNm0aUlJS2DCI1+no6GDx4sVQU1Njt/F4PEyePBkNDQ0oKCho8T1OnjwJPp+PlStXstt69eqFTz75BImJiexa7lzrZB1PS6hhESIjMzMz3Lx5U2gRPXnZs2cPjh07BjU1NamDSX/++Wdoa2uLNNLX3bx5E+bm5iJL5Nja2uLFixe4ceOGVHWyjqcldNOdkDZ6+vQptLW1sW7dOjg7O8Pa2hobN27E3Llz0bVrV7Gvqa6ulpgUXVVVJRJCKk0oaVFREaqrq1FQUIDDhw/jp59+QmxsrMSxvPo6SSGpAPDgwQOp6mQdT0uoYRHSRqtXr4ahoSG++OILJCcnY/ny5fj3v/+NPn36wNvbG/7+/ujZs6fQa+7cuSM2ZLWZLMsNu7q64sqVKwBeLt+8c+dOuLi4tPq6Z8+ecQpJ5Von63haQg2LkDaqrKzE1KlTAQATJ07EX3/9heTkZOzevRshISH46quvkJqaKnQJZGFhgdOnT4s93vz582XKKPzqq6/w9OlTlJWV4ZdffkFgYCCOHz+OS5cuQU1NDTdu3EBGRgZbb2RkBCcnJ6iqqnIKSeVax3U8bUENixA54fF4cHR0hKOjI3788Ue4uLggODhY6FEFNTU1iUk26urqMkW+m5qasv89adIkWFlZYebMmYiNjcXChQtx5swZbN++na2ZOHEinJyc0KdPH04hqVzruI6nLeimOyHtYPr06bCyshKa0XS05jDVe/fuAQBCQ0OFwlT/+9//Ang568vOzhYJjGgOTh06dKhUdVzH0xbUsAhpB3V1dcjPz38jwlT79evXYt2MGTPw+PFjXLp0SWh7fHw8+vbti0GDBklVJ+t4WkKXhITIoKqqCtOmTcOUKVNgZmaG3r17o7CwEJGRkSgpKcGhQ4fafQyfffYZtLS04ODgAGNjY9TU1ODatWsICQmBqakpPvjggxZf7+TkBCsrK3h5eSEiIgJ9+/ZFXFwczp07h/3797P5ilzrZB1PS6hhESKDrl27oqKiAv7+/uwNaR6PBysrKyQlJbE35dvToEGDsHXrVmzbto3dpqmpCWdnZ+zYsQPdu3dv8fU8Hg+nT5+Gh4cHZs2aBQDQ0tJCaGgovL29pa6TdTwtoYZFiAw0NDTw66+/oqGhAWVlZaitrYWxsbHYJ9yvX7/e4rGaL5mk3e/r6wsfHx9UVFTg8ePHUFdXh4GBgcQn48UxNjbGhQsXUF5ejurqapiYmIDPF20PXOrkMR5JqGERIgddu3YVu7JBR+HxeNDV1YWurq5Mx+F6jNbq5DWe19FNd0KIwqCGRQhRGHRJSIgE/fr1w40bN9gHI0nnoxkWIRLY2Njg4sWL0NPTw6lTp0T2Z2dnd8KolBs1LEJaYGRkBD6fj7lz5wptZxgGJSUlyMrK6qSRKSdqWIRI6fHjxxAIBKivr8eQIUM6ezhKhRoWIVKqrq4GwzDQ0tLq7KEoHWpYhBCFQQ2LEKIwqGERQhQGNSxCiMKgB0cJkZO6ujrExMQgNTUVz549g76+PiwsLDBr1iw2qCEpKQkXL17Eli1bxIYxnD9/HhcuXEBISIjYL1Cnp6cjLi4O3t7eGDBggNA+gUCAc+fO4fz58ygoKIC2tjbee+89eHt7o1u3bpzOISMjA4cOHUJeXh4MDQ2xaNEiWFtbi9SVlpZiz549yMrKgqamJmbPno158+aJPWZFRQVOnjyJmzdvory8HD169MDx48fFfrm6NTTD+n/t3XlYVOX7P/D3DIMjIggIDAriAhoIqSkoKqjgjiL+1ELDClCTVFQExRRNSzM0chfc0tzog5pkpEVaYeQeiYqIK6Agq4Ls2zy/P7w4X4cZmAUMT92v6+K6vpxzn3Oe0/fy/sx5OPO8CWkGz549g6OjI/z9/XHv3j1UV1fj4sWLCAwMxGeffcbVnTt3DuHh4aiqqlJ4noSEBISHh6OiokJu365duzB48GCEh4cjPT1dZl9NTQ2cnJwwYcIE3LhxA2ZmZigrK8Py5cthZ2encGnj+mJjY9G3b18kJCTA3NwciYmJGDRoEGJiYmTq0tLS0KtXL+zduxfGxsYoKirCO++8g+DgYLlznj17Fm+88QZWr16Nqqoq9OjRAwKBQG7VUnVQ8nMjKPmZ1E9+TktLYwCYqakpO3r0KGOMsVWrVjEALDY2VubY/Px8mX9fISEhDAArLi5WeK3ly5czAOzZs2fcttLSUvb++++zVq1asfnz5zMA7JdffpE7Njo6miUlJclsu3DhAgPAVq5c2eg9VldXMwsLC+bq6solWtfW1rJx48YxMzMzmX/3Xl5ezNjYmGVnZ3PbwsLCGACWmJjIbXv48CHT19dn48ePZ8+fP2/0+spQ8jMhzSg1NRVisRju7u4y29u3b9/kZZKzsrJw/vx5nD17ttGYrLfffltuXXUnJyfo6+srXUc9Pj4ejx8/RlBQEPeoJhQKsXjxYmRnZ3Prv5eXl+O7776Dj48PJBIJd3xAQADatGmDAwcOcNvWr18PkUiEw4cPN2nRvpdRwyKkCSorK1FbW4tu3bqhsrJS6SJ9mrC2tsbt27fh7OysdvpzXSK1srzDxMREAC8a3MucnJwgFApx4cIFAMDNmzdRXV0tV6ejo4M+ffpwdQBw4sQJTJo0Cfr6+mqNuTE06U6IhgwNDTFr1izExsYiPDwcERERGDt2LJYtW4aZM2fKxV697I8//lAYSlp/bqqOqgnQ5eXlyMzMRGFhIS5fvow1a9Zg2LBhmDdvXqPHZWZmonXr1mjfvr3MdrELmyorAAAgAElEQVRYDBMTE5n0ZwANJkDXpVrn5+cjOzsbvXv3xv79+7F//348e/YMtra2WLJkCfr27avS/dRHDYsQDZmbm+P27dvc71evXsXcuXMREhKClStXwsvLCytWrFCYQ1j/0bG5/Pnnnxg5ciT3+4QJE/Dll18qbI4vayjVGXixHvvL6c+AfGhq/bqcnBwAwDfffAOhUIjp06dDKpXi4MGDGDBgAH7//XcMHjxY7fujhkVIM+natStOnTqFmzdvYtu2bdi/fz+OHTuG48ePy4VRJCUlcRHvL9u4cSN27Nih8RgGDhyIGzduoLi4GA8fPsTXX3+NN998E4cOHcKUKVPw+PFj/PTTT1y9UCiEn59fg6nOwIu/QL6c/gygwQTourq6v0oaGxvjxx9/5BJ1/P39YWNjg9DQULm4MFVQwyKkmdnb2yMyMhKLFy/G0KFDMXv2bLlHvW7duil8N8rQ0LBJ19bV1YW9vT2AF83Ly8sLAwcORGBgIKZMmYJbt27B39+fqxeJRPDz84OJiQmKi4tRVVUl935YQUGBTPpz3bb68vPzubq6e/P19eWaFfDiEXP06NE4evSoRvdHk+6EvCJWVlaYPn06MjIyUFhY2CJj0NLSwltvvYXHjx+jsrISo0aNkkl/rnvfy97eHowxmUdc4MU7V2VlZdxfH+uW06lLe37ZrVu3uLrOnTtDIBAoXK21trZW4XtmqqCGRcgrlJqaCl1dXZXfNG9utbW1uHjxIiwsLCAWixusGzFiBMRiMY4dOyazPTo6GgKBAKNGjQIASCQSODo6ytVdvnwZ6enpGD16NIAXr3MMHDgQBw4ckHlJtLa2FgkJCejTp49G90OPhIRo6NmzZ9z/PW3aNPTs2RM2Njbo2LEjCgsLcezYMcTExGDJkiUafQ1FHTdv3sTSpUsxZcoU9OjRA/r6+sjIyMCOHTtw/fp1bNu2rdHjjYyMMHfuXGzYsAESiQTOzs64cuUKPv30U3h5ecl8DSg0NBSenp4ICAiAr68vsrOzsXDhQnTt2hXe3t5cXVhYGIYNG4Zp06Zh0aJFqKmpwaZNm3D79m2cOHFCo/ukhkWIhuo+TQAv/kK2bt06lJeXc9s6deqEzZs3K32loDkYGxujpqYGs2bNQk1NDbfdxsYGe/bswYwZM5SeY926dSgrK8OiRYtQVVUFoVCIadOmYefOnTJ1EyZMwI4dO7B8+XKuEQ4cOBD79u2T+euhs7MzTp48iQULFmDAgAEAXnxC+/rrr7nkaHUJ8OKrOSq9jaujo4Nnz54p/FLmv1VYWBiePXsmE7tN/lvefPNNREVFcZPZ6enp6NKlC6ytrXH37l2uTiqVIj8/H4WFhZBIJGjXrt0/PtaKigrk5uaioqICxsbGjb4L1pCSkhJkZ2fD3Ny80dchqqurkZGRAUNDw0avwxhDZmYmqqur0blzZ5lJeFVlZ2ejQ4cO9AmLkOYiFAphamoKU1PTFhtD69atYWlp2aRztG3bVuG7Y/Vpa2vDyspKaZ1AIFD4oqkmaNKdEMIb1LAIIbxBDYsQwhvUsAghvEENixDCG9SwCCG8QQ2LEMIb1LAIIbxBDYsQwhvUsAghvEFfzSGkmcTGxuLkyZPIycmBoaEhrKys4OHhwS2lkpqait27d2PGjBmwtbWVO/7u3bvYuXMnfH19uXWnXvaqQ1RVDUdVtS4/Px+7d+9GYmIitLS0YG9vjw8//LBJX12iT1iENANvb294eHjg3LlzkEqlSElJwfr16+Hl5cXVPHz4EOHh4Q1GbqWnpyM8PFzmC9V1XnWIqqrhqKrW3bt3D3Z2dtiyZQtMTU1hbGyMnTt3wtraGlevXlU6nsZQkGojKEiVNBSkam1tzRhj7Pfff2cAWHBwsMxxFRUV7O7du9zvp0+fZgDYDz/8oPA6v/zyCwPATpw4wW37J0JUGVM9HFXVOn9/f6arqyvTWwoKClj79u3ZpEmTlI6nPgpSJaSZpKamAgAmTZoks10sFqu06kFj/okQVVXDUdUJUc3Ly4OlpaXMslVGRkawsrJCbm6uajevADUsQpqoW7duAMBl8jWnfyJEVdVwVHVCVAcPHozU1FT8+uuv3Lbk5GQkJSVh/Pjxat3Hy2jSnRANlZWVYd++ffjggw8waNAghIaG4tGjRwgMDJSbFH/ZjRs3FE6EJyUlKaz/J0JUAeXhqKrWAcCcOXNw5swZuLu7IyAgABKJBGvWrIG3tzeWLFmi0v0oQg2LEA15eXlh+PDh+OyzzxAXF4eQkBDs2bMHERERcHNzQ2hoKFxdXeWOW7Zs2SsZT1NCVAHl4aiq1gEvHocPHjyIgQMH4ssvvwTw4hE1PDwcAoFAzTv7P/RISIiGzMzMYGlpiU8++QS6urrYtm0b0tPT8dlnnyE5ORlubm5YvXq13HG7du3C3bt35X6++eabJo2nLkT1/PnzOHz4MEpLS/Hmm29yCTe1tbXYs2ePzE9OTo7K4aiq1gHA/fv3YW9vD319fZw7dw579+5FZmYmbG1tkZKSovE90icsQjTQ0KcEiUSC0NBQLFiwAJMnT8bq1asxffp0maWEO3TooHAyPi0trUljUhaiWlNTIxOiCgC2trYqh6OqWgcAkydPhpmZGRISEiAWi+Hi4oLJkydj2LBhGDt2LO7du6dRkhB9wiJEA7q6ujIJOfXp6elh0aJFYIzhxo0b/+DI/k/9EFWxWCwTolpTU4PBgwerHI6qal1ubi6SkpLg7e0tk4XYrl07zJkzB+np6bhz545G90QNixANCIVC6OrqNlpT97qDKolUr4KqIaqqhqOqWqejowOhUIgnT57IXatu4t7AwECje6JHQkKaaM2aNXj69Cn69u0LCwsLLt04LCwMTk5O6N+//yu9flNDVAHVw1FVqdPT08OECROwfft2dO/eHe7u7hAKhfj555+xYcMGeHh4oGPHjhrfL73p3gh6050oetNdX1+fbdiwgTHGWEREBDM2NmYAuB89PT0WGBjInj59yh2nyZvuivbXf9P9yZMnbPTo0UwkEsmMwcbGhu3Zs0fl+9yxYwczNDTkjh84cCC7ffu2RnVFRUUsICCAtWnThqtr06YNCwoKYsXFxSqP6eV7BMAoSFUJClIlioJUe/XqhRUrVsh8h66wsBD5+flo27ZtizwGNkeIqqrhqOqEqD558gS1tbWwsLDQ+JUGClIlpJkZGBhoPDfTHJojRFXVcFR1QlSb8vhXH026E0J4gxoWIYQ3qGERQniDGhYhhDeoYRFCeIMaFiGEN6hhEUJ4gxoWIYQ3qGERQniDGhYhhDfoqzmENNGTJ0/w9ddf49q1a2CMoUOHDhg4cCDGjx8PfX19AMDWrVshlUqxYMEChefYvn07qqqqEBgYqHB/dHQ0Ll++jPXr10MolP2cUVpaiujoaPzxxx8oKChAhw4d4OLigmnTpsnVNuT7779HTEwM8vPzYWdnh4CAAJibm8vVJSUlYffu3UhPT0fHjh0xc+ZMODo6Khxrffb29vDx8VFpPA2hT1iENMHVq1dhY2ODtWvX4unTpyguLsZPP/0Eb29vxMbGcnWHDx/GwYMHGzxPVFSUwiWSKysr4e/vDy8vL4SHh8sl59y/fx9du3ZFQEAACgoKYG5ujnv37mH69Onw9PQEY0zpPYSEhGDixIl48uQJOnbsiMOHD+Ott97Cw4cPZepiY2PRt29fJCQkwNzcHImJiRg0aBBiYmJk6r799ltEREQgJiZG5ufSpUtKx6IKWl6mEbS8DGlseZlhw4YxIyMjlp6eLnPM3bt3Zf6tDBgwgPXr16/BawwePJj17t1bZtvDhw+Zg4MD69ixI3v33XcZAFZdXS137NatW1lOTo7MtnXr1jEA7Ndff2303m7dusUAsBUrVnDbCgoKmLm5OfP09OS2VVdXMwsLC+bq6sqNoba2lo0bN46ZmZnJ3KuzszObOnVqo9dVFwWpEqIiOzs7eHh4oHv37ujevTuGDRuGmpoaAC9WFXVwcJBbJcHa2rrJyzBdunQJAoEAly9fbnRlhHnz5sHU1FRmW93qn8pCVI8cOQKRSIRFixZx24yMjDBr1izExsZy67fHx8fj8ePHCAoK4tZiFwqFWLx4MbKzs/Hzzz9zx+fl5cHY2Fi9m1URzWERosTevXtllvvNzMxESEgIgBchqnWBpXXzVc3Fy8sLU6ZMgZaWltohqr/99hsAyKVB15eYmAgbGxu5ZXEGDRqE2tpaXLlyBWPGjEFiYiIAyIWoOjk5QSgU4sKFC1wyNTUsQlqQrq6uTMqNtrY2UlJSUF1djWXLlsHDwwOOjo5YtWoVJk+ejFatWik8T3FxcYPp0EVFRQoDU1UNUX369CkKCgqQk5OD06dPIzw8HEuWLFG6PHNmZmaDwajA/yX5ZGZmonXr1mjfvr1MnVgshomJCVdXW1uLZ8+eIT4+HtOnT0dlZSW6du2KiRMnYtCgQSrdS2OoYRGiAQMDA5SWlsLd3R1xcXFYuHAh3n33XZiYmGD27NkIDg5Gu3btZI65c+eOwmDVOsoi5Rvz1VdfYe3atQAAkUiEwMBALF26VOlxJSUlDQaj1u1vrK6utq6utrYWY8eORVVVFUQiESoqKvC///0PGzZswEcffYQdO3ZodH91qGERogGBQIA1a9YAAIYPH47r168jLi4OW7ZswZo1a3Dw4EGcO3dOZm7L3t4eJ06cUHi+qVOncvNimpg/fz68vLzw7Nkz3LhxA1u2bMGhQ4fw+++/o0ePHrhy5QqSkpK4enNzc4wdOxba2toNBqMCkAlRVVRXV1tX16pVK/z4448y+6urqzFjxgxERERg0qRJGDFihMb3SQ2LkGYgEAgwevRojB49Gj/++CM8PT2xYsUKmVcVxGKxwgBV4MXyxi9HvavL1NSUm3gfMmQI3nnnHXTq1AmfffYZDh48iJiYGISFhXH1w4cPx9ixY2FiYtJgMCoAmRDV4uJiVFVVyT3yFhQUNLquu7a2NlatWoWDBw8iPj6+SQ2L/kpISDMbN24cHBwcZD7R/NNMTEzQuXNn7q+Ea9eulQlQrfurnr29PVJSUuTe16oLS62btLe3twdjDLdv35apS0tLQ1lZmdLJfT09PQBQ6b2wxlDDIqSZVVRUICMjo8UCVIEXk+QPHz5UGhQxfvx4PH36lPurYp3o6GhYWlrC1tYWADBixAiIxWK5ENXo6GgIBAKMGjWq0evUPSbWfyteXfRISIiGcnNz4ePjg1GjRqFbt25o3749Hj9+jG3btiE7Oxu7d+9+5WPYt28fEhIS4O7uji5dukAoFOLWrVv4/PPPIRQKsXDhwkaPHzt2LBwcHODn54fNmzfD0tISUVFROH36NCIjI7mv9hgZGWHu3LnYsGEDJBIJnJ2dceXKFXz66afw8vJC9+7dAQDHjx9HfHw8XF1dYWlpiYqKCpw9exbr16+Hk5MTPDw8mnzP9KZ7I+hNd1JfWloa69y5MysqKmL9+/dnWlpaXFioQCBgjo6O7PTp0zLHaPKm+8uWL1+u8E33+Ph49tZbb8kEqGppaTEXFxeWkJCg0v08evSIDR8+nDteV1eXrV27Vq6usrKS+fv7s1atWr1461woZN7e3qykpISruXTpErOxsZEZj66uLvvwww9ZYWGhSuNRhIJUVURBqqS+9PR0DB06lHv3qKqqCnl5eSgvL4eFhUWL/Pt4/vw58vLyIBAIIJFIoKurq/Y58vPzUVxcjE6dOnFvsytSUlKC7OxsmJubN/iqQ2lpKXJyciAQCJSeTxUUpEpIM2nVqpXClQ3+Sfr6+k1+097Y2FilN9Tbtm3b4F876+jq6qJbt25NGo8iNOlOCOENaliEEN6ghkUI4Q1qWIQQ3qCGRQjhDWpYhBDeoIZFCOENaliEEN6ghkUI4Q1qWIQQ3qCv5hDSDGJjY3Hy5Enk5OTA0NAQVlZW8PDwQJ8+fQC8WJVz6dKlGDZsGMaPHy93vFQqxZIlSzBkyBBMmDBBbn9ubi42bdqEIUOGYMyYMXL7ExMTcfz4caSmpkJLSwvW1taYNWsWunTpotL4KysrsWvXLvz555+oqqqCs7Mz5syZI/e9SFXrkpOTcejQIaSmpkJfXx/9+/fHjBkzIBaLVRpPQ+gTFiFN5O3tDQ8PD5w7dw5SqRQpKSlYv349vLy8uJqamhqEh4c3GEIhlUoRHh6OX3/9VW7f+fPn0bdvX6xbtw4JCQly+xctWoR+/frh+++/h4GBAdq0aYO9e/fCxsYGf/75p9LxV1VVYeTIkQgJCYFQKISuri5WrlyJ4cOHo6qqSu26jz/+GH369MGpU6dgaGiIwsJCLFiwAH379kVRUZHS8ShDy8s0gpaXIfXVLS/DGGO///47A8CCg4NlaioqKtjdu3e538vLyxkAFhQUpPCc1dXVDABbsGCBzPaNGzcybW1tNnfuXNa6dWu2fPlyuWOvXLnCvv/+e5ltBQUFrEOHDmzIkCFK7yciIoIBYGfPnuW2XbhwgQmFQrZx40a16/bt28cOHTokc40ffviBAWDr1q1TOh5FKEiVkGaQmpoKAJg0aZLM9sbWb1dVZWUljhw5go0bN2LLli2oqKhQWOfg4CD3GGlkZARHR0elQaoAcPjwYTg4OMDNzY3b5uTkhCFDhsisSa9qnY+PD7y9vWWuMW7cOOjo6CAlJUXpeBpDDYuQJqhbQqWhR72mEIvFuHDhAubOnat2kGpxcTH++usvpdFhjDH8/fffcgGpwIsw1aSkJJSVlalc15CysjJUVlZCIpGodR/10aQ7IRqQSqW4d+8e3NzcMGjQIISGhuLRo0cIDAzklgtW5NGjRwqbW0MRWqoGqQLAvXv3UF5ejtTUVISFhUEkEiE8PLzRY4qKilBaWtpgmCpjjFufXpU6GxsbhdfZv38/pFIp3n77bZXvRxFqWIRoID8/H9u3b4eBgQHi4uIQEhKCPXv2ICIiAm5ubggNDVUYmhodHY3o6OhmH09NTY1Mo7S3t8eePXsabCB16qLFlIWpqlqnSEpKCj7++GP4+PhQCAUhLaG6uhpz587l5qm2bduGFStWYPfu3di2bRvc3NywatUqfPLJJzLHzZgxQ2Eic21trdLm0hiRSIQbN26gsrISWVlZOHnyJEaNGoXAwECEh4ejtrYW+/btkznGw8MD2tra3PXrezlMVdW6+h49eoTRo0fDzs4O27dv1/j+6lDDIqSZSCQShIaGYsGCBZg8eTJWr16N6dOny0RtGRgYKJyMb0rqcx17e3sAQL9+/eDh4QF9fX189dVX+Oijj9CpUyf4+/vL1Nva2qJ///7Q0tJSGqZqZGSkUt3Lnjx5guHDh8PU1BSnTp3iPok1BU26E9LM9PT0sGjRIjDGcOPGjRYbh4ODAwDgwYMHEIvFMkGqNTU1GDx4MLS1tdGjRw8uOPVlt27dgrGxMTp06KByXZ3s7Gy4urrC0NAQZ86cgaGhYbPcEzUsQl6ButcdWjJMte4lU2VhEOPHj8eZM2dkXuosLS3Fjz/+iNGjR6tdl5OTwzWruLg4GBgYNNct0SMhIU2xZs0aPH36FH379oWFhQVqa2uRkJCAsLAwODk5oX///q98DCNGjMC4cePQu3dvSCQS5OfnIyYmBpGRkZgyZYrS98Hmz5+PnTt3YtKkSVi1ahW0tLSwdu1aFBcXY/HixWrVlZSUwM3NDWlpaVi9ejWioqLkrjd16lSNmxg1LEKawNjYGJs3b8bGjRu5bXp6evD398eKFSu45ORXqVu3bli1ahWeP3/ObTM1NcXixYvlJv0VsbCwQGxsLPz8/DBkyBAAgKWlJY4dOybzHpcqddnZ2dxjY0hIiMLrDRs2TOOGRUGqSlCQKqkvPT0d1tbWSElJ4T69FBYWIj8/H23btm2Rx8Camhrk5eXh+fPn0NfXh5mZGQQCgVrnYIzh8ePHEAqF6NixY4PHq1rXnChIlZBmZGBg0KxzNeoSiUTo0KGDzMS3uupSmpur7lWgSXdCCG9QwyKE8AY1LEIIb1DDIoTwBjUsQjRQU1ODw4cPt/Qw/nOoYRGioalTp7b0EP5zqGERQniDGhYhhDeoYRFCeIMaFiGEN6hhEUJ4g75LSEgTXbt2DYcOHcL9+/eho6MDCwsLjBw5Eq6urhCJRP+51Of6tm/fjitXrmD9+vUwNTVVaUwNoU9YhDTBzp070a9fPxw6dAiVlZV4/PgxDhw4gDFjxiA7OxvAfyv1ub74+HjMnz8f33zzjczyN01Byc+NoORnUl9aWhoDwP7++2+mq6vLnJ2dZf5dSKVSlpyczP3+X0p9fllhYSGztLRko0aNYgBkkrDVRcnPhDRRTk4OSktL4e7uLvNYJBAI0LNnzyadm6+pzy+bN28e9PX18cEHHygdh6qoYRGiITMzM4hEIsTHxzf7ufme+nz06FEcPXoUhw8fbtZVV2nSnRANmZmZITg4GF988QVGjhyJlStXwsXFpcH6/0rqc2ZmJvz9/bF27Vr06tVLYdKOpqhhEaKhyMhIrFu3Dh07dsSaNWswZMgQ2NraIigoCL6+vnKfLP4Lqc+MMfj6+qJPnz5YtGiRBnfTOGpYhGho+fLlAICAgADMmjULUVFR2LRpE2bOnIno6GjExsZyiclAy6U+A8DJkyeRm5vLHePg4MAtp9ycqc9btmzB1atXcf369Vey1js1LEKaQevWreHr6wsfHx+Ehobi888/x6FDh+Dr68vVtFTqs7W1NdavX4+LFy9y9Z9++ikWL17crKnPqampWLp0Kfz9/ZGWloa0tDQA/5fR+NdffyE3NxeDBg3S+D6pYRHSjAQCAdewkpKSWmwcL6c+W1tbK3yHC4DKac6q1J09exYVFRXYtGkTNm3aJFc7depUiMXiBv/iqQpqWIQ0szt37gDgT+pzZGQkioqK0K5dOwANpz4rq5swYQJSUlLkrnHq1CkEBQXh559/Vvnt+4ZQwyJETSKRCAKBAD/++CO+++47ODs7o3PnztDR0UFycjK++OILGBoa4r333nvlY3mdUp/19fWhr68vd41r164BeNE8lY1HGWpYhKjJ3NwcWlpaiI2Nxfnz53HgwAFun0gkwoQJE7BmzRqYm5u/8rG8TqnP/wRKflaCkp+JItra2igvL4dIJEJpaSny8vIgEAhgYWGh1vtTzeHfnvoMUPIzIc1GV1cXurq6LXb9/0rqM0BfzSGE8Ag1LEIIb1DDIoTwBjUsQghvUMMihPAGNSxCCG9QwyKE8AY1LEIIb1DDIoTwBjUsQghv0FdzCGmi2NhYnDx5Ejk5OTA0NISVlRU8PDzQp08fAPjPBKlmZGRgy5YtjV5r/vz5sLS0VGlcDaFcwkZQLiFRRCQSserqavbuu+8yAOyNN95g48ePZ/3792dt27ZlPXr04Go1zSVkjLE///yTmZubMwAKcwkDAwMZAGZnZ8dmzJjBfHx8mEQiYWKxmCUkJCi9j8rKSubi4sJ0dHTYtGnT2PTp05muri4bNGgQq6ysVKvu77//ZlZWVgp/jIyMuCxHTdTlElLDUoIaFlFEJBKxs2fPMgAsODhYZl9FRYVMaOh/NUj1ZUOHDmV2dnZK6xpCQaqENFHdyqKTJk2S2S4Wi5u8UN2/IUi1zpUrVxAfH98sKTrUsAjRUNeuXQFAYdZgU/E9SPVlYWFhkEgk8Pb2Vus+FKFJd0I0YGNjAzc3NwwaNAihoaF49OgRAgMDZfIB6/uvBKnWH9eJEyewevVqiMVile+nIdSwCNHApUuX8PnnnyMuLg4hISHYs2cPIiIi4ObmhtDQULi6usod818IUq1vw4YNEIvF+Oijj1S4E+WoYRGigTZt2nBrpm/btg0rVqzA7t27sW3bNri5uWHVqlVya6q3VJBqbW0t9u3bJ3OMh4eHygGp6gSpviw3NxcHDhyAr68v2rdvr/H9vYwaFiHNQCKRIDQ0FAsWLMDkyZOxevVqTJ8+HVZWVlxNSwWpdurUCf7+/jL1tra26N+/f7MGqda3efNmVFZWYuHChU2+vzo06U5IM9LT08OiRYvAGMONGzdabBwvB6mKxWLU1NTI/AwePBja2toqBaSqWveykpISREREwMPDAz169Gi2+6KGRUgzq4tm50uQ6pkzZ1BUVMRtayhIVZW6Ort378azZ88QFBTU1FuRQY+EhGhozZo1ePr0Kfr27QsLCwvU1tYiISEBYWFhcHJyQv/+/V/5GF6nINU6NTU12LRpExwcHLgMw+ZCDYsQDRkbG2Pz5s3YuHEjt01PTw/+/v5YsWIFhMJX/wDzOgapRkVFISMj45VkeVKQqhIUpEqUKSwsRH5+Ptq2bdsij4EUpEoIUZmBgQEMDAxa7PoUpEoIIa8haliEEN6ghkUI4Q1qWIQQ3qCGRQjhDWpYhBDeoIZFCOENaliEEN6ghkUI4Q1qWIQQ3qCGxWMVFRXYtWsXpk+fjokTJ2L27NnYunUrHj16xNWkpqYiODgYKSkpCs9x9+5dBAcHIzk5WeH+v/76C8HBwbh7967C/cnJyfj4448xadIk+Pj4YMeOHaisrFT5HnJychAaGor/9//+H7y9vXHs2LFG66OjoxEcHKxSMENmZiZ8fX2xa9culcdDXn+US9iI1zWX8OnTp8ze3p4JBAI2YMAA5u7uznr16sW0tLTYrFmzuLrTp08zAOyHH35QeJ5ffvmFAWAnTpyQ27dz504mFosZAPbLL7/I7V+6dCkTiUSsV69ezM/Pj3l6ejKRSMR69uzJCgsLld7Dw4cPmampKTMzM2MzZ85k48aNYwKBQGF+X0VFBZs9e3ZdmCarrq5u9NxSqZSNGDGCAWDe3t5Kx0Jeb3W5hPTlZ57asmULbt68idjYWIwbN47bXlBQgOrq6iadu6ysDB999BG+/fZb+Pv7Nxg//sYbb2D//v0y8U2xsbHw8PBARESEwvXLX7Z06VJIpVJcv34dEk7LmhMAABIkSURBVIkEALB+/XqEhITA29sbb731FgAgLS0Nb7/9NrKysvDuu+/iyJEjSu9h8+bNSE5O5pYOJv8O9EjIU6mpqRCLxXB3d5fZ3r59+yYvcZKVlYXz58/j7Nmz8PT0bLDOx8dHLmtu3Lhx0NHRafARtE55eTm+++47+Pj4cM0KAAICAtCmTRscOHCA23bp0iUIBAJcvnxZZo30htQ9pn711VdgjCmtJ/xBDYununXrhsrKSly8eLHZz21tbY3bt2/D2dlZ7RDPsrIyVFZWyjQhRW7evInq6mq5cE4dHR306dMHFy5c4LZ5eXnhwoULMDc3Vzqeqqoqbk5v6tSpzRLwQF4f9Eiogps3b2Lv3r0tPQyOq6sr5syZg4iICIwdOxbLli3DzJkzFSaX1Llx4wbatm0rtz0pKUlhvTohni/bv38/pFIp3n777UbrMjMzAaDBcM76gaOqjmfFihUoKChARESEagMmvEINS4k5c+bgzp07Mv+L39IuXbqEXbt24erVq5g7dy5CQkKwcuVKeHl5YcWKFQrX8V62bNkrH1dKSgo+/vhj+Pj4wNHRsdFaZeGcDQVzNubcuXP46quvEBcX16IL6pFXhxqWEnp6eq/Vp6uXde3aFadOncLNmzexbds27N+/H8eOHcPx48cxZswYmdpdu3YpTCM+f/48PvjggyaP5dGjRxg9ejTs7Oywfft2bvvjx4/x008/cb8LhUL4+fkpDedU1Mga8/z5c7z//vtYuHChwvsk/w7UsP4F7O3tERkZicWLF2Po0KGYPXs20tPTZWo6dOig8JNXWlpak6//5MkTDB8+HKampjh16hQXXw68yK17OcRTJBLBz88PJiYmANBgOGdjj7eKLFy4EGVlZRg7diwXcQW8mNzPy8tDQkICunTpovARlPAHTbr/i1hZWWH69OnIyMhAYWHhP3LN7OxsuLq6wtDQEGfOnIGhoaHM/lGjRskEeFZUVAAA7OzsAKDBcM5evXqpNY5z584hLy8Pw4cPh4uLC/eTkZGBuLg4uLi44NChQxreJXld0Cesf5nU1FTo6uoqnGBvbjk5OVyz+umnn9CuXTuVj5VIJHB0dMSxY8cwf/58bvvly5eRnp6O0NBQtcYSFxeHqqoque3u7u6wt7fH+vXrYWpqqtY5yeuHGhZPTZs2DT179oSNjQ06duyIwsJCHDt2DDExMViyZAlEolf7/9qSkhK4ubkhLS0Nq1evRlRUlFzN1KlTG538Dg0NhaenJwICAuDr64vs7GwsXLgQXbt2lXu/S5mGEo5btWoFfX192NjYqHU+8nqihsVTbdq0wbp161BeXs5t69SpEzZv3ox58+a98utnZ2dzj3MhISEKa4YNG9Zow5owYQJ27NiB5cuXY9u2bQCAgQMHYt++fWpPupP/BgpS5TGpVIr8/HwUFhZCIpGo9Uj2OqmurkZGRgYMDQ3Vnmwn/w0UpPovIBQKYWpqyvu5GW1tbZW+ckMI/ZWQEMIb1LAIIbxBDYsQwhvUsAghvEENixDCG9SwCCG8QQ2LEMIb1LAIIbxBDYsQwhvUsAghvEENixDCG7z6LuG1a9dw6NAh3L9/Hzo6OrCwsMDIkSPh6urKLaeydetWSKVSLFiwQOE5tm/fjqqqKgQGBsrtq6mpwaZNm6Cjo4O5c+fK7a+ursbhw4fx22+/obi4GF27dsX777+P3r17q3wP33//PWJiYpCfnw87OzsEBATA3NxcYW1ubi42bdqEIUOGyC15DACJiYk4fvw4UlNToaWlBWtra8yaNQtdunRReTyE8A0vkp8jIyOZUChkEomEjR07lrm4uDCJRMKEQiF79OgRVzdgwADWr1+/Bs8zePBg1rt3b7ntmZmZbPDgwQwAGzx4sNz+69evM1tbW6arq8smTpzI/Pz8WPfu3ZlQKGSRkZEq3cOSJUsYADZ69Gj24YcfMgsLC2ZiYsIePHggV/vnn38yc3NzBoAtX75cbn9gYCADwOzs7NiMGTOYj48Pk0gkTCwWs4SEBJXGQwhf1CU/86JhlZSUMF1dXebs7CxzfalUypKTk2VqNWlYZ8+eZaampmzw4MHMyclJYcMqLCxkAQEBLCsri9tWVVXFnJycmL6+PqusrGz0Hm7dusUAsBUrVnDbCgoKmLm5OfP09JSp3bhxI9PW1mZz585lrVu3Vtiwrly5wr7//nuZbQUFBaxDhw5syJAhjY6FEL6pa1i8mMPKzMxEaWkp3N3dZdbiEggE6NmzZ5PPf+zYMbi7u+Ps2bNcmkt97dq1w5YtW9ChQwdum7a2Njw9PfH8+XMuZ68hR44cgUgkwqJFi7htRkZGmDVrFmJjY7kwhsrKShw5cgQbN27Eli1buDXQ63NwcMCECRNkthkZGcHR0RH3799X6b4J4Ru157AyMjIgFotfxVgU0tbWRqdOnSASiRAfH4+PP/642a+xdetWLqhT3aTjZ8+eQUtLC8bGxo3WJSYmwsbGRm4FzkGDBqG2thZXrlzBmDFjIBaLceHCBWhpaamdWlxcXIy//vpLrTk1QvhErYY1depUjBo16lWNRaEuXbrA1dUVwcHB+OKLLzBy5EisXLkSLi4uDR5TXFwslxxcp6ioSC5FWNOU44qKCkRFRWHMmDHQ09NrtDYzM7PBlGNANm5LnfHcu3cP5eXlSE1NRVhYGEQiEcLDw1U+nhA+Uath7du371WNQyUdO3bEmjVrMGTIENja2iIoKAi+vr4QCmWfbO/cudNomGZzfQKZN28eCgoKsGHDBqW1JSUlDaYc1+1XV01NDbp37879bm9vjz179lDgAvnX4tVrDQEBAZg1axaioqKwadMmzJw5E9HR0YiNjZWZe7K3t8eJEycUnmPq1KlqP2opsmrVKuzbtw/ffvstbG1tue0nT55Ebm4u97uDgwP69OkDbW3tBlOOAcWR7cqIRCLcuHEDlZWVyMrKwsmTJzFq1CgEBgbSpyzyr6XyXwlfJ1KplC1btowBYF9//TW3XdPXGl7er+ivhC/bsGEDEwqFbP/+/QqP19LS4n7Wrl3LGGPMxcVF4XkvXbrEALAjR47I7auurm7wtYaGLFq0iAFgd+/eVfkYQl53vPoroSICgYAL20xKSvrHrrtx40YsXboU+/fvxwcffCC3PyEhQSbpeNmyZQBefOpLSUkBY0ymvi4qS92k44Y4ODgAAB48eNAs5yPkdcLbhgW8mKsCoFJEWXPYvHkzFi9ejAMHDuC9995T69jx48fj6dOn+O2332S2R0dHw9LSUuaxsikSEhIANBwsSgif8WIOKzY2FkePHoWzszM6d+4MHR0dJCcn44svvoChoaHazUMTX3/9NRYuXIhRo0bh+fPniIyMlNlvbW2NESNGNHj82LFj4eDgAD8/P2zevBmWlpaIiorC6dOnERkZKfeHA2VGjBiBcePGoXfv3pBIJMjPz0dMTAwiIyMxZcoUWFtba3SfhLzOeNGwjI2Ncf78eRw4cIDbJhKJMGHCBKxZs6bB7+I1p19//RUAEBcXh7i4OLn9Xl5ejTYsgUCAEydOwMfHBxMnTgQA6OrqYu3atZg9e7ba4+nWrRtWrVqF58+fc9tMTU2xePFifPLJJ2qfjxA+UCv5uaWVlpYiLy8PAoEAFhYWGr8/1dLy8/NRXFzMvRCrqZqaGuTl5eH58+fQ19eHmZkZBAJBM46UkNdDXfIzrxoWIeS/qa5h8XrSnRDy30INixDCG9SwCCG8QQ2LEMIb1LAIIbxBDYsQwhvUsAghvEENixDCG9SwCCG8QQ2LEMIb1LAIIbxBDYsQwhvUsAghvKFyw2KMISQkRKN0l9ddeXk5QkJCmiWcghDy6qi8vIxUKoWWlhZycnJgamr6z4zuH1JYWAhDQ0OUl5fLJEsTQl4PtLwMIYR3qGERQniDGhYhhDfUXlC8rKwMpaWlr2IsLaasrKylh0AIUYHKDUsqlQIAunbt+soG09IqKipo0p2Q15jKDasuN+/evXswMTF5ZQNqCUVFRbC0tKRmRchrTu1HQj09Pejr67+KsbSYuk+PhJDXG026E0J4gxoWIYQ3qGERQnhD5YYlEAgQFBSENm3avMrxtAixWIygoKAmxcYTQl49iqonhLz26LuEhBDeoYZFCOENjSZtsrKyEBUVhaKiIrz11lvw9PTkXixVpzY/Px/Hjx9HRkYGzMzM8M4770AikSg99tatWzh37pzctXR0dPDBBx+oPUZlampq8O233yI5ORndu3fHe++9B21tbZmaK1eu4Ndff0VhYSEmTpyIAQMGaHQtQkjD1P4XfOvWLTg4OCAnJwdmZmYICwvDtGnT1K7NysrCm2++iYSEBOjq6uLixYuwtbVFenq60mOzs7ORkJAg87Nv3z589tlnao9RFVOnTsWGDRvQqlUrREREYPLkyTL758+fj3feeQcVFRXo1KkTqqurNb4WIaRx7MmTJ0xVK1euZG+//Tb3+4MHD5hAIGBlZWVq1xYWFsrUDx06lH355ZdqX4cxxkaOHMnCwsLUOjYrK4vdu3ePSaXSBu83MTGRtWnThuXn5zPGGCsqKmKGhobsjz/+YIwxdvz4cWZpacmePXvW4DkIIU3z5MkTBoCp/QnLysoK169f51ZsuH79Orp16wYdHR21a9u1a8fV1tbWoqCggPueojrXuXbtGi5evIgPP/xQpWNLSkrg6emJgQMHwtPTE/b29rh//77C+z137hxcXFzQvn17AIC+vj5cXV0RFxcHANi7dy/mzZsHAwMDdf4zEkI0oPYclre3Ny5cuIB+/frBzc0N8fHxOHHihMa1//vf/5Cfn48ffvgBjo6OePfdd9W+TlhYGPz8/LimoezY5cuXQ1tbG/fv34eWlhaCgoIwd+5c/PTTT3LnzszMhLm5ucw2c3Nz7tE1KSkJkydPxpgxY/DgwQP07t0b69ev/1evakFIS9FoFrpt27bQ0tJCamoqpFJpo+tJKav95ZdfEBcXh6ysLDDGUFhYqNZ1Hj58iO+++w4LFixQ+bpHjx6Fo6MjLly4gISEBFhZWeG3334DYwylpaUoKSlBSUkJpFIpamtr5T7V6ejooKqqCgCQl5eH3bt3Y+PGjbh48SLMzc3h6ekJxpjq/0EJISpTaw4rNDSUjRo1ilVUVDDGGIuJiWFGRkbswYMHTaqtra1lHh4ezNfXV61j58yZIzNfpcqxQqGQDR06lHl6esr8VFVVsXbt2jEtLS2mpaXFEhIS2Lp165i3t7fM+T/88EM2e/ZsxhhjYrGYnTlzhttXUlLCBAIBy8jIUPG/KCFEmbo5LLUbloODA/v2229ltjk6OrIDBw40qZYxxsLCwtjAgQNVPjY3N5fp6OiwixcvqnVdMzMzdvTo0cZukxMTE8PefPNNmW1OTk5s69atjDHGevbsyY4fP87tKykpYQBYZmamSucnhCin8aR7z549ERsbi9raWgBASkoKbt++jV69egEANmzYgKtXryqtvXPnjsxEd1ZWFg4ePIihQ4eqdB0A2Lp1K/r27Sv3zpOyY6dNm4bPP/8cOTk5AF68Z3X79m2F9ztmzBhkZWXh5MmTAIAzZ84gKSkJkyZNAgD4+Pjg008/RXFxMQBg8+bN6NmzJzp27Kjuf1pCiArU+oT15MkT5ubmxkxMTFjPnj2ZiYkJ2759O2PsxWOdnp4eW7JkidLauLg4ZmpqyoyMjJilpSXT09Njfn5+rLy8XOmxjL34JGNkZMS+++47tcbIGGNlZWXMx8eHtW7dmllYWDBdXV02f/78Bu/5hx9+YEZGRqx9+/asXbt2LCoqittXXV3N5syZwwwMDJiZmRmztbVl165dU/m/JyFEubpPWBp/+bm0tBRFRUUwMzOTeYM8Ly8PhoaGMisfNFQrlUqRn5+PyspKSCQStGrVSuXrNGWMdcrKypCfnw9jY2Olq1BUV1dzL6IqWtWhpKQE5eXl/7rlowl5HdR9+ZlWayCEvPZotQZCCO9QwyKE8AY1LEIIb1DDIoTwBjUsQghvUMMihPAGNSxCCG9QwyKE8AY1LEIIb1DDIoTwBjUsQghvUMMihPAGNSxCCG9QwyKE8AY1LEIIb1DDIoTwBjUsQghvUMMihPAGNSxCCG9QwyKE8AY1LEIIb1DDIoTwBjUsQghvUMMihPAGNSxCCG9QwyKE8AY1LEIIb4gA4KOPPoJEImnpsRBCiEI5OTkAgP8PvXj7P9w1Rj4AAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "t.tree_styler(show_legend_type_labels=False).highlight(tdist).render(w=300)" ] }, { "cell_type": "markdown", "id": "41076d4d-1069-46a2-b9f3-17511466260d", "metadata": {}, "source": [ "### 4.5.2. Select by most recent common ancestor\n", "\n", "Another type of query instead of distance is `mrca` which selects samples that all share a particular most recent common ancestor." ] }, { "cell_type": "code", "execution_count": 36, "id": "23bb9f39-735f-47fa-b511-2732eb844555", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tmrca = t.isin(['SH14-002', 'SH14-025'], kind='mrca')\n", "t.tree_styler(show_legend_type_labels=False).highlight(tmrca).render(w=300)" ] }, { "cell_type": "markdown", "id": "16486ed2-6701-47df-8451-8045909468a7", "metadata": {}, "source": [ "### 4.5.3. Select by distance and mrca\n", "\n", "If you wish to select by distance, but restrict yourself to some particular clade you can chain the above two queries together." ] }, { "cell_type": "code", "execution_count": 37, "id": "05a4d717-75ea-48a9-80f7-e1672d2c3987", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "execution_count": 37, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tmrca_and_dist = t.isin(['SH14-002', 'SH14-025'], kind='mrca')\\\n", " .isin('SH14-002', kind='distance', distance=1e-7, units='substitutions/site')\n", "\n", "t.tree_styler(show_legend_type_labels=False).highlight(tmrca_and_dist).render(w=300)" ] }, { "cell_type": "markdown", "id": "9e6caceb-baca-4f12-84a1-c40ef91fb6e8", "metadata": {}, "source": [ "## 4.6 Attach external metadata\n", "\n", "So far we've been looking at only the genomics data. But often times many details insights can be derived from the associated metadata with the genomic samples. External metadata can be attached and tracked by our queries. This also gives us annother method for selecting samples using pandas selection statements (e.g., `metadata['Column'] == 'value'`).\n", "\n", "To attach external metadata we first must load it up in Python as a DataFrame (note `head(3)` just means only print the first 3 rows, which avoids printing a very large table for this tutorial)." ] }, { "cell_type": "code", "execution_count": 38, "id": "a30f2d3f-76a0-44bb-b7d1-6d16d08ed262", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Sample Name OrigRunAssay TypeAvgSpotLenBasesBioProjectBioSampleBioSampleModelBytesCenter Name...PFGE_SecondaryEnzyme_patternPhagetypePlatformReleaseDateSerovarSRA StudySTRAINsub_speciesHost_diseaseHost
0SH08-001SRR3028792WGS429354123684PRJNA305824SAMN04334683Pathogen.cl197484364MCGILL UNIVERSITY...SHBNI.000119ILLUMINA2015-12-19T00:00:00ZHeidelbergSRP067504SH08-001entericaSalmonella gastroenteritisHomo sapiens
1SH09-29SRR3028793WGS422519366460PRJNA305824SAMN04334684Pathogen.cl288691068MCGILL UNIVERSITY...SHBNI.000126ILLUMINA2015-12-19T00:00:00ZHeidelbergSRP067504SH09-29entericaSalmonella gastroenteritisHomo sapiens
2SH10-001SRR3028783WGS421387145160PRJNA305824SAMN04334674Pathogen.cl233911529MCGILL UNIVERSITY...SHBNI.000119ILLUMINA2015-12-19T00:00:00ZHeidelbergSRP067504SH10-001entericaSalmonella gastroenteritisHomo sapiens
\n", "

3 rows × 40 columns

\n", "
" ], "text/plain": [ " Sample Name Orig Run Assay Type AvgSpotLen Bases BioProject \\\n", "0 SH08-001 SRR3028792 WGS 429 354123684 PRJNA305824 \n", "1 SH09-29 SRR3028793 WGS 422 519366460 PRJNA305824 \n", "2 SH10-001 SRR3028783 WGS 421 387145160 PRJNA305824 \n", "\n", " BioSample BioSampleModel Bytes Center Name ... \\\n", "0 SAMN04334683 Pathogen.cl 197484364 MCGILL UNIVERSITY ... \n", "1 SAMN04334684 Pathogen.cl 288691068 MCGILL UNIVERSITY ... \n", "2 SAMN04334674 Pathogen.cl 233911529 MCGILL UNIVERSITY ... \n", "\n", " PFGE_SecondaryEnzyme_pattern Phagetype Platform ReleaseDate \\\n", "0 SHBNI.0001 19 ILLUMINA 2015-12-19T00:00:00Z \n", "1 SHBNI.0001 26 ILLUMINA 2015-12-19T00:00:00Z \n", "2 SHBNI.0001 19 ILLUMINA 2015-12-19T00:00:00Z \n", "\n", " Serovar SRA Study STRAIN sub_species Host_disease \\\n", "0 Heidelberg SRP067504 SH08-001 enterica Salmonella gastroenteritis \n", "1 Heidelberg SRP067504 SH09-29 enterica Salmonella gastroenteritis \n", "2 Heidelberg SRP067504 SH10-001 enterica Salmonella gastroenteritis \n", "\n", " Host \n", "0 Homo sapiens \n", "1 Homo sapiens \n", "2 Homo sapiens \n", "\n", "[3 rows x 40 columns]" ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import pandas as pd\n", "\n", "# I rename 'Sample Name' here to 'Sample Name Orig' to avoid issues later on with other columns named 'Sample Name'\n", "metadata_df = pd.read_csv('salmonella-project/metadata.tsv.gz', sep='\\t', dtype=str).rename(\n", " {'Sample Name': 'Sample Name Orig'}, axis='columns')\n", "metadata_df.head(3)" ] }, { "cell_type": "markdown", "id": "30181c03-3541-4abf-8cc1-3410369a7a65", "metadata": {}, "source": [ "Now we can attach to our query using the `join()` method:" ] }, { "cell_type": "code", "execution_count": 39, "id": "e1910c1f-1b53-4976-9832-133864ca6c77", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 39, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Setup a new query (you don't have to do this, but this makes sure the results are all as expected in the tutorial)\n", "q = db.samples_query().hasa('hgvs_gn:NC_011083.1:siiE:p.R1263S')\n", "\n", "# Join our query with the given data frame\n", "q = q.join(metadata_df, sample_names_column='Sample Name Orig')\n", "q" ] }, { "cell_type": "markdown", "id": "79dc9bfd-facb-43ca-bd9f-33a456395571", "metadata": {}, "source": [ "To join we had to define a column containing the sample names. We now get back a query of type `DataFrameSamplesQuery`." ] }, { "cell_type": "markdown", "id": "909c7750-5866-470d-a40c-5e2e984d6074", "metadata": {}, "source": [ "## 4.7 Query external metadata\n", "\n", "We can continue using this to select samples and when we're done use the `toframe()` method to dump out our selected data as a DataFrame (change to `toframe(include_unknown=True)` if you wish to include unknown results)." ] }, { "cell_type": "code", "execution_count": 40, "id": "b6cd0b7d-f219-45fe-864c-4540acb38c4f", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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QuerySample NameSample IDStatusSample Name OrigRunAssay TypeAvgSpotLenBasesBioProject...PFGE_SecondaryEnzyme_patternPhagetypePlatformReleaseDateSerovarSRA StudySTRAINsub_speciesHost_diseaseHost
0hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram...SH10-3016PresentSH10-30SRR3028794WGS408614636422PRJNA305824...SHBNI.000129ILLUMINA2015-12-19T00:00:00ZHeidelbergSRP067504SH10-30entericaSalmonella gastroenteritisHomo sapiens
1hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram...SH14-00230PresentSH14-002SRR3028755WGS513687874904PRJNA305824...SHBNI.000119ILLUMINA2015-12-19T00:00:00ZHeidelbergSRP067504SH14-002entericaSalmonella gastroenteritisHomo sapiens
2hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram...SH14-00320PresentSH14-003SRR3028756WGS508697302985PRJNA305824...SHBNI.000119ILLUMINA2015-12-19T00:00:00ZHeidelbergSRP067504SH14-003entericaSalmonella gastroenteritisHomo sapiens
3hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram...SH14-00452PresentSH14-004SRR3028757WGS505808762405PRJNA305824...SHBNI.000119ILLUMINA2015-12-19T00:00:00ZHeidelbergSRP067504SH14-004entericaSalmonella gastroenteritisHomo sapiens
4hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram...SH14-00511PresentSH14-005SRR3028758WGS510852322915PRJNA305824...SHBNI.000119ILLUMINA2015-12-19T00:00:00ZHeidelbergSRP067504SH14-005entericaSalmonella gastroenteritisHomo sapiens
5hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram...SH14-00624PresentSH14-006SRR3028759WGS515705385264PRJNA305824...SHBNI.000119ILLUMINA2015-12-19T00:00:00ZHeidelbergSRP067504SH14-006entericaSalmonella gastroenteritisHomo sapiens
6hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram...SH14-00713PresentSH14-007SRR3028760WGS511770747207PRJNA305824...SHBNI.000119ILLUMINA2015-12-19T00:00:00ZHeidelbergSRP067504SH14-007entericaSalmonella gastroenteritisHomo sapiens
7hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram...SH14-00843PresentSH14-008SRR3028761WGS510495519791PRJNA305824...SHBNI.000119ILLUMINA2015-12-19T00:00:00ZHeidelbergSRP067504SH14-008entericaSalmonella gastroenteritisHomo sapiens
8hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram...SH14-01129PresentSH14-011SRR3028764WGS516658814410PRJNA305824...SHBNI.000117ILLUMINA2015-12-19T00:00:00ZHeidelbergSRP067504SH14-011entericaSalmonella gastroenteritisHomo sapiens
9hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram...SH14-01225PresentSH14-012SRR3028765WGS524802527201PRJNA305824...SHBNI.0001ATHE-35ILLUMINA2015-12-19T00:00:00ZHeidelbergSRP067504SH14-012entericaSalmonella gastroenteritisHomo sapiens
10hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram...SH14-01946PresentSH14-019SRR3028772WGS514372480499PRJNA305824...SHBNI.000119ILLUMINA2015-12-19T00:00:00ZHeidelbergSRP067504SH14-019entericaNaNNaN
11hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram...SH14-0218PresentSH14-021SRR3028774WGS517409621309PRJNA305824...SHBNI.000119ILLUMINA2015-12-19T00:00:00ZHeidelbergSRP067504SH14-021entericaNaNNaN
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12 rows × 44 columns

\n", "
" ], "text/plain": [ " Query Sample Name Sample ID \\\n", "0 hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram... SH10-30 16 \n", "1 hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram... SH14-002 30 \n", "2 hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram... SH14-003 20 \n", "3 hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram... SH14-004 52 \n", "4 hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram... SH14-005 11 \n", "5 hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram... SH14-006 24 \n", "6 hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram... SH14-007 13 \n", "7 hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram... SH14-008 43 \n", "8 hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram... SH14-011 29 \n", "9 hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram... SH14-012 25 \n", "10 hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram... SH14-019 46 \n", "11 hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram... SH14-021 8 \n", "\n", " Status Sample Name Orig Run Assay Type AvgSpotLen Bases \\\n", "0 Present SH10-30 SRR3028794 WGS 408 614636422 \n", "1 Present SH14-002 SRR3028755 WGS 513 687874904 \n", "2 Present SH14-003 SRR3028756 WGS 508 697302985 \n", "3 Present SH14-004 SRR3028757 WGS 505 808762405 \n", "4 Present SH14-005 SRR3028758 WGS 510 852322915 \n", "5 Present SH14-006 SRR3028759 WGS 515 705385264 \n", "6 Present SH14-007 SRR3028760 WGS 511 770747207 \n", "7 Present SH14-008 SRR3028761 WGS 510 495519791 \n", "8 Present SH14-011 SRR3028764 WGS 516 658814410 \n", "9 Present SH14-012 SRR3028765 WGS 524 802527201 \n", "10 Present SH14-019 SRR3028772 WGS 514 372480499 \n", "11 Present SH14-021 SRR3028774 WGS 517 409621309 \n", "\n", " BioProject ... PFGE_SecondaryEnzyme_pattern Phagetype Platform \\\n", "0 PRJNA305824 ... SHBNI.0001 29 ILLUMINA \n", "1 PRJNA305824 ... SHBNI.0001 19 ILLUMINA \n", "2 PRJNA305824 ... SHBNI.0001 19 ILLUMINA \n", "3 PRJNA305824 ... SHBNI.0001 19 ILLUMINA \n", "4 PRJNA305824 ... SHBNI.0001 19 ILLUMINA \n", "5 PRJNA305824 ... SHBNI.0001 19 ILLUMINA \n", "6 PRJNA305824 ... SHBNI.0001 19 ILLUMINA \n", "7 PRJNA305824 ... SHBNI.0001 19 ILLUMINA \n", "8 PRJNA305824 ... SHBNI.0001 17 ILLUMINA \n", "9 PRJNA305824 ... SHBNI.0001 ATHE-35 ILLUMINA \n", "10 PRJNA305824 ... SHBNI.0001 19 ILLUMINA \n", "11 PRJNA305824 ... SHBNI.0001 19 ILLUMINA \n", "\n", " ReleaseDate Serovar SRA Study STRAIN sub_species \\\n", "0 2015-12-19T00:00:00Z Heidelberg SRP067504 SH10-30 enterica \n", "1 2015-12-19T00:00:00Z Heidelberg SRP067504 SH14-002 enterica \n", "2 2015-12-19T00:00:00Z Heidelberg SRP067504 SH14-003 enterica \n", "3 2015-12-19T00:00:00Z Heidelberg SRP067504 SH14-004 enterica \n", "4 2015-12-19T00:00:00Z Heidelberg SRP067504 SH14-005 enterica \n", "5 2015-12-19T00:00:00Z Heidelberg SRP067504 SH14-006 enterica \n", "6 2015-12-19T00:00:00Z Heidelberg SRP067504 SH14-007 enterica \n", "7 2015-12-19T00:00:00Z Heidelberg SRP067504 SH14-008 enterica \n", "8 2015-12-19T00:00:00Z Heidelberg SRP067504 SH14-011 enterica \n", "9 2015-12-19T00:00:00Z Heidelberg SRP067504 SH14-012 enterica \n", "10 2015-12-19T00:00:00Z Heidelberg SRP067504 SH14-019 enterica \n", "11 2015-12-19T00:00:00Z Heidelberg SRP067504 SH14-021 enterica \n", "\n", " Host_disease Host \n", "0 Salmonella gastroenteritis Homo sapiens \n", "1 Salmonella gastroenteritis Homo sapiens \n", "2 Salmonella gastroenteritis Homo sapiens \n", "3 Salmonella gastroenteritis Homo sapiens \n", "4 Salmonella gastroenteritis Homo sapiens \n", "5 Salmonella gastroenteritis Homo sapiens \n", "6 Salmonella gastroenteritis Homo sapiens \n", "7 Salmonella gastroenteritis Homo sapiens \n", "8 Salmonella gastroenteritis Homo sapiens \n", "9 Salmonella gastroenteritis Homo sapiens \n", "10 NaN NaN \n", "11 NaN NaN \n", "\n", "[12 rows x 44 columns]" ] }, "execution_count": 40, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q.hasa('hgvs:NC_011083.1:SEHA_RS17780:c.1080T>C').toframe()" ] }, { "cell_type": "markdown", "id": "f490a58b-ade8-4b1a-91ea-14d904dc6885", "metadata": {}, "source": [ "Running `toframe()` will add some additional columns to the front of the external data frame defining the genomics query information." ] }, { "cell_type": "markdown", "id": "416004c7-b77e-4fa9-97a6-fefb3c88a1e6", "metadata": {}, "source": [ "## 4.8 Selecting by column values using `isa()`\n", "\n", "We can now use the `isa()` method to select samples by values in a particular metadata column. For example, to select all samples with an **Isolation_source** of `food` we can use:" ] }, { "cell_type": "code", "execution_count": 41, "id": "2781766f-4bb3-4ad9-90a5-55d0ed2388bd", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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QuerySample NameStatusIsolation_source
0hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram...SH14-014Presentfood
1hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram...SH14-019Presentfood
2hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram...SH14-021Presentfood
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" ], "text/plain": [ " Query Sample Name Status \\\n", "0 hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram... SH14-014 Present \n", "1 hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram... SH14-019 Present \n", "2 hgvs_gn:NC_011083.1:siiE:p.R1263S AND datafram... SH14-021 Present \n", "\n", " Isolation_source \n", "0 food \n", "1 food \n", "2 food " ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q.isa('food', isa_column='Isolation_source', kind='dataframe').toframe()[\n", " ['Query', 'Sample Name', 'Status', 'Isolation_source']].head(3)" ] }, { "cell_type": "markdown", "id": "65985873-7fc3-48b1-98ef-9485b1ae9f88", "metadata": {}, "source": [ "To make it easier to write these query expressions, you can set a default column for `isa()` queries when joining to a dataframe:" ] }, { "cell_type": "code", "execution_count": 42, "id": "af2ee367-4ced-4481-b660-3b2e1a4eb8e3", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
QuerySample NameStatusIsolation_source
0dataframe(names_col=[Sample Name Orig]) AND is...SH12-009Presentfood
1dataframe(names_col=[Sample Name Orig]) AND is...SH12-010Presentfood
2dataframe(names_col=[Sample Name Orig]) AND is...SH14-013Presentfood
\n", "
" ], "text/plain": [ " Query Sample Name Status \\\n", "0 dataframe(names_col=[Sample Name Orig]) AND is... SH12-009 Present \n", "1 dataframe(names_col=[Sample Name Orig]) AND is... SH12-010 Present \n", "2 dataframe(names_col=[Sample Name Orig]) AND is... SH14-013 Present \n", "\n", " Isolation_source \n", "0 food \n", "1 food \n", "2 food " ] }, "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q = db.samples_query().join(metadata_df, sample_names_column='Sample Name Orig',\n", " default_isa_kind='dataframe', default_isa_column='Isolation_source')\n", "\n", "q.isa('food').toframe()[['Query', 'Sample Name', 'Status', 'Isolation_source']].head(3)" ] }, { "cell_type": "markdown", "id": "47ca3495-2faa-4004-bba2-60db5fd8520e", "metadata": {}, "source": [ "You can also pass `regex=True` to `isa()` to query by a regex." ] }, { "cell_type": "markdown", "id": "4a898e8f-f7ce-43fa-97d5-e97fcda1719e", "metadata": {}, "source": [ "## 4.9 Selecting by pandas selection expressions\n", "\n", "You can also select samples using the more powerful pandas selection expressions. You use the `isin()` method for this.\n", "\n", "For example, an alternative way to select samples where **Isolation_source** is `food` is:" ] }, { "cell_type": "code", "execution_count": 43, "id": "79f33015-2c73-4d65-b452-397d5b960a83", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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QuerySample NameStatusIsolation_source
0dataframe(names_col=[Sample Name Orig]) AND is...SH12-009Presentfood
1dataframe(names_col=[Sample Name Orig]) AND is...SH12-010Presentfood
2dataframe(names_col=[Sample Name Orig]) AND is...SH14-013Presentfood
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" ], "text/plain": [ " Query Sample Name Status \\\n", "0 dataframe(names_col=[Sample Name Orig]) AND is... SH12-009 Present \n", "1 dataframe(names_col=[Sample Name Orig]) AND is... SH12-010 Present \n", "2 dataframe(names_col=[Sample Name Orig]) AND is... SH14-013 Present \n", "\n", " Isolation_source \n", "0 food \n", "1 food \n", "2 food " ] }, "execution_count": 43, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q.isin(metadata_df['Isolation_source'] == 'food', kind='dataframe').toframe()[\n", " ['Query', 'Sample Name', 'Status', 'Isolation_source']].head(3)" ] }, { "cell_type": "markdown", "id": "844d79d9-fc31-4258-90bd-7f734c51868b", "metadata": {}, "source": [ "# 5. Working with MLST results\n", "\n", "So far we've been working with mutations (specified either as nucleotides or as amino acids). But we can also use the same query syntax to work with MLST data.\n", "\n", "MLST (multi-locus sequence typing) data specifies genomic features as a combination of a **Scheme**, **Locus (gene)**, and **Allele**. For example, `Scheme=senterica`...\n", "\n", "## 5.1. Viewing all MLST data\n", "\n", "To view all MLST schemes available in the system, we can use `db.mlst_schemes()`." ] }, { "cell_type": "code", "execution_count": 44, "id": "6fe6a338-57cc-4b54-9062-82f020366604", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['senterica', 'sistr_330']" ] }, "execution_count": 44, "metadata": {}, "output_type": "execute_result" } ], "source": [ "db.mlst_schemes()" ] }, { "cell_type": "markdown", "id": "a47a0d4a-8ca8-4982-98d8-6c51d95ae7c2", "metadata": {}, "source": [ "This says we have two MLST schemes: `senterica` and `sistr_330`.\n", "\n", "To view all MLST features for a particular scheme, we can use `db.mlst_summary()`." ] }, { "cell_type": "code", "execution_count": 45, "id": "a8e4d8a7-fb1e-4bdf-93bc-3a4c002d10d6", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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SchemeLocusAlleleCountUnknown CountPresent and Unknown CountTotalPercentUnknown PercentPresent and Unknown Percent
MLST Feature
mlst:senterica:aroC:2sentericaaroC259<NA><NA>59100.0<NA><NA>
mlst:senterica:dnaN:7sentericadnaN759<NA><NA>59100.0<NA><NA>
mlst:senterica:hemD:9sentericahemD959<NA><NA>59100.0<NA><NA>
mlst:senterica:hisD:9sentericahisD959<NA><NA>59100.0<NA><NA>
mlst:senterica:purE:5sentericapurE559<NA><NA>59100.0<NA><NA>
mlst:senterica:sucA:9sentericasucA959<NA><NA>59100.0<NA><NA>
mlst:senterica:thrA:12sentericathrA1259<NA><NA>59100.0<NA><NA>
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" ], "text/plain": [ " Scheme Locus Allele Count Unknown Count \\\n", "MLST Feature \n", "mlst:senterica:aroC:2 senterica aroC 2 59 \n", "mlst:senterica:dnaN:7 senterica dnaN 7 59 \n", "mlst:senterica:hemD:9 senterica hemD 9 59 \n", "mlst:senterica:hisD:9 senterica hisD 9 59 \n", "mlst:senterica:purE:5 senterica purE 5 59 \n", "mlst:senterica:sucA:9 senterica sucA 9 59 \n", "mlst:senterica:thrA:12 senterica thrA 12 59 \n", "\n", " Present and Unknown Count Total Percent \\\n", "MLST Feature \n", "mlst:senterica:aroC:2 59 100.0 \n", "mlst:senterica:dnaN:7 59 100.0 \n", "mlst:senterica:hemD:9 59 100.0 \n", "mlst:senterica:hisD:9 59 100.0 \n", "mlst:senterica:purE:5 59 100.0 \n", "mlst:senterica:sucA:9 59 100.0 \n", "mlst:senterica:thrA:12 59 100.0 \n", "\n", " Unknown Percent Present and Unknown Percent \n", "MLST Feature \n", "mlst:senterica:aroC:2 \n", "mlst:senterica:dnaN:7 \n", "mlst:senterica:hemD:9 \n", "mlst:senterica:hisD:9 \n", "mlst:senterica:purE:5 \n", "mlst:senterica:sucA:9 \n", "mlst:senterica:thrA:12 " ] }, "execution_count": 45, "metadata": {}, "output_type": "execute_result" } ], "source": [ "db.mlst_summary(scheme_name='senterica').sort_values('Count', ascending=False)" ] }, { "cell_type": "markdown", "id": "7349c67e-519f-49b6-9b71-af2c321cabd8", "metadata": {}, "source": [ "In this case, every genome has all the same classic 7-gene MLST alleles (all 100% for the **Percent** column)." ] }, { "cell_type": "code", "execution_count": 46, "id": "e4ba128e-72ce-45fe-b054-f56996620fd2", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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SchemeLocusAlleleCountUnknown CountPresent and Unknown CountTotalPercentUnknown PercentPresent and Unknown Percent
MLST Feature
mlst:sistr_330:NC_003198.1_3005:419666160sistr_330NC_003198.1_300541966616059NaNNaN59100.000000NaNNaN
mlst:sistr_330:NZ_AOXE01000068.1_67:3713645811sistr_330NZ_AOXE01000068.1_67371364581159NaNNaN59100.000000NaNNaN
mlst:sistr_330:NZ_AOXE01000068.1_58:93691856sistr_330NZ_AOXE01000068.1_589369185659NaNNaN59100.000000NaNNaN
mlst:sistr_330:NZ_AOXE01000068.1_52:1426386553sistr_330NZ_AOXE01000068.1_52142638655359NaNNaN59100.000000NaNNaN
mlst:sistr_330:NZ_AOXE01000068.1_5:4267848688sistr_330NZ_AOXE01000068.1_5426784868859NaNNaN59100.000000NaNNaN
.................................
mlst:sistr_330:NZ_AOXE01000072.1_65:2777708285sistr_330NZ_AOXE01000072.1_6527777082851NaNNaN591.694915NaNNaN
mlst:sistr_330:NZ_AOXE01000059.1_430:1260977859sistr_330NZ_AOXE01000059.1_43012609778591NaNNaN591.694915NaNNaN
mlst:sistr_330:NZ_AOXE01000059.1_433:4100983823sistr_330NZ_AOXE01000059.1_43341009838231NaNNaN591.694915NaNNaN
mlst:sistr_330:NZ_AOYX01000092.1_135:466472938sistr_330NZ_AOYX01000092.1_1354664729381NaNNaN591.694915NaNNaN
mlst:sistr_330:NZ_AOXE01000034.1_119:1444220767sistr_330NZ_AOXE01000034.1_11914442207671NaNNaN591.694915NaNNaN
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347 rows × 10 columns

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" ], "text/plain": [ " Scheme \\\n", "MLST Feature \n", "mlst:sistr_330:NC_003198.1_3005:419666160 sistr_330 \n", "mlst:sistr_330:NZ_AOXE01000068.1_67:3713645811 sistr_330 \n", "mlst:sistr_330:NZ_AOXE01000068.1_58:93691856 sistr_330 \n", "mlst:sistr_330:NZ_AOXE01000068.1_52:1426386553 sistr_330 \n", "mlst:sistr_330:NZ_AOXE01000068.1_5:4267848688 sistr_330 \n", "... ... \n", "mlst:sistr_330:NZ_AOXE01000072.1_65:2777708285 sistr_330 \n", "mlst:sistr_330:NZ_AOXE01000059.1_430:1260977859 sistr_330 \n", "mlst:sistr_330:NZ_AOXE01000059.1_433:4100983823 sistr_330 \n", "mlst:sistr_330:NZ_AOYX01000092.1_135:466472938 sistr_330 \n", "mlst:sistr_330:NZ_AOXE01000034.1_119:1444220767 sistr_330 \n", "\n", " Locus \\\n", "MLST Feature \n", "mlst:sistr_330:NC_003198.1_3005:419666160 NC_003198.1_3005 \n", "mlst:sistr_330:NZ_AOXE01000068.1_67:3713645811 NZ_AOXE01000068.1_67 \n", "mlst:sistr_330:NZ_AOXE01000068.1_58:93691856 NZ_AOXE01000068.1_58 \n", "mlst:sistr_330:NZ_AOXE01000068.1_52:1426386553 NZ_AOXE01000068.1_52 \n", "mlst:sistr_330:NZ_AOXE01000068.1_5:4267848688 NZ_AOXE01000068.1_5 \n", "... ... \n", "mlst:sistr_330:NZ_AOXE01000072.1_65:2777708285 NZ_AOXE01000072.1_65 \n", "mlst:sistr_330:NZ_AOXE01000059.1_430:1260977859 NZ_AOXE01000059.1_430 \n", "mlst:sistr_330:NZ_AOXE01000059.1_433:4100983823 NZ_AOXE01000059.1_433 \n", "mlst:sistr_330:NZ_AOYX01000092.1_135:466472938 NZ_AOYX01000092.1_135 \n", "mlst:sistr_330:NZ_AOXE01000034.1_119:1444220767 NZ_AOXE01000034.1_119 \n", "\n", " Allele Count \\\n", "MLST Feature \n", "mlst:sistr_330:NC_003198.1_3005:419666160 419666160 59 \n", "mlst:sistr_330:NZ_AOXE01000068.1_67:3713645811 3713645811 59 \n", "mlst:sistr_330:NZ_AOXE01000068.1_58:93691856 93691856 59 \n", "mlst:sistr_330:NZ_AOXE01000068.1_52:1426386553 1426386553 59 \n", "mlst:sistr_330:NZ_AOXE01000068.1_5:4267848688 4267848688 59 \n", "... ... ... \n", "mlst:sistr_330:NZ_AOXE01000072.1_65:2777708285 2777708285 1 \n", "mlst:sistr_330:NZ_AOXE01000059.1_430:1260977859 1260977859 1 \n", "mlst:sistr_330:NZ_AOXE01000059.1_433:4100983823 4100983823 1 \n", "mlst:sistr_330:NZ_AOYX01000092.1_135:466472938 466472938 1 \n", "mlst:sistr_330:NZ_AOXE01000034.1_119:1444220767 1444220767 1 \n", "\n", " Unknown Count \\\n", "MLST Feature \n", "mlst:sistr_330:NC_003198.1_3005:419666160 NaN \n", "mlst:sistr_330:NZ_AOXE01000068.1_67:3713645811 NaN \n", "mlst:sistr_330:NZ_AOXE01000068.1_58:93691856 NaN \n", "mlst:sistr_330:NZ_AOXE01000068.1_52:1426386553 NaN \n", "mlst:sistr_330:NZ_AOXE01000068.1_5:4267848688 NaN \n", "... ... \n", "mlst:sistr_330:NZ_AOXE01000072.1_65:2777708285 NaN \n", "mlst:sistr_330:NZ_AOXE01000059.1_430:1260977859 NaN \n", "mlst:sistr_330:NZ_AOXE01000059.1_433:4100983823 NaN \n", "mlst:sistr_330:NZ_AOYX01000092.1_135:466472938 NaN \n", "mlst:sistr_330:NZ_AOXE01000034.1_119:1444220767 NaN \n", "\n", " Present and Unknown Count \\\n", "MLST Feature \n", "mlst:sistr_330:NC_003198.1_3005:419666160 NaN \n", "mlst:sistr_330:NZ_AOXE01000068.1_67:3713645811 NaN \n", "mlst:sistr_330:NZ_AOXE01000068.1_58:93691856 NaN \n", "mlst:sistr_330:NZ_AOXE01000068.1_52:1426386553 NaN \n", "mlst:sistr_330:NZ_AOXE01000068.1_5:4267848688 NaN \n", "... ... \n", "mlst:sistr_330:NZ_AOXE01000072.1_65:2777708285 NaN \n", "mlst:sistr_330:NZ_AOXE01000059.1_430:1260977859 NaN \n", "mlst:sistr_330:NZ_AOXE01000059.1_433:4100983823 NaN \n", "mlst:sistr_330:NZ_AOYX01000092.1_135:466472938 NaN \n", "mlst:sistr_330:NZ_AOXE01000034.1_119:1444220767 NaN \n", "\n", " Total Percent \\\n", "MLST Feature \n", "mlst:sistr_330:NC_003198.1_3005:419666160 59 100.000000 \n", "mlst:sistr_330:NZ_AOXE01000068.1_67:3713645811 59 100.000000 \n", "mlst:sistr_330:NZ_AOXE01000068.1_58:93691856 59 100.000000 \n", "mlst:sistr_330:NZ_AOXE01000068.1_52:1426386553 59 100.000000 \n", "mlst:sistr_330:NZ_AOXE01000068.1_5:4267848688 59 100.000000 \n", "... ... ... \n", "mlst:sistr_330:NZ_AOXE01000072.1_65:2777708285 59 1.694915 \n", "mlst:sistr_330:NZ_AOXE01000059.1_430:1260977859 59 1.694915 \n", "mlst:sistr_330:NZ_AOXE01000059.1_433:4100983823 59 1.694915 \n", "mlst:sistr_330:NZ_AOYX01000092.1_135:466472938 59 1.694915 \n", "mlst:sistr_330:NZ_AOXE01000034.1_119:1444220767 59 1.694915 \n", "\n", " Unknown Percent \\\n", "MLST Feature \n", "mlst:sistr_330:NC_003198.1_3005:419666160 NaN \n", "mlst:sistr_330:NZ_AOXE01000068.1_67:3713645811 NaN \n", "mlst:sistr_330:NZ_AOXE01000068.1_58:93691856 NaN \n", "mlst:sistr_330:NZ_AOXE01000068.1_52:1426386553 NaN \n", "mlst:sistr_330:NZ_AOXE01000068.1_5:4267848688 NaN \n", "... ... \n", "mlst:sistr_330:NZ_AOXE01000072.1_65:2777708285 NaN \n", "mlst:sistr_330:NZ_AOXE01000059.1_430:1260977859 NaN \n", "mlst:sistr_330:NZ_AOXE01000059.1_433:4100983823 NaN \n", "mlst:sistr_330:NZ_AOYX01000092.1_135:466472938 NaN \n", "mlst:sistr_330:NZ_AOXE01000034.1_119:1444220767 NaN \n", "\n", " Present and Unknown Percent \n", "MLST Feature \n", "mlst:sistr_330:NC_003198.1_3005:419666160 NaN \n", "mlst:sistr_330:NZ_AOXE01000068.1_67:3713645811 NaN \n", "mlst:sistr_330:NZ_AOXE01000068.1_58:93691856 NaN \n", "mlst:sistr_330:NZ_AOXE01000068.1_52:1426386553 NaN \n", "mlst:sistr_330:NZ_AOXE01000068.1_5:4267848688 NaN \n", "... ... \n", "mlst:sistr_330:NZ_AOXE01000072.1_65:2777708285 NaN \n", "mlst:sistr_330:NZ_AOXE01000059.1_430:1260977859 NaN \n", "mlst:sistr_330:NZ_AOXE01000059.1_433:4100983823 NaN \n", "mlst:sistr_330:NZ_AOYX01000092.1_135:466472938 NaN \n", "mlst:sistr_330:NZ_AOXE01000034.1_119:1444220767 NaN \n", "\n", "[347 rows x 10 columns]" ] }, "execution_count": 46, "metadata": {}, "output_type": "execute_result" } ], "source": [ "db.mlst_summary(scheme_name='sistr_330').sort_values('Count', ascending=False)" ] }, { "cell_type": "markdown", "id": "a6d52aab-d1f9-4014-8589-6c92a3a84ca7", "metadata": {}, "source": [ "The [SISTR](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0147101) MLST results consist of 330 loci in the scheme, and we can see that not all genomes have the same SISTR alleles (not all alleles have 100% for **Percent**)." ] }, { "cell_type": "markdown", "id": "c3ce770c-3e7b-4a11-910b-5ba415f8b0ab", "metadata": {}, "source": [ "## 5.2. Querying for a specific MLST feature (`hasa()`)\n", "\n", "We can use `hasa()` to also query for genomic samples with a specific MLST feature. We can use the **MLST Feature** listed in the above tables as the identifier." ] }, { "cell_type": "code", "execution_count": 47, "id": "0d0542aa-498c-4aab-8348-85ad56e2aac1", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 47, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q = db.samples_query().hasa('mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850')\n", "q" ] }, { "cell_type": "markdown", "id": "717b999b-a589-4f6f-afb0-3bc2999e0bf4", "metadata": {}, "source": [ "The MLST feature identifier is specified in terms of `mlst:[scheme]:[locus]:[allele]` (i.e., `mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850`).\n", "\n", "Only 11 genomic samples have this particular MLST feature. Similar to the operations on mutations, we can use `q.toframe()` to list the specific genomic samples with this MLST feature." ] }, { "cell_type": "code", "execution_count": 48, "id": "fd442035-9806-4194-9539-b799c76aa601", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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QuerySample NameSample IDStatus
0mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850SH13-0019Present
1mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850SH10-01414Present
2mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850SH11-00223Present
3mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850SH10-01534Present
4mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850SH13-00437Present
5mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850SH13-00638Present
6mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850SH13-00741Present
7mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850SH13-00842Present
8mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850SH13-00345Present
9mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850SH13-00249Present
10mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850SH13-00559Present
\n", "
" ], "text/plain": [ " Query Sample Name Sample ID \\\n", "0 mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850 SH13-001 9 \n", "1 mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850 SH10-014 14 \n", "2 mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850 SH11-002 23 \n", "3 mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850 SH10-015 34 \n", "4 mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850 SH13-004 37 \n", "5 mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850 SH13-006 38 \n", "6 mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850 SH13-007 41 \n", "7 mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850 SH13-008 42 \n", "8 mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850 SH13-003 45 \n", "9 mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850 SH13-002 49 \n", "10 mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850 SH13-005 59 \n", "\n", " Status \n", "0 Present \n", "1 Present \n", "2 Present \n", "3 Present \n", "4 Present \n", "5 Present \n", "6 Present \n", "7 Present \n", "8 Present \n", "9 Present \n", "10 Present " ] }, "execution_count": 48, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q.toframe()" ] }, { "cell_type": "markdown", "id": "a8b84e6c-97b7-4007-8837-a491ff389251", "metadata": {}, "source": [ "We can even combine this together with the previous phylogenetic tree visualization to see how this MLST feature clusters with respect to a tree constructed from mutations." ] }, { "cell_type": "code", "execution_count": 49, "id": "129c0266-0943-4941-933b-336a5f0b872a", "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "" ] }, "execution_count": 49, "metadata": {}, "output_type": "execute_result" } ], "source": [ "t = db.samples_query(universe='mutations', reference_name='NC_011083')\n", "t.tree_styler(show_legend_type_labels=False, include_unknown=False)\\\n", " .highlight(t.hasa('mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850'), legend_label='mlst:1944731850')\\\n", " .render()" ] }, { "cell_type": "markdown", "id": "1fbd909c-6243-4e12-974b-c1776d4b7b13", "metadata": {}, "source": [ "## 5.3. Features summmary\n", "\n", "We can use `features_summary()` on the previous query to view a summary of other MLST features (possibly from other MLST schemes) in our query, or even a summary of mutations." ] }, { "cell_type": "code", "execution_count": 50, "id": "e9b7382e-f495-4dea-a750-441ebe6679de", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 50, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q = db.samples_query().hasa('mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850')\n", "q" ] }, { "cell_type": "code", "execution_count": 51, "id": "248f00c3-4f41-4eb8-ac9e-da78b69ba90c", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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SchemeLocusAlleleCountUnknown CountPresent and Unknown CountTotalPercentUnknown PercentPresent and Unknown Percent
MLST Feature
mlst:sistr_330:NC_003198.1_3005:419666160sistr_330NC_003198.1_300541966616011NaNNaN11100.0NaNNaN
mlst:sistr_330:NZ_AOXE01000072.1_12:2530339645sistr_330NZ_AOXE01000072.1_12253033964511NaNNaN11100.0NaNNaN
mlst:sistr_330:NZ_AOXE01000072.1_100:2740047193sistr_330NZ_AOXE01000072.1_100274004719311NaNNaN11100.0NaNNaN
mlst:sistr_330:NZ_AOXE01000068.1_76:2883770685sistr_330NZ_AOXE01000068.1_76288377068511NaNNaN11100.0NaNNaN
mlst:sistr_330:NZ_AOXE01000068.1_72:739645922sistr_330NZ_AOXE01000068.1_7273964592211NaNNaN11100.0NaNNaN
.................................
mlst:sistr_330:NZ_AOXE01000036.1_16:3783573123sistr_330NZ_AOXE01000036.1_16378357312311NaNNaN11100.0NaNNaN
mlst:sistr_330:NZ_AOXE01000036.1_157:1706422672sistr_330NZ_AOXE01000036.1_157170642267211NaNNaN11100.0NaNNaN
mlst:sistr_330:NZ_AOXE01000036.1_15:519139030sistr_330NZ_AOXE01000036.1_1551913903011NaNNaN11100.0NaNNaN
mlst:sistr_330:NZ_AOXE01000036.1_116:2832724106sistr_330NZ_AOXE01000036.1_116283272410611NaNNaN11100.0NaNNaN
mlst:sistr_330:NZ_CM001471.1_3941:799094037sistr_330NZ_CM001471.1_394179909403711NaNNaN11100.0NaNNaN
\n", "

330 rows × 10 columns

\n", "
" ], "text/plain": [ " Scheme \\\n", "MLST Feature \n", "mlst:sistr_330:NC_003198.1_3005:419666160 sistr_330 \n", "mlst:sistr_330:NZ_AOXE01000072.1_12:2530339645 sistr_330 \n", "mlst:sistr_330:NZ_AOXE01000072.1_100:2740047193 sistr_330 \n", "mlst:sistr_330:NZ_AOXE01000068.1_76:2883770685 sistr_330 \n", "mlst:sistr_330:NZ_AOXE01000068.1_72:739645922 sistr_330 \n", "... ... \n", "mlst:sistr_330:NZ_AOXE01000036.1_16:3783573123 sistr_330 \n", "mlst:sistr_330:NZ_AOXE01000036.1_157:1706422672 sistr_330 \n", "mlst:sistr_330:NZ_AOXE01000036.1_15:519139030 sistr_330 \n", "mlst:sistr_330:NZ_AOXE01000036.1_116:2832724106 sistr_330 \n", "mlst:sistr_330:NZ_CM001471.1_3941:799094037 sistr_330 \n", "\n", " Locus \\\n", "MLST Feature \n", "mlst:sistr_330:NC_003198.1_3005:419666160 NC_003198.1_3005 \n", "mlst:sistr_330:NZ_AOXE01000072.1_12:2530339645 NZ_AOXE01000072.1_12 \n", "mlst:sistr_330:NZ_AOXE01000072.1_100:2740047193 NZ_AOXE01000072.1_100 \n", "mlst:sistr_330:NZ_AOXE01000068.1_76:2883770685 NZ_AOXE01000068.1_76 \n", "mlst:sistr_330:NZ_AOXE01000068.1_72:739645922 NZ_AOXE01000068.1_72 \n", "... ... \n", "mlst:sistr_330:NZ_AOXE01000036.1_16:3783573123 NZ_AOXE01000036.1_16 \n", "mlst:sistr_330:NZ_AOXE01000036.1_157:1706422672 NZ_AOXE01000036.1_157 \n", "mlst:sistr_330:NZ_AOXE01000036.1_15:519139030 NZ_AOXE01000036.1_15 \n", "mlst:sistr_330:NZ_AOXE01000036.1_116:2832724106 NZ_AOXE01000036.1_116 \n", "mlst:sistr_330:NZ_CM001471.1_3941:799094037 NZ_CM001471.1_3941 \n", "\n", " Allele Count \\\n", "MLST Feature \n", "mlst:sistr_330:NC_003198.1_3005:419666160 419666160 11 \n", "mlst:sistr_330:NZ_AOXE01000072.1_12:2530339645 2530339645 11 \n", "mlst:sistr_330:NZ_AOXE01000072.1_100:2740047193 2740047193 11 \n", "mlst:sistr_330:NZ_AOXE01000068.1_76:2883770685 2883770685 11 \n", "mlst:sistr_330:NZ_AOXE01000068.1_72:739645922 739645922 11 \n", "... ... ... \n", "mlst:sistr_330:NZ_AOXE01000036.1_16:3783573123 3783573123 11 \n", "mlst:sistr_330:NZ_AOXE01000036.1_157:1706422672 1706422672 11 \n", "mlst:sistr_330:NZ_AOXE01000036.1_15:519139030 519139030 11 \n", "mlst:sistr_330:NZ_AOXE01000036.1_116:2832724106 2832724106 11 \n", "mlst:sistr_330:NZ_CM001471.1_3941:799094037 799094037 11 \n", "\n", " Unknown Count \\\n", "MLST Feature \n", "mlst:sistr_330:NC_003198.1_3005:419666160 NaN \n", "mlst:sistr_330:NZ_AOXE01000072.1_12:2530339645 NaN \n", "mlst:sistr_330:NZ_AOXE01000072.1_100:2740047193 NaN \n", "mlst:sistr_330:NZ_AOXE01000068.1_76:2883770685 NaN \n", "mlst:sistr_330:NZ_AOXE01000068.1_72:739645922 NaN \n", "... ... \n", "mlst:sistr_330:NZ_AOXE01000036.1_16:3783573123 NaN \n", "mlst:sistr_330:NZ_AOXE01000036.1_157:1706422672 NaN \n", "mlst:sistr_330:NZ_AOXE01000036.1_15:519139030 NaN \n", "mlst:sistr_330:NZ_AOXE01000036.1_116:2832724106 NaN \n", "mlst:sistr_330:NZ_CM001471.1_3941:799094037 NaN \n", "\n", " Present and Unknown Count \\\n", "MLST Feature \n", "mlst:sistr_330:NC_003198.1_3005:419666160 NaN \n", "mlst:sistr_330:NZ_AOXE01000072.1_12:2530339645 NaN \n", "mlst:sistr_330:NZ_AOXE01000072.1_100:2740047193 NaN \n", "mlst:sistr_330:NZ_AOXE01000068.1_76:2883770685 NaN \n", "mlst:sistr_330:NZ_AOXE01000068.1_72:739645922 NaN \n", "... ... \n", "mlst:sistr_330:NZ_AOXE01000036.1_16:3783573123 NaN \n", "mlst:sistr_330:NZ_AOXE01000036.1_157:1706422672 NaN \n", "mlst:sistr_330:NZ_AOXE01000036.1_15:519139030 NaN \n", "mlst:sistr_330:NZ_AOXE01000036.1_116:2832724106 NaN \n", "mlst:sistr_330:NZ_CM001471.1_3941:799094037 NaN \n", "\n", " Total Percent \\\n", "MLST Feature \n", "mlst:sistr_330:NC_003198.1_3005:419666160 11 100.0 \n", "mlst:sistr_330:NZ_AOXE01000072.1_12:2530339645 11 100.0 \n", "mlst:sistr_330:NZ_AOXE01000072.1_100:2740047193 11 100.0 \n", "mlst:sistr_330:NZ_AOXE01000068.1_76:2883770685 11 100.0 \n", "mlst:sistr_330:NZ_AOXE01000068.1_72:739645922 11 100.0 \n", "... ... ... \n", "mlst:sistr_330:NZ_AOXE01000036.1_16:3783573123 11 100.0 \n", "mlst:sistr_330:NZ_AOXE01000036.1_157:1706422672 11 100.0 \n", "mlst:sistr_330:NZ_AOXE01000036.1_15:519139030 11 100.0 \n", "mlst:sistr_330:NZ_AOXE01000036.1_116:2832724106 11 100.0 \n", "mlst:sistr_330:NZ_CM001471.1_3941:799094037 11 100.0 \n", "\n", " Unknown Percent \\\n", "MLST Feature \n", "mlst:sistr_330:NC_003198.1_3005:419666160 NaN \n", "mlst:sistr_330:NZ_AOXE01000072.1_12:2530339645 NaN \n", "mlst:sistr_330:NZ_AOXE01000072.1_100:2740047193 NaN \n", "mlst:sistr_330:NZ_AOXE01000068.1_76:2883770685 NaN \n", "mlst:sistr_330:NZ_AOXE01000068.1_72:739645922 NaN \n", "... ... \n", "mlst:sistr_330:NZ_AOXE01000036.1_16:3783573123 NaN \n", "mlst:sistr_330:NZ_AOXE01000036.1_157:1706422672 NaN \n", "mlst:sistr_330:NZ_AOXE01000036.1_15:519139030 NaN \n", "mlst:sistr_330:NZ_AOXE01000036.1_116:2832724106 NaN \n", "mlst:sistr_330:NZ_CM001471.1_3941:799094037 NaN \n", "\n", " Present and Unknown Percent \n", "MLST Feature \n", "mlst:sistr_330:NC_003198.1_3005:419666160 NaN \n", "mlst:sistr_330:NZ_AOXE01000072.1_12:2530339645 NaN \n", "mlst:sistr_330:NZ_AOXE01000072.1_100:2740047193 NaN \n", "mlst:sistr_330:NZ_AOXE01000068.1_76:2883770685 NaN \n", "mlst:sistr_330:NZ_AOXE01000068.1_72:739645922 NaN \n", "... ... \n", "mlst:sistr_330:NZ_AOXE01000036.1_16:3783573123 NaN \n", "mlst:sistr_330:NZ_AOXE01000036.1_157:1706422672 NaN \n", "mlst:sistr_330:NZ_AOXE01000036.1_15:519139030 NaN \n", "mlst:sistr_330:NZ_AOXE01000036.1_116:2832724106 NaN \n", "mlst:sistr_330:NZ_CM001471.1_3941:799094037 NaN \n", "\n", "[330 rows x 10 columns]" ] }, "execution_count": 51, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q.features_summary(kind='mlst', scheme='sistr_330').sort_values('Count', ascending=False)" ] }, { "cell_type": "code", "execution_count": 52, "id": "46460aa6-472e-42d8-b12e-1456494a7dd7", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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SequencePositionDeletionInsertionTypeCountUnknown CountPresent and Unknown CountTotalPercent...Gene_NameGene_IDFeature_TypeTranscript_BioTypeHGVS.cHGVS.pID_HGVS.cID_HGVS.pID_HGVS_GN.cID_HGVS_GN.p
Mutation
NC_011083.1:1947794:A:GNC_011083.11947794AGSNP11NaNNaN11100.000000...SEHA_RS10125SEHA_RS10125transcriptprotein_codingc.181A>Gp.T61Ahgvs:NC_011083.1:SEHA_RS10125:c.181A>Ghgvs:NC_011083.1:SEHA_RS10125:p.T61Ahgvs_gn:NC_011083.1:SEHA_RS10125:c.181A>Ghgvs_gn:NC_011083.1:SEHA_RS10125:p.T61A
NC_011083.1:379589:C:TNC_011083.1379589CTSNP11NaNNaN11100.000000...SEHA_RS02285SEHA_RS02285transcriptprotein_codingc.353G>Ap.R118Hhgvs:NC_011083.1:SEHA_RS02285:c.353G>Ahgvs:NC_011083.1:SEHA_RS02285:p.R118Hhgvs_gn:NC_011083.1:SEHA_RS02285:c.353G>Ahgvs_gn:NC_011083.1:SEHA_RS02285:p.R118H
NC_011083.1:3533472:C:TNC_011083.13533472CTSNP11NaNNaN11100.000000...SEHA_RS17775SEHA_RS17775transcriptprotein_codingc.975G>Ap.V325Vhgvs:NC_011083.1:SEHA_RS17775:c.975G>Ahgvs:NC_011083.1:SEHA_RS17775:p.V325Vhgvs_gn:NC_011083.1:SEHA_RS17775:c.975G>Ahgvs_gn:NC_011083.1:SEHA_RS17775:p.V325V
NC_011083.1:3691534:C:ANC_011083.13691534CASNP11NaNNaN11100.000000...malTSEHA_RS18595transcriptprotein_codingc.1074C>Ap.S358Rhgvs:NC_011083.1:SEHA_RS18595:c.1074C>Ahgvs:NC_011083.1:SEHA_RS18595:p.S358Rhgvs_gn:NC_011083.1:malT:c.1074C>Ahgvs_gn:NC_011083.1:malT:p.S358R
NC_011083.1:602044:T:GNC_011083.1602044TGSNP11NaNNaN11100.000000...SEHA_RS03410SEHA_RS03410transcriptprotein_codingc.1163T>Gp.V388Ghgvs:NC_011083.1:SEHA_RS03410:c.1163T>Ghgvs:NC_011083.1:SEHA_RS03410:p.V388Ghgvs_gn:NC_011083.1:SEHA_RS03410:c.1163T>Ghgvs_gn:NC_011083.1:SEHA_RS03410:p.V388G
..................................................................
NC_011083.1:2010696:G:TNC_011083.12010696GTSNP1NaNNaN119.090909...SEHA_RS25120-SEHA_RS10450SEHA_RS25120-SEHA_RS10450intergenic_region<NA>n.2010696G>T<NA>hgvs:NC_011083.1:n.2010696G>T<NA>hgvs_gn:NC_011083.1:n.2010696G>T<NA>
NC_011083.1:495275:G:ANC_011083.1495275GASNP1NaNNaN119.090909...sbcCSEHA_RS02910transcriptprotein_codingc.1242C>Tp.A414Ahgvs:NC_011083.1:SEHA_RS02910:c.1242C>Thgvs:NC_011083.1:SEHA_RS02910:p.A414Ahgvs_gn:NC_011083.1:sbcC:c.1242C>Thgvs_gn:NC_011083.1:sbcC:p.A414A
NC_011083.1:1514675:G:ANC_011083.11514675GASNP1NaNNaN119.090909...purR-SEHA_RS08035SEHA_RS08030-SEHA_RS08035intergenic_region<NA>n.1514675G>A<NA>hgvs:NC_011083.1:n.1514675G>A<NA>hgvs_gn:NC_011083.1:n.1514675G>A<NA>
NC_011083.1:3401393:T:ANC_011083.13401393TASNP1NaNNaN119.090909...SEHA_RS17120-SEHA_RS17125SEHA_RS17120-SEHA_RS17125intergenic_region<NA>n.3401393T>A<NA>hgvs:NC_011083.1:n.3401393T>A<NA>hgvs_gn:NC_011083.1:n.3401393T>A<NA>
NC_011083.1:1310359:T:GNC_011083.11310359TGSNP1NaNNaN119.090909...nagKSEHA_RS06940transcriptprotein_codingc.175T>Gp.S59Ahgvs:NC_011083.1:SEHA_RS06940:c.175T>Ghgvs:NC_011083.1:SEHA_RS06940:p.S59Ahgvs_gn:NC_011083.1:nagK:c.175T>Ghgvs_gn:NC_011083.1:nagK:p.S59A
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158 rows × 24 columns

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" ], "text/plain": [ " Sequence Position Deletion Insertion Type Count \\\n", "Mutation \n", "NC_011083.1:1947794:A:G NC_011083.1 1947794 A G SNP 11 \n", "NC_011083.1:379589:C:T NC_011083.1 379589 C T SNP 11 \n", "NC_011083.1:3533472:C:T NC_011083.1 3533472 C T SNP 11 \n", "NC_011083.1:3691534:C:A NC_011083.1 3691534 C A SNP 11 \n", "NC_011083.1:602044:T:G NC_011083.1 602044 T G SNP 11 \n", "... ... ... ... ... ... ... \n", "NC_011083.1:2010696:G:T NC_011083.1 2010696 G T SNP 1 \n", "NC_011083.1:495275:G:A NC_011083.1 495275 G A SNP 1 \n", "NC_011083.1:1514675:G:A NC_011083.1 1514675 G A SNP 1 \n", "NC_011083.1:3401393:T:A NC_011083.1 3401393 T A SNP 1 \n", "NC_011083.1:1310359:T:G NC_011083.1 1310359 T G SNP 1 \n", "\n", " Unknown Count Present and Unknown Count Total \\\n", "Mutation \n", "NC_011083.1:1947794:A:G NaN NaN 11 \n", "NC_011083.1:379589:C:T NaN NaN 11 \n", "NC_011083.1:3533472:C:T NaN NaN 11 \n", "NC_011083.1:3691534:C:A NaN NaN 11 \n", "NC_011083.1:602044:T:G NaN NaN 11 \n", "... ... ... ... \n", "NC_011083.1:2010696:G:T NaN NaN 11 \n", "NC_011083.1:495275:G:A NaN NaN 11 \n", "NC_011083.1:1514675:G:A NaN NaN 11 \n", "NC_011083.1:3401393:T:A NaN NaN 11 \n", "NC_011083.1:1310359:T:G NaN NaN 11 \n", "\n", " Percent ... Gene_Name \\\n", "Mutation ... \n", "NC_011083.1:1947794:A:G 100.000000 ... SEHA_RS10125 \n", "NC_011083.1:379589:C:T 100.000000 ... SEHA_RS02285 \n", "NC_011083.1:3533472:C:T 100.000000 ... SEHA_RS17775 \n", "NC_011083.1:3691534:C:A 100.000000 ... malT \n", "NC_011083.1:602044:T:G 100.000000 ... SEHA_RS03410 \n", "... ... ... ... \n", "NC_011083.1:2010696:G:T 9.090909 ... SEHA_RS25120-SEHA_RS10450 \n", "NC_011083.1:495275:G:A 9.090909 ... sbcC \n", "NC_011083.1:1514675:G:A 9.090909 ... purR-SEHA_RS08035 \n", "NC_011083.1:3401393:T:A 9.090909 ... SEHA_RS17120-SEHA_RS17125 \n", "NC_011083.1:1310359:T:G 9.090909 ... nagK \n", "\n", " Gene_ID Feature_Type \\\n", "Mutation \n", "NC_011083.1:1947794:A:G SEHA_RS10125 transcript \n", "NC_011083.1:379589:C:T SEHA_RS02285 transcript \n", "NC_011083.1:3533472:C:T SEHA_RS17775 transcript \n", "NC_011083.1:3691534:C:A SEHA_RS18595 transcript \n", "NC_011083.1:602044:T:G SEHA_RS03410 transcript \n", "... ... ... \n", "NC_011083.1:2010696:G:T SEHA_RS25120-SEHA_RS10450 intergenic_region \n", "NC_011083.1:495275:G:A SEHA_RS02910 transcript \n", "NC_011083.1:1514675:G:A SEHA_RS08030-SEHA_RS08035 intergenic_region \n", "NC_011083.1:3401393:T:A SEHA_RS17120-SEHA_RS17125 intergenic_region \n", "NC_011083.1:1310359:T:G SEHA_RS06940 transcript \n", "\n", " Transcript_BioType HGVS.c HGVS.p \\\n", "Mutation \n", "NC_011083.1:1947794:A:G protein_coding c.181A>G p.T61A \n", "NC_011083.1:379589:C:T protein_coding c.353G>A p.R118H \n", "NC_011083.1:3533472:C:T protein_coding c.975G>A p.V325V \n", "NC_011083.1:3691534:C:A protein_coding c.1074C>A p.S358R \n", "NC_011083.1:602044:T:G protein_coding c.1163T>G p.V388G \n", "... ... ... ... \n", "NC_011083.1:2010696:G:T n.2010696G>T \n", "NC_011083.1:495275:G:A protein_coding c.1242C>T p.A414A \n", "NC_011083.1:1514675:G:A n.1514675G>A \n", "NC_011083.1:3401393:T:A n.3401393T>A \n", "NC_011083.1:1310359:T:G protein_coding c.175T>G p.S59A \n", "\n", " ID_HGVS.c \\\n", "Mutation \n", "NC_011083.1:1947794:A:G hgvs:NC_011083.1:SEHA_RS10125:c.181A>G \n", "NC_011083.1:379589:C:T hgvs:NC_011083.1:SEHA_RS02285:c.353G>A \n", "NC_011083.1:3533472:C:T hgvs:NC_011083.1:SEHA_RS17775:c.975G>A \n", "NC_011083.1:3691534:C:A hgvs:NC_011083.1:SEHA_RS18595:c.1074C>A \n", "NC_011083.1:602044:T:G hgvs:NC_011083.1:SEHA_RS03410:c.1163T>G \n", "... ... \n", "NC_011083.1:2010696:G:T hgvs:NC_011083.1:n.2010696G>T \n", "NC_011083.1:495275:G:A hgvs:NC_011083.1:SEHA_RS02910:c.1242C>T \n", "NC_011083.1:1514675:G:A hgvs:NC_011083.1:n.1514675G>A \n", "NC_011083.1:3401393:T:A hgvs:NC_011083.1:n.3401393T>A \n", "NC_011083.1:1310359:T:G hgvs:NC_011083.1:SEHA_RS06940:c.175T>G \n", "\n", " ID_HGVS.p \\\n", "Mutation \n", "NC_011083.1:1947794:A:G hgvs:NC_011083.1:SEHA_RS10125:p.T61A \n", "NC_011083.1:379589:C:T hgvs:NC_011083.1:SEHA_RS02285:p.R118H \n", "NC_011083.1:3533472:C:T hgvs:NC_011083.1:SEHA_RS17775:p.V325V \n", "NC_011083.1:3691534:C:A hgvs:NC_011083.1:SEHA_RS18595:p.S358R \n", "NC_011083.1:602044:T:G hgvs:NC_011083.1:SEHA_RS03410:p.V388G \n", "... ... \n", "NC_011083.1:2010696:G:T \n", "NC_011083.1:495275:G:A hgvs:NC_011083.1:SEHA_RS02910:p.A414A \n", "NC_011083.1:1514675:G:A \n", "NC_011083.1:3401393:T:A \n", "NC_011083.1:1310359:T:G hgvs:NC_011083.1:SEHA_RS06940:p.S59A \n", "\n", " ID_HGVS_GN.c \\\n", "Mutation \n", "NC_011083.1:1947794:A:G hgvs_gn:NC_011083.1:SEHA_RS10125:c.181A>G \n", "NC_011083.1:379589:C:T hgvs_gn:NC_011083.1:SEHA_RS02285:c.353G>A \n", "NC_011083.1:3533472:C:T hgvs_gn:NC_011083.1:SEHA_RS17775:c.975G>A \n", "NC_011083.1:3691534:C:A hgvs_gn:NC_011083.1:malT:c.1074C>A \n", "NC_011083.1:602044:T:G hgvs_gn:NC_011083.1:SEHA_RS03410:c.1163T>G \n", "... ... \n", "NC_011083.1:2010696:G:T hgvs_gn:NC_011083.1:n.2010696G>T \n", "NC_011083.1:495275:G:A hgvs_gn:NC_011083.1:sbcC:c.1242C>T \n", "NC_011083.1:1514675:G:A hgvs_gn:NC_011083.1:n.1514675G>A \n", "NC_011083.1:3401393:T:A hgvs_gn:NC_011083.1:n.3401393T>A \n", "NC_011083.1:1310359:T:G hgvs_gn:NC_011083.1:nagK:c.175T>G \n", "\n", " ID_HGVS_GN.p \n", "Mutation \n", "NC_011083.1:1947794:A:G hgvs_gn:NC_011083.1:SEHA_RS10125:p.T61A \n", "NC_011083.1:379589:C:T hgvs_gn:NC_011083.1:SEHA_RS02285:p.R118H \n", "NC_011083.1:3533472:C:T hgvs_gn:NC_011083.1:SEHA_RS17775:p.V325V \n", "NC_011083.1:3691534:C:A hgvs_gn:NC_011083.1:malT:p.S358R \n", "NC_011083.1:602044:T:G hgvs_gn:NC_011083.1:SEHA_RS03410:p.V388G \n", "... ... \n", "NC_011083.1:2010696:G:T \n", "NC_011083.1:495275:G:A hgvs_gn:NC_011083.1:sbcC:p.A414A \n", "NC_011083.1:1514675:G:A \n", "NC_011083.1:3401393:T:A \n", "NC_011083.1:1310359:T:G hgvs_gn:NC_011083.1:nagK:p.S59A \n", "\n", "[158 rows x 24 columns]" ] }, "execution_count": 52, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q.features_summary(kind='mutations').sort_values('Count', ascending=False)" ] }, { "cell_type": "markdown", "id": "7ea5fca1-ea18-4377-b9f4-246947359906", "metadata": {}, "source": [ "This lets us summarize what other genomic features (MLST or mutations) are found in the set of samples that **have a** `mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850` MLST feature.\n", "\n", "Setting `q.features_summary(..., selection='unique')` lets us narrow-down the scope of our summary to only features that are **uniquely** found in the set of genomic samples that **have a** `mlst:sistr_330:NZ_AOXE01000034.1_103:1944731850` MLST feature." ] }, { "cell_type": "code", "execution_count": 53, "id": "413f9712-06b4-4f70-9661-58cb43857863", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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SequencePositionDeletionInsertionTypeCountUnknown CountPresent and Unknown CountTotalPercent...Gene_NameGene_IDFeature_TypeTranscript_BioTypeHGVS.cHGVS.pID_HGVS.cID_HGVS.pID_HGVS_GN.cID_HGVS_GN.p
Mutation
NC_011083.1:3691534:C:ANC_011083.13691534CASNP11NaNNaN11100.000000...malTSEHA_RS18595transcriptprotein_codingc.1074C>Ap.S358Rhgvs:NC_011083.1:SEHA_RS18595:c.1074C>Ahgvs:NC_011083.1:SEHA_RS18595:p.S358Rhgvs_gn:NC_011083.1:malT:c.1074C>Ahgvs_gn:NC_011083.1:malT:p.S358R
NC_011083.1:2428696:AT:ANC_011083.12428696ATAINDEL11NaNNaN11100.000000...SEHA_RS12535-nrdASEHA_RS12535-SEHA_RS12540intergenic_region<NA>n.2428697delT<NA>hgvs:NC_011083.1:n.2428697delT<NA>hgvs_gn:NC_011083.1:n.2428697delT<NA>
NC_011083.1:3796657:C:ANC_011083.13796657CASNP11NaNNaN11100.000000...SEHA_RS19050SEHA_RS19050transcriptprotein_codingc.489C>Ap.G163Ghgvs:NC_011083.1:SEHA_RS19050:c.489C>Ahgvs:NC_011083.1:SEHA_RS19050:p.G163Ghgvs_gn:NC_011083.1:SEHA_RS19050:c.489C>Ahgvs_gn:NC_011083.1:SEHA_RS19050:p.G163G
NC_011083.1:2841095:G:ANC_011083.12841095GASNP11NaNNaN11100.000000...bapASEHA_RS14380transcriptprotein_codingc.5317G>Ap.D1773Nhgvs:NC_011083.1:SEHA_RS14380:c.5317G>Ahgvs:NC_011083.1:SEHA_RS14380:p.D1773Nhgvs_gn:NC_011083.1:bapA:c.5317G>Ahgvs_gn:NC_011083.1:bapA:p.D1773N
NC_011083.1:2209731:A:CNC_011083.12209731ACSNP11NaNNaN11100.000000...SEHA_RS11560SEHA_RS11560transcriptprotein_codingc.250T>Gp.W84Ghgvs:NC_011083.1:SEHA_RS11560:c.250T>Ghgvs:NC_011083.1:SEHA_RS11560:p.W84Ghgvs_gn:NC_011083.1:SEHA_RS11560:c.250T>Ghgvs_gn:NC_011083.1:SEHA_RS11560:p.W84G
..................................................................
NC_011083.1:3535143:A:TNC_011083.13535143ATSNP1NaNNaN119.090909...oadASEHA_RS17780transcriptprotein_codingc.1101T>Ap.I367Ihgvs:NC_011083.1:SEHA_RS17780:c.1101T>Ahgvs:NC_011083.1:SEHA_RS17780:p.I367Ihgvs_gn:NC_011083.1:oadA:c.1101T>Ahgvs_gn:NC_011083.1:oadA:p.I367I
NC_011083.1:1310359:T:GNC_011083.11310359TGSNP1NaNNaN119.090909...nagKSEHA_RS06940transcriptprotein_codingc.175T>Gp.S59Ahgvs:NC_011083.1:SEHA_RS06940:c.175T>Ghgvs:NC_011083.1:SEHA_RS06940:p.S59Ahgvs_gn:NC_011083.1:nagK:c.175T>Ghgvs_gn:NC_011083.1:nagK:p.S59A
NC_011083.1:936248:G:ANC_011083.1936248GASNP1NaNNaN119.090909...rhlESEHA_RS05055transcriptprotein_codingc.1225G>Ap.G409Rhgvs:NC_011083.1:SEHA_RS05055:c.1225G>Ahgvs:NC_011083.1:SEHA_RS05055:p.G409Rhgvs_gn:NC_011083.1:rhlE:c.1225G>Ahgvs_gn:NC_011083.1:rhlE:p.G409R
NC_011083.1:4536022:C:TNC_011083.14536022CTSNP1NaNNaN119.090909...adiASEHA_RS22440transcriptprotein_codingc.909G>Ap.P303Phgvs:NC_011083.1:SEHA_RS22440:c.909G>Ahgvs:NC_011083.1:SEHA_RS22440:p.P303Phgvs_gn:NC_011083.1:adiA:c.909G>Ahgvs_gn:NC_011083.1:adiA:p.P303P
NC_011083.1:4800575:C:TNC_011083.14800575CTSNP1NaNNaN119.090909...SEHA_RS23755-SEHA_RS23765SEHA_RS23755-SEHA_RS23765intergenic_region<NA>n.4800575C>T<NA>hgvs:NC_011083.1:n.4800575C>T<NA>hgvs_gn:NC_011083.1:n.4800575C>T<NA>
\n", "

72 rows × 24 columns

\n", "
" ], "text/plain": [ " Sequence Position Deletion Insertion Type \\\n", "Mutation \n", "NC_011083.1:3691534:C:A NC_011083.1 3691534 C A SNP \n", "NC_011083.1:2428696:AT:A NC_011083.1 2428696 AT A INDEL \n", "NC_011083.1:3796657:C:A NC_011083.1 3796657 C A SNP \n", "NC_011083.1:2841095:G:A NC_011083.1 2841095 G A SNP \n", "NC_011083.1:2209731:A:C NC_011083.1 2209731 A C SNP \n", "... ... ... ... ... ... \n", "NC_011083.1:3535143:A:T NC_011083.1 3535143 A T SNP \n", "NC_011083.1:1310359:T:G NC_011083.1 1310359 T G SNP \n", "NC_011083.1:936248:G:A NC_011083.1 936248 G A SNP \n", "NC_011083.1:4536022:C:T NC_011083.1 4536022 C T SNP \n", "NC_011083.1:4800575:C:T NC_011083.1 4800575 C T SNP \n", "\n", " Count Unknown Count Present and Unknown Count \\\n", "Mutation \n", "NC_011083.1:3691534:C:A 11 NaN NaN \n", "NC_011083.1:2428696:AT:A 11 NaN NaN \n", "NC_011083.1:3796657:C:A 11 NaN NaN \n", "NC_011083.1:2841095:G:A 11 NaN NaN \n", "NC_011083.1:2209731:A:C 11 NaN NaN \n", "... ... ... ... \n", "NC_011083.1:3535143:A:T 1 NaN NaN \n", "NC_011083.1:1310359:T:G 1 NaN NaN \n", "NC_011083.1:936248:G:A 1 NaN NaN \n", "NC_011083.1:4536022:C:T 1 NaN NaN \n", "NC_011083.1:4800575:C:T 1 NaN NaN \n", "\n", " Total Percent ... Gene_Name \\\n", "Mutation ... \n", "NC_011083.1:3691534:C:A 11 100.000000 ... malT \n", "NC_011083.1:2428696:AT:A 11 100.000000 ... SEHA_RS12535-nrdA \n", "NC_011083.1:3796657:C:A 11 100.000000 ... SEHA_RS19050 \n", "NC_011083.1:2841095:G:A 11 100.000000 ... bapA \n", "NC_011083.1:2209731:A:C 11 100.000000 ... SEHA_RS11560 \n", "... ... ... ... ... \n", "NC_011083.1:3535143:A:T 11 9.090909 ... oadA \n", "NC_011083.1:1310359:T:G 11 9.090909 ... nagK \n", "NC_011083.1:936248:G:A 11 9.090909 ... rhlE \n", "NC_011083.1:4536022:C:T 11 9.090909 ... adiA \n", "NC_011083.1:4800575:C:T 11 9.090909 ... SEHA_RS23755-SEHA_RS23765 \n", "\n", " Gene_ID Feature_Type \\\n", "Mutation \n", "NC_011083.1:3691534:C:A SEHA_RS18595 transcript \n", "NC_011083.1:2428696:AT:A SEHA_RS12535-SEHA_RS12540 intergenic_region \n", "NC_011083.1:3796657:C:A SEHA_RS19050 transcript \n", "NC_011083.1:2841095:G:A SEHA_RS14380 transcript \n", "NC_011083.1:2209731:A:C SEHA_RS11560 transcript \n", "... ... ... \n", "NC_011083.1:3535143:A:T SEHA_RS17780 transcript \n", "NC_011083.1:1310359:T:G SEHA_RS06940 transcript \n", "NC_011083.1:936248:G:A SEHA_RS05055 transcript \n", "NC_011083.1:4536022:C:T SEHA_RS22440 transcript \n", "NC_011083.1:4800575:C:T SEHA_RS23755-SEHA_RS23765 intergenic_region \n", "\n", " Transcript_BioType HGVS.c HGVS.p \\\n", "Mutation \n", "NC_011083.1:3691534:C:A protein_coding c.1074C>A p.S358R \n", "NC_011083.1:2428696:AT:A n.2428697delT \n", "NC_011083.1:3796657:C:A protein_coding c.489C>A p.G163G \n", "NC_011083.1:2841095:G:A protein_coding c.5317G>A p.D1773N \n", "NC_011083.1:2209731:A:C protein_coding c.250T>G p.W84G \n", "... ... ... ... \n", "NC_011083.1:3535143:A:T protein_coding c.1101T>A p.I367I \n", "NC_011083.1:1310359:T:G protein_coding c.175T>G p.S59A \n", "NC_011083.1:936248:G:A protein_coding c.1225G>A p.G409R \n", "NC_011083.1:4536022:C:T protein_coding c.909G>A p.P303P \n", "NC_011083.1:4800575:C:T n.4800575C>T \n", "\n", " ID_HGVS.c \\\n", "Mutation \n", "NC_011083.1:3691534:C:A hgvs:NC_011083.1:SEHA_RS18595:c.1074C>A \n", "NC_011083.1:2428696:AT:A hgvs:NC_011083.1:n.2428697delT \n", "NC_011083.1:3796657:C:A hgvs:NC_011083.1:SEHA_RS19050:c.489C>A \n", "NC_011083.1:2841095:G:A hgvs:NC_011083.1:SEHA_RS14380:c.5317G>A \n", "NC_011083.1:2209731:A:C hgvs:NC_011083.1:SEHA_RS11560:c.250T>G \n", "... ... \n", "NC_011083.1:3535143:A:T hgvs:NC_011083.1:SEHA_RS17780:c.1101T>A \n", "NC_011083.1:1310359:T:G hgvs:NC_011083.1:SEHA_RS06940:c.175T>G \n", "NC_011083.1:936248:G:A hgvs:NC_011083.1:SEHA_RS05055:c.1225G>A \n", "NC_011083.1:4536022:C:T hgvs:NC_011083.1:SEHA_RS22440:c.909G>A \n", "NC_011083.1:4800575:C:T hgvs:NC_011083.1:n.4800575C>T \n", "\n", " ID_HGVS.p \\\n", "Mutation \n", "NC_011083.1:3691534:C:A hgvs:NC_011083.1:SEHA_RS18595:p.S358R \n", "NC_011083.1:2428696:AT:A \n", "NC_011083.1:3796657:C:A hgvs:NC_011083.1:SEHA_RS19050:p.G163G \n", "NC_011083.1:2841095:G:A hgvs:NC_011083.1:SEHA_RS14380:p.D1773N \n", "NC_011083.1:2209731:A:C hgvs:NC_011083.1:SEHA_RS11560:p.W84G \n", "... ... \n", "NC_011083.1:3535143:A:T hgvs:NC_011083.1:SEHA_RS17780:p.I367I \n", "NC_011083.1:1310359:T:G hgvs:NC_011083.1:SEHA_RS06940:p.S59A \n", "NC_011083.1:936248:G:A hgvs:NC_011083.1:SEHA_RS05055:p.G409R \n", "NC_011083.1:4536022:C:T hgvs:NC_011083.1:SEHA_RS22440:p.P303P \n", "NC_011083.1:4800575:C:T \n", "\n", " ID_HGVS_GN.c \\\n", "Mutation \n", "NC_011083.1:3691534:C:A hgvs_gn:NC_011083.1:malT:c.1074C>A \n", "NC_011083.1:2428696:AT:A hgvs_gn:NC_011083.1:n.2428697delT \n", "NC_011083.1:3796657:C:A hgvs_gn:NC_011083.1:SEHA_RS19050:c.489C>A \n", "NC_011083.1:2841095:G:A hgvs_gn:NC_011083.1:bapA:c.5317G>A \n", "NC_011083.1:2209731:A:C hgvs_gn:NC_011083.1:SEHA_RS11560:c.250T>G \n", "... ... \n", "NC_011083.1:3535143:A:T hgvs_gn:NC_011083.1:oadA:c.1101T>A \n", "NC_011083.1:1310359:T:G hgvs_gn:NC_011083.1:nagK:c.175T>G \n", "NC_011083.1:936248:G:A hgvs_gn:NC_011083.1:rhlE:c.1225G>A \n", "NC_011083.1:4536022:C:T hgvs_gn:NC_011083.1:adiA:c.909G>A \n", "NC_011083.1:4800575:C:T hgvs_gn:NC_011083.1:n.4800575C>T \n", "\n", " ID_HGVS_GN.p \n", "Mutation \n", "NC_011083.1:3691534:C:A hgvs_gn:NC_011083.1:malT:p.S358R \n", "NC_011083.1:2428696:AT:A \n", "NC_011083.1:3796657:C:A hgvs_gn:NC_011083.1:SEHA_RS19050:p.G163G \n", "NC_011083.1:2841095:G:A hgvs_gn:NC_011083.1:bapA:p.D1773N \n", "NC_011083.1:2209731:A:C hgvs_gn:NC_011083.1:SEHA_RS11560:p.W84G \n", "... ... \n", "NC_011083.1:3535143:A:T hgvs_gn:NC_011083.1:oadA:p.I367I \n", "NC_011083.1:1310359:T:G hgvs_gn:NC_011083.1:nagK:p.S59A \n", "NC_011083.1:936248:G:A hgvs_gn:NC_011083.1:rhlE:p.G409R \n", "NC_011083.1:4536022:C:T hgvs_gn:NC_011083.1:adiA:p.P303P \n", "NC_011083.1:4800575:C:T \n", "\n", "[72 rows x 24 columns]" ] }, "execution_count": 53, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q.features_summary(kind='mutations', selection='unique').sort_values('Count', ascending=False)" ] }, { "cell_type": "markdown", "id": "81606d37-efc4-4de5-bfd9-b5f6d79fde5b", "metadata": {}, "source": [ "Similar to `mutations_summary()` to calculate values for the **Unknown Count** and **Present and Unknown Count** columns you can pass `include_unknown_sampes=True`. This might slow down the table generation for larger datasets." ] }, { "cell_type": "code", "execution_count": 54, "id": "4d8f74f4-cb8b-4013-a82c-662329ade6b9", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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SequencePositionDeletionInsertionTypeCountUnknown CountPresent and Unknown CountTotalPercent...Gene_NameGene_IDFeature_TypeTranscript_BioTypeHGVS.cHGVS.pID_HGVS.cID_HGVS.pID_HGVS_GN.cID_HGVS_GN.p
Mutation
NC_011083.1:3691534:C:ANC_011083.13691534CASNP1101111100.000000...malTSEHA_RS18595transcriptprotein_codingc.1074C>Ap.S358Rhgvs:NC_011083.1:SEHA_RS18595:c.1074C>Ahgvs:NC_011083.1:SEHA_RS18595:p.S358Rhgvs_gn:NC_011083.1:malT:c.1074C>Ahgvs_gn:NC_011083.1:malT:p.S358R
NC_011083.1:2428696:AT:ANC_011083.12428696ATAINDEL1101111100.000000...SEHA_RS12535-nrdASEHA_RS12535-SEHA_RS12540intergenic_region<NA>n.2428697delT<NA>hgvs:NC_011083.1:n.2428697delT<NA>hgvs_gn:NC_011083.1:n.2428697delT<NA>
NC_011083.1:3796657:C:ANC_011083.13796657CASNP1101111100.000000...SEHA_RS19050SEHA_RS19050transcriptprotein_codingc.489C>Ap.G163Ghgvs:NC_011083.1:SEHA_RS19050:c.489C>Ahgvs:NC_011083.1:SEHA_RS19050:p.G163Ghgvs_gn:NC_011083.1:SEHA_RS19050:c.489C>Ahgvs_gn:NC_011083.1:SEHA_RS19050:p.G163G
NC_011083.1:2841095:G:ANC_011083.12841095GASNP1101111100.000000...bapASEHA_RS14380transcriptprotein_codingc.5317G>Ap.D1773Nhgvs:NC_011083.1:SEHA_RS14380:c.5317G>Ahgvs:NC_011083.1:SEHA_RS14380:p.D1773Nhgvs_gn:NC_011083.1:bapA:c.5317G>Ahgvs_gn:NC_011083.1:bapA:p.D1773N
NC_011083.1:2209731:A:CNC_011083.12209731ACSNP1101111100.000000...SEHA_RS11560SEHA_RS11560transcriptprotein_codingc.250T>Gp.W84Ghgvs:NC_011083.1:SEHA_RS11560:c.250T>Ghgvs:NC_011083.1:SEHA_RS11560:p.W84Ghgvs_gn:NC_011083.1:SEHA_RS11560:c.250T>Ghgvs_gn:NC_011083.1:SEHA_RS11560:p.W84G
..................................................................
NC_011083.1:3535143:A:TNC_011083.13535143ATSNP123119.090909...oadASEHA_RS17780transcriptprotein_codingc.1101T>Ap.I367Ihgvs:NC_011083.1:SEHA_RS17780:c.1101T>Ahgvs:NC_011083.1:SEHA_RS17780:p.I367Ihgvs_gn:NC_011083.1:oadA:c.1101T>Ahgvs_gn:NC_011083.1:oadA:p.I367I
NC_011083.1:1310359:T:GNC_011083.11310359TGSNP101119.090909...nagKSEHA_RS06940transcriptprotein_codingc.175T>Gp.S59Ahgvs:NC_011083.1:SEHA_RS06940:c.175T>Ghgvs:NC_011083.1:SEHA_RS06940:p.S59Ahgvs_gn:NC_011083.1:nagK:c.175T>Ghgvs_gn:NC_011083.1:nagK:p.S59A
NC_011083.1:936248:G:ANC_011083.1936248GASNP101119.090909...rhlESEHA_RS05055transcriptprotein_codingc.1225G>Ap.G409Rhgvs:NC_011083.1:SEHA_RS05055:c.1225G>Ahgvs:NC_011083.1:SEHA_RS05055:p.G409Rhgvs_gn:NC_011083.1:rhlE:c.1225G>Ahgvs_gn:NC_011083.1:rhlE:p.G409R
NC_011083.1:4536022:C:TNC_011083.14536022CTSNP101119.090909...adiASEHA_RS22440transcriptprotein_codingc.909G>Ap.P303Phgvs:NC_011083.1:SEHA_RS22440:c.909G>Ahgvs:NC_011083.1:SEHA_RS22440:p.P303Phgvs_gn:NC_011083.1:adiA:c.909G>Ahgvs_gn:NC_011083.1:adiA:p.P303P
NC_011083.1:4800575:C:TNC_011083.14800575CTSNP101119.090909...SEHA_RS23755-SEHA_RS23765SEHA_RS23755-SEHA_RS23765intergenic_region<NA>n.4800575C>T<NA>hgvs:NC_011083.1:n.4800575C>T<NA>hgvs_gn:NC_011083.1:n.4800575C>T<NA>
\n", "

72 rows × 24 columns

\n", "
" ], "text/plain": [ " Sequence Position Deletion Insertion Type \\\n", "Mutation \n", "NC_011083.1:3691534:C:A NC_011083.1 3691534 C A SNP \n", "NC_011083.1:2428696:AT:A NC_011083.1 2428696 AT A INDEL \n", "NC_011083.1:3796657:C:A NC_011083.1 3796657 C A SNP \n", "NC_011083.1:2841095:G:A NC_011083.1 2841095 G A SNP \n", "NC_011083.1:2209731:A:C NC_011083.1 2209731 A C SNP \n", "... ... ... ... ... ... \n", "NC_011083.1:3535143:A:T NC_011083.1 3535143 A T SNP \n", "NC_011083.1:1310359:T:G NC_011083.1 1310359 T G SNP \n", "NC_011083.1:936248:G:A NC_011083.1 936248 G A SNP \n", "NC_011083.1:4536022:C:T NC_011083.1 4536022 C T SNP \n", "NC_011083.1:4800575:C:T NC_011083.1 4800575 C T SNP \n", "\n", " Count Unknown Count Present and Unknown Count \\\n", "Mutation \n", "NC_011083.1:3691534:C:A 11 0 11 \n", "NC_011083.1:2428696:AT:A 11 0 11 \n", "NC_011083.1:3796657:C:A 11 0 11 \n", "NC_011083.1:2841095:G:A 11 0 11 \n", "NC_011083.1:2209731:A:C 11 0 11 \n", "... ... ... ... \n", "NC_011083.1:3535143:A:T 1 2 3 \n", "NC_011083.1:1310359:T:G 1 0 1 \n", "NC_011083.1:936248:G:A 1 0 1 \n", "NC_011083.1:4536022:C:T 1 0 1 \n", "NC_011083.1:4800575:C:T 1 0 1 \n", "\n", " Total Percent ... Gene_Name \\\n", "Mutation ... \n", "NC_011083.1:3691534:C:A 11 100.000000 ... malT \n", "NC_011083.1:2428696:AT:A 11 100.000000 ... SEHA_RS12535-nrdA \n", "NC_011083.1:3796657:C:A 11 100.000000 ... SEHA_RS19050 \n", "NC_011083.1:2841095:G:A 11 100.000000 ... bapA \n", "NC_011083.1:2209731:A:C 11 100.000000 ... SEHA_RS11560 \n", "... ... ... ... ... \n", "NC_011083.1:3535143:A:T 11 9.090909 ... oadA \n", "NC_011083.1:1310359:T:G 11 9.090909 ... nagK \n", "NC_011083.1:936248:G:A 11 9.090909 ... rhlE \n", "NC_011083.1:4536022:C:T 11 9.090909 ... adiA \n", "NC_011083.1:4800575:C:T 11 9.090909 ... SEHA_RS23755-SEHA_RS23765 \n", "\n", " Gene_ID Feature_Type \\\n", "Mutation \n", "NC_011083.1:3691534:C:A SEHA_RS18595 transcript \n", "NC_011083.1:2428696:AT:A SEHA_RS12535-SEHA_RS12540 intergenic_region \n", "NC_011083.1:3796657:C:A SEHA_RS19050 transcript \n", "NC_011083.1:2841095:G:A SEHA_RS14380 transcript \n", "NC_011083.1:2209731:A:C SEHA_RS11560 transcript \n", "... ... ... \n", "NC_011083.1:3535143:A:T SEHA_RS17780 transcript \n", "NC_011083.1:1310359:T:G SEHA_RS06940 transcript \n", "NC_011083.1:936248:G:A SEHA_RS05055 transcript \n", "NC_011083.1:4536022:C:T SEHA_RS22440 transcript \n", "NC_011083.1:4800575:C:T SEHA_RS23755-SEHA_RS23765 intergenic_region \n", "\n", " Transcript_BioType HGVS.c HGVS.p \\\n", "Mutation \n", "NC_011083.1:3691534:C:A protein_coding c.1074C>A p.S358R \n", "NC_011083.1:2428696:AT:A n.2428697delT \n", "NC_011083.1:3796657:C:A protein_coding c.489C>A p.G163G \n", "NC_011083.1:2841095:G:A protein_coding c.5317G>A p.D1773N \n", "NC_011083.1:2209731:A:C protein_coding c.250T>G p.W84G \n", "... ... ... ... \n", "NC_011083.1:3535143:A:T protein_coding c.1101T>A p.I367I \n", "NC_011083.1:1310359:T:G protein_coding c.175T>G p.S59A \n", "NC_011083.1:936248:G:A protein_coding c.1225G>A p.G409R \n", "NC_011083.1:4536022:C:T protein_coding c.909G>A p.P303P \n", "NC_011083.1:4800575:C:T n.4800575C>T \n", "\n", " ID_HGVS.c \\\n", "Mutation \n", "NC_011083.1:3691534:C:A hgvs:NC_011083.1:SEHA_RS18595:c.1074C>A \n", "NC_011083.1:2428696:AT:A hgvs:NC_011083.1:n.2428697delT \n", "NC_011083.1:3796657:C:A hgvs:NC_011083.1:SEHA_RS19050:c.489C>A \n", "NC_011083.1:2841095:G:A hgvs:NC_011083.1:SEHA_RS14380:c.5317G>A \n", "NC_011083.1:2209731:A:C hgvs:NC_011083.1:SEHA_RS11560:c.250T>G \n", "... ... \n", "NC_011083.1:3535143:A:T hgvs:NC_011083.1:SEHA_RS17780:c.1101T>A \n", "NC_011083.1:1310359:T:G hgvs:NC_011083.1:SEHA_RS06940:c.175T>G \n", "NC_011083.1:936248:G:A hgvs:NC_011083.1:SEHA_RS05055:c.1225G>A \n", "NC_011083.1:4536022:C:T hgvs:NC_011083.1:SEHA_RS22440:c.909G>A \n", "NC_011083.1:4800575:C:T hgvs:NC_011083.1:n.4800575C>T \n", "\n", " ID_HGVS.p \\\n", "Mutation \n", "NC_011083.1:3691534:C:A hgvs:NC_011083.1:SEHA_RS18595:p.S358R \n", "NC_011083.1:2428696:AT:A \n", "NC_011083.1:3796657:C:A hgvs:NC_011083.1:SEHA_RS19050:p.G163G \n", "NC_011083.1:2841095:G:A hgvs:NC_011083.1:SEHA_RS14380:p.D1773N \n", "NC_011083.1:2209731:A:C hgvs:NC_011083.1:SEHA_RS11560:p.W84G \n", "... ... \n", "NC_011083.1:3535143:A:T hgvs:NC_011083.1:SEHA_RS17780:p.I367I \n", "NC_011083.1:1310359:T:G hgvs:NC_011083.1:SEHA_RS06940:p.S59A \n", "NC_011083.1:936248:G:A hgvs:NC_011083.1:SEHA_RS05055:p.G409R \n", "NC_011083.1:4536022:C:T hgvs:NC_011083.1:SEHA_RS22440:p.P303P \n", "NC_011083.1:4800575:C:T \n", "\n", " ID_HGVS_GN.c \\\n", "Mutation \n", "NC_011083.1:3691534:C:A hgvs_gn:NC_011083.1:malT:c.1074C>A \n", "NC_011083.1:2428696:AT:A hgvs_gn:NC_011083.1:n.2428697delT \n", "NC_011083.1:3796657:C:A hgvs_gn:NC_011083.1:SEHA_RS19050:c.489C>A \n", "NC_011083.1:2841095:G:A hgvs_gn:NC_011083.1:bapA:c.5317G>A \n", "NC_011083.1:2209731:A:C hgvs_gn:NC_011083.1:SEHA_RS11560:c.250T>G \n", "... ... \n", "NC_011083.1:3535143:A:T hgvs_gn:NC_011083.1:oadA:c.1101T>A \n", "NC_011083.1:1310359:T:G hgvs_gn:NC_011083.1:nagK:c.175T>G \n", "NC_011083.1:936248:G:A hgvs_gn:NC_011083.1:rhlE:c.1225G>A \n", "NC_011083.1:4536022:C:T hgvs_gn:NC_011083.1:adiA:c.909G>A \n", "NC_011083.1:4800575:C:T hgvs_gn:NC_011083.1:n.4800575C>T \n", "\n", " ID_HGVS_GN.p \n", "Mutation \n", "NC_011083.1:3691534:C:A hgvs_gn:NC_011083.1:malT:p.S358R \n", "NC_011083.1:2428696:AT:A \n", "NC_011083.1:3796657:C:A hgvs_gn:NC_011083.1:SEHA_RS19050:p.G163G \n", "NC_011083.1:2841095:G:A hgvs_gn:NC_011083.1:bapA:p.D1773N \n", "NC_011083.1:2209731:A:C hgvs_gn:NC_011083.1:SEHA_RS11560:p.W84G \n", "... ... \n", "NC_011083.1:3535143:A:T hgvs_gn:NC_011083.1:oadA:p.I367I \n", "NC_011083.1:1310359:T:G hgvs_gn:NC_011083.1:nagK:p.S59A \n", "NC_011083.1:936248:G:A hgvs_gn:NC_011083.1:rhlE:p.G409R \n", "NC_011083.1:4536022:C:T hgvs_gn:NC_011083.1:adiA:p.P303P \n", "NC_011083.1:4800575:C:T \n", "\n", "[72 rows x 24 columns]" ] }, "execution_count": 54, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q.features_summary(kind='mutations', selection='unique', include_unknown_samples=True).sort_values('Count', ascending=False)" ] }, { "cell_type": "markdown", "id": "79d441fc-9e35-4c04-b62a-fc9202c1981a", "metadata": {}, "source": [ "# 6. Putting it all together\n", "\n", "So far we've seen connecting to an index (project), querying by mutations and by relationships in a tree, attaching external metadata, and working with MLST features. We can put this all together and do some basic visualiations of our selections on the tree (using the `ete3` toolkit)." ] }, { "cell_type": "markdown", "id": "cdea5a2f-8ee9-4b0c-834d-1154f35f4b84", "metadata": {}, "source": [ "## 6.1. Highlight everything in each outbreak and show a unique mutation/MLST feature" ] }, { "cell_type": "markdown", "id": "87c7ab38-c97a-420b-9afd-4d5759e3a814", "metadata": {}, "source": [ "### 6.1.1 Load tree and attach data frame" ] }, { "cell_type": "code", "execution_count": 55, "id": "808d4a81-ffcf-4ab4-950e-bf1be67eefe6", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 55, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q = db.samples_query(universe='mutations', reference_name='NC_011083')\\\n", " .join(metadata_df, sample_names_column='Sample Name Orig')\n", "q" ] }, { "cell_type": "markdown", "id": "b770d920-7140-4cf9-89e2-38b197e00abc", "metadata": {}, "source": [ "### 6.1.2 Select samples in outbreak 1 and show mutations" ] }, { "cell_type": "code", "execution_count": 56, "id": "840e2293-0ee8-47f1-88d2-f43268cf786b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 56, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q_o1 = q.isa('1', isa_column='outbreak_number', kind='dataframe')\n", "q_o1" ] }, { "cell_type": "code", "execution_count": 57, "id": "fb551eb2-30a5-46ee-8cf1-be33fa4dff95", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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SequencePositionDeletionInsertionTypeCountUnknown CountPresent and Unknown CountTotalPercent...Annotation_ImpactGene_NameGene_IDFeature_TypeTranscript_BioTypeHGVS.cHGVS.pID_HGVS.cID_HGVS.pID_HGVS_GN.c
ID_HGVS_GN.p
hgvs_gn:NC_011083.1:pqiA:p.Q219QNC_011083.11159308GASNP10<NA><NA>10100.0...LOWpqiASEHA_RS06145transcriptprotein_codingc.657G>Ap.Q219Qhgvs:NC_011083.1:SEHA_RS06145:c.657G>Ahgvs:NC_011083.1:SEHA_RS06145:p.Q219Qhgvs_gn:NC_011083.1:pqiA:c.657G>A
hgvs_gn:NC_011083.1:ychF:p.I128VNC_011083.11930007AGSNP10<NA><NA>10100.0...MODERATEychFSEHA_RS10040transcriptprotein_codingc.382A>Gp.I128Vhgvs:NC_011083.1:SEHA_RS10040:c.382A>Ghgvs:NC_011083.1:SEHA_RS10040:p.I128Vhgvs_gn:NC_011083.1:ychF:c.382A>G
<NA>NC_011083.12732743GASNP10<NA><NA>10100.0...MODIFIERsseB-pepBSEHA_RS13890-SEHA_RS13895intergenic_region<NA>n.2732743G>A<NA>hgvs:NC_011083.1:n.2732743G>A<NA>hgvs_gn:NC_011083.1:n.2732743G>A
hgvs_gn:NC_011083.1:SEHA_RS00825:p.I23FNC_011083.158804TASNP10<NA><NA>10100.0...MODERATESEHA_RS00825SEHA_RS00825transcriptprotein_codingc.67A>Tp.I23Fhgvs:NC_011083.1:SEHA_RS00825:c.67A>Thgvs:NC_011083.1:SEHA_RS00825:p.I23Fhgvs_gn:NC_011083.1:SEHA_RS00825:c.67A>T
<NA>NC_011083.1349640AGSNP10<NA><NA>10100.0...MODIFIERistB-tcfASEHA_RS26020-SEHA_RS02145intergenic_region<NA>n.349640A>G<NA>hgvs:NC_011083.1:n.349640A>G<NA>hgvs_gn:NC_011083.1:n.349640A>G
hgvs_gn:NC_011083.1:SEHA_RS22485:p.S224SNC_011083.14548496CTSNP10<NA><NA>10100.0...LOWSEHA_RS22485SEHA_RS22485transcriptprotein_codingc.672C>Tp.S224Shgvs:NC_011083.1:SEHA_RS22485:c.672C>Thgvs:NC_011083.1:SEHA_RS22485:p.S224Shgvs_gn:NC_011083.1:SEHA_RS22485:c.672C>T
hgvs_gn:NC_011083.1:SEHA_RS08400:p.P5PNC_011083.11582551CASNP10<NA><NA>10100.0...LOWSEHA_RS08400SEHA_RS08400transcriptprotein_codingc.15G>Tp.P5Phgvs:NC_011083.1:SEHA_RS08400:c.15G>Thgvs:NC_011083.1:SEHA_RS08400:p.P5Phgvs_gn:NC_011083.1:SEHA_RS08400:c.15G>T
<NA>NC_011083.11572779CTTCAGCGCAACGCGGCTGTAAGCATTGCTGCTAAAAAGAGGCCGG...CINDEL4<NA><NA>1040.0...HIGHgstA&pdxYSEHA_RS08355&SEHA_RS08350gene_variant<NA>n.1572780_1572862delTTCAGCGCAACGCGGCTGTAAGCATT...<NA>hgvs:NC_011083.1:n.1572780_1572862delTTCAGCGCA...<NA>hgvs_gn:NC_011083.1:n.1572780_1572862delTTCAGC...
\n", "

8 rows × 23 columns

\n", "
" ], "text/plain": [ " Sequence Position \\\n", "ID_HGVS_GN.p \n", "hgvs_gn:NC_011083.1:pqiA:p.Q219Q NC_011083.1 1159308 \n", "hgvs_gn:NC_011083.1:ychF:p.I128V NC_011083.1 1930007 \n", " NC_011083.1 2732743 \n", "hgvs_gn:NC_011083.1:SEHA_RS00825:p.I23F NC_011083.1 58804 \n", " NC_011083.1 349640 \n", "hgvs_gn:NC_011083.1:SEHA_RS22485:p.S224S NC_011083.1 4548496 \n", "hgvs_gn:NC_011083.1:SEHA_RS08400:p.P5P NC_011083.1 1582551 \n", " NC_011083.1 1572779 \n", "\n", " Deletion \\\n", "ID_HGVS_GN.p \n", "hgvs_gn:NC_011083.1:pqiA:p.Q219Q G \n", "hgvs_gn:NC_011083.1:ychF:p.I128V A \n", " G \n", "hgvs_gn:NC_011083.1:SEHA_RS00825:p.I23F T \n", " A \n", "hgvs_gn:NC_011083.1:SEHA_RS22485:p.S224S C \n", "hgvs_gn:NC_011083.1:SEHA_RS08400:p.P5P C \n", " CTTCAGCGCAACGCGGCTGTAAGCATTGCTGCTAAAAAGAGGCCGG... \n", "\n", " Insertion Type Count \\\n", "ID_HGVS_GN.p \n", "hgvs_gn:NC_011083.1:pqiA:p.Q219Q A SNP 10 \n", "hgvs_gn:NC_011083.1:ychF:p.I128V G SNP 10 \n", " A SNP 10 \n", "hgvs_gn:NC_011083.1:SEHA_RS00825:p.I23F A SNP 10 \n", " G SNP 10 \n", "hgvs_gn:NC_011083.1:SEHA_RS22485:p.S224S T SNP 10 \n", "hgvs_gn:NC_011083.1:SEHA_RS08400:p.P5P A SNP 10 \n", " C INDEL 4 \n", "\n", " Unknown Count \\\n", "ID_HGVS_GN.p \n", "hgvs_gn:NC_011083.1:pqiA:p.Q219Q \n", "hgvs_gn:NC_011083.1:ychF:p.I128V \n", " \n", "hgvs_gn:NC_011083.1:SEHA_RS00825:p.I23F \n", " \n", "hgvs_gn:NC_011083.1:SEHA_RS22485:p.S224S \n", "hgvs_gn:NC_011083.1:SEHA_RS08400:p.P5P \n", " \n", "\n", " Present and Unknown Count Total \\\n", "ID_HGVS_GN.p \n", "hgvs_gn:NC_011083.1:pqiA:p.Q219Q 10 \n", "hgvs_gn:NC_011083.1:ychF:p.I128V 10 \n", " 10 \n", "hgvs_gn:NC_011083.1:SEHA_RS00825:p.I23F 10 \n", " 10 \n", "hgvs_gn:NC_011083.1:SEHA_RS22485:p.S224S 10 \n", "hgvs_gn:NC_011083.1:SEHA_RS08400:p.P5P 10 \n", " 10 \n", "\n", " Percent ... Annotation_Impact \\\n", "ID_HGVS_GN.p ... \n", "hgvs_gn:NC_011083.1:pqiA:p.Q219Q 100.0 ... LOW \n", "hgvs_gn:NC_011083.1:ychF:p.I128V 100.0 ... MODERATE \n", " 100.0 ... MODIFIER \n", "hgvs_gn:NC_011083.1:SEHA_RS00825:p.I23F 100.0 ... MODERATE \n", " 100.0 ... MODIFIER \n", "hgvs_gn:NC_011083.1:SEHA_RS22485:p.S224S 100.0 ... LOW \n", "hgvs_gn:NC_011083.1:SEHA_RS08400:p.P5P 100.0 ... LOW \n", " 40.0 ... HIGH \n", "\n", " Gene_Name \\\n", "ID_HGVS_GN.p \n", "hgvs_gn:NC_011083.1:pqiA:p.Q219Q pqiA \n", "hgvs_gn:NC_011083.1:ychF:p.I128V ychF \n", " sseB-pepB \n", "hgvs_gn:NC_011083.1:SEHA_RS00825:p.I23F SEHA_RS00825 \n", " istB-tcfA \n", "hgvs_gn:NC_011083.1:SEHA_RS22485:p.S224S SEHA_RS22485 \n", "hgvs_gn:NC_011083.1:SEHA_RS08400:p.P5P SEHA_RS08400 \n", " gstA&pdxY \n", "\n", " Gene_ID \\\n", "ID_HGVS_GN.p \n", "hgvs_gn:NC_011083.1:pqiA:p.Q219Q SEHA_RS06145 \n", "hgvs_gn:NC_011083.1:ychF:p.I128V SEHA_RS10040 \n", " SEHA_RS13890-SEHA_RS13895 \n", "hgvs_gn:NC_011083.1:SEHA_RS00825:p.I23F SEHA_RS00825 \n", " SEHA_RS26020-SEHA_RS02145 \n", "hgvs_gn:NC_011083.1:SEHA_RS22485:p.S224S SEHA_RS22485 \n", "hgvs_gn:NC_011083.1:SEHA_RS08400:p.P5P SEHA_RS08400 \n", " SEHA_RS08355&SEHA_RS08350 \n", "\n", " Feature_Type \\\n", "ID_HGVS_GN.p \n", "hgvs_gn:NC_011083.1:pqiA:p.Q219Q transcript \n", "hgvs_gn:NC_011083.1:ychF:p.I128V transcript \n", " intergenic_region \n", "hgvs_gn:NC_011083.1:SEHA_RS00825:p.I23F transcript \n", " intergenic_region \n", "hgvs_gn:NC_011083.1:SEHA_RS22485:p.S224S transcript \n", "hgvs_gn:NC_011083.1:SEHA_RS08400:p.P5P transcript \n", " gene_variant \n", "\n", " Transcript_BioType \\\n", "ID_HGVS_GN.p \n", "hgvs_gn:NC_011083.1:pqiA:p.Q219Q protein_coding \n", "hgvs_gn:NC_011083.1:ychF:p.I128V protein_coding \n", " \n", "hgvs_gn:NC_011083.1:SEHA_RS00825:p.I23F protein_coding \n", " \n", "hgvs_gn:NC_011083.1:SEHA_RS22485:p.S224S protein_coding \n", "hgvs_gn:NC_011083.1:SEHA_RS08400:p.P5P protein_coding \n", " \n", "\n", " HGVS.c \\\n", "ID_HGVS_GN.p \n", "hgvs_gn:NC_011083.1:pqiA:p.Q219Q c.657G>A \n", "hgvs_gn:NC_011083.1:ychF:p.I128V c.382A>G \n", " n.2732743G>A \n", "hgvs_gn:NC_011083.1:SEHA_RS00825:p.I23F c.67A>T \n", " n.349640A>G \n", "hgvs_gn:NC_011083.1:SEHA_RS22485:p.S224S c.672C>T \n", "hgvs_gn:NC_011083.1:SEHA_RS08400:p.P5P c.15G>T \n", " n.1572780_1572862delTTCAGCGCAACGCGGCTGTAAGCATT... \n", "\n", " HGVS.p \\\n", "ID_HGVS_GN.p \n", "hgvs_gn:NC_011083.1:pqiA:p.Q219Q p.Q219Q \n", "hgvs_gn:NC_011083.1:ychF:p.I128V p.I128V \n", " \n", "hgvs_gn:NC_011083.1:SEHA_RS00825:p.I23F p.I23F \n", " \n", "hgvs_gn:NC_011083.1:SEHA_RS22485:p.S224S p.S224S \n", "hgvs_gn:NC_011083.1:SEHA_RS08400:p.P5P p.P5P \n", " \n", "\n", " ID_HGVS.c \\\n", "ID_HGVS_GN.p \n", "hgvs_gn:NC_011083.1:pqiA:p.Q219Q hgvs:NC_011083.1:SEHA_RS06145:c.657G>A \n", "hgvs_gn:NC_011083.1:ychF:p.I128V hgvs:NC_011083.1:SEHA_RS10040:c.382A>G \n", " hgvs:NC_011083.1:n.2732743G>A \n", "hgvs_gn:NC_011083.1:SEHA_RS00825:p.I23F hgvs:NC_011083.1:SEHA_RS00825:c.67A>T \n", " hgvs:NC_011083.1:n.349640A>G \n", "hgvs_gn:NC_011083.1:SEHA_RS22485:p.S224S hgvs:NC_011083.1:SEHA_RS22485:c.672C>T \n", "hgvs_gn:NC_011083.1:SEHA_RS08400:p.P5P hgvs:NC_011083.1:SEHA_RS08400:c.15G>T \n", " hgvs:NC_011083.1:n.1572780_1572862delTTCAGCGCA... \n", "\n", " ID_HGVS.p \\\n", "ID_HGVS_GN.p \n", "hgvs_gn:NC_011083.1:pqiA:p.Q219Q hgvs:NC_011083.1:SEHA_RS06145:p.Q219Q \n", "hgvs_gn:NC_011083.1:ychF:p.I128V hgvs:NC_011083.1:SEHA_RS10040:p.I128V \n", " \n", "hgvs_gn:NC_011083.1:SEHA_RS00825:p.I23F hgvs:NC_011083.1:SEHA_RS00825:p.I23F \n", " \n", "hgvs_gn:NC_011083.1:SEHA_RS22485:p.S224S hgvs:NC_011083.1:SEHA_RS22485:p.S224S \n", "hgvs_gn:NC_011083.1:SEHA_RS08400:p.P5P hgvs:NC_011083.1:SEHA_RS08400:p.P5P \n", " \n", "\n", " ID_HGVS_GN.c \n", "ID_HGVS_GN.p \n", "hgvs_gn:NC_011083.1:pqiA:p.Q219Q hgvs_gn:NC_011083.1:pqiA:c.657G>A \n", "hgvs_gn:NC_011083.1:ychF:p.I128V hgvs_gn:NC_011083.1:ychF:c.382A>G \n", " hgvs_gn:NC_011083.1:n.2732743G>A \n", "hgvs_gn:NC_011083.1:SEHA_RS00825:p.I23F hgvs_gn:NC_011083.1:SEHA_RS00825:c.67A>T \n", " hgvs_gn:NC_011083.1:n.349640A>G \n", "hgvs_gn:NC_011083.1:SEHA_RS22485:p.S224S hgvs_gn:NC_011083.1:SEHA_RS22485:c.672C>T \n", "hgvs_gn:NC_011083.1:SEHA_RS08400:p.P5P hgvs_gn:NC_011083.1:SEHA_RS08400:c.15G>T \n", " hgvs_gn:NC_011083.1:n.1572780_1572862delTTCAGC... \n", "\n", "[8 rows x 23 columns]" ] }, "execution_count": 57, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q_o1.features_summary(selection='unique').sort_values('Count', ascending=False).set_index('ID_HGVS_GN.p').head(8)" ] }, { "cell_type": "markdown", "id": "334e2848-3f25-4aa3-bf47-2a2b94d6d900", "metadata": { "tags": [] }, "source": [ "Passing `selection='unique'` will select only those mutations that are unique to the selected set (useful for searching for lineage-defining mutations or mutations in subsets of the selected samples).\n", "\n", "Let's pick one of the lineage-defining mutations (i.e., a mutation uniquely found in only **Outbreak 1**). We can detect these by using `selection='unique'` and filtering to mutations where `Count` is equal to `Total` (count of samples with mutation equals total samples in selection)." ] }, { "cell_type": "code", "execution_count": 58, "id": "5f3fb9a6-84fa-48d9-ab18-505d01f51ca2", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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SequencePositionDeletionInsertionTypeCountUnknown CountPresent and Unknown CountTotalPercent...Annotation_ImpactGene_NameGene_IDFeature_TypeTranscript_BioTypeHGVS.cHGVS.pID_HGVS.cID_HGVS_GN.cID_HGVS_GN.p
ID_HGVS.p
hgvs:NC_011083.1:SEHA_RS00825:p.I23FNC_011083.158804TASNP10<NA><NA>10100.0...MODERATESEHA_RS00825SEHA_RS00825transcriptprotein_codingc.67A>Tp.I23Fhgvs:NC_011083.1:SEHA_RS00825:c.67A>Thgvs_gn:NC_011083.1:SEHA_RS00825:c.67A>Thgvs_gn:NC_011083.1:SEHA_RS00825:p.I23F
<NA>NC_011083.1349640AGSNP10<NA><NA>10100.0...MODIFIERistB-tcfASEHA_RS26020-SEHA_RS02145intergenic_region<NA>n.349640A>G<NA>hgvs:NC_011083.1:n.349640A>Ghgvs_gn:NC_011083.1:n.349640A>G<NA>
hgvs:NC_011083.1:SEHA_RS06145:p.Q219QNC_011083.11159308GASNP10<NA><NA>10100.0...LOWpqiASEHA_RS06145transcriptprotein_codingc.657G>Ap.Q219Qhgvs:NC_011083.1:SEHA_RS06145:c.657G>Ahgvs_gn:NC_011083.1:pqiA:c.657G>Ahgvs_gn:NC_011083.1:pqiA:p.Q219Q
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3 rows × 23 columns

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" ], "text/plain": [ " Sequence Position Deletion \\\n", "ID_HGVS.p \n", "hgvs:NC_011083.1:SEHA_RS00825:p.I23F NC_011083.1 58804 T \n", " NC_011083.1 349640 A \n", "hgvs:NC_011083.1:SEHA_RS06145:p.Q219Q NC_011083.1 1159308 G \n", "\n", " Insertion Type Count Unknown Count \\\n", "ID_HGVS.p \n", "hgvs:NC_011083.1:SEHA_RS00825:p.I23F A SNP 10 \n", " G SNP 10 \n", "hgvs:NC_011083.1:SEHA_RS06145:p.Q219Q A SNP 10 \n", "\n", " Present and Unknown Count Total \\\n", "ID_HGVS.p \n", "hgvs:NC_011083.1:SEHA_RS00825:p.I23F 10 \n", " 10 \n", "hgvs:NC_011083.1:SEHA_RS06145:p.Q219Q 10 \n", "\n", " Percent ... Annotation_Impact \\\n", "ID_HGVS.p ... \n", "hgvs:NC_011083.1:SEHA_RS00825:p.I23F 100.0 ... MODERATE \n", " 100.0 ... MODIFIER \n", "hgvs:NC_011083.1:SEHA_RS06145:p.Q219Q 100.0 ... LOW \n", "\n", " Gene_Name \\\n", "ID_HGVS.p \n", "hgvs:NC_011083.1:SEHA_RS00825:p.I23F SEHA_RS00825 \n", " istB-tcfA \n", "hgvs:NC_011083.1:SEHA_RS06145:p.Q219Q pqiA \n", "\n", " Gene_ID \\\n", "ID_HGVS.p \n", "hgvs:NC_011083.1:SEHA_RS00825:p.I23F SEHA_RS00825 \n", " SEHA_RS26020-SEHA_RS02145 \n", "hgvs:NC_011083.1:SEHA_RS06145:p.Q219Q SEHA_RS06145 \n", "\n", " Feature_Type Transcript_BioType \\\n", "ID_HGVS.p \n", "hgvs:NC_011083.1:SEHA_RS00825:p.I23F transcript protein_coding \n", " intergenic_region \n", "hgvs:NC_011083.1:SEHA_RS06145:p.Q219Q transcript protein_coding \n", "\n", " HGVS.c HGVS.p \\\n", "ID_HGVS.p \n", "hgvs:NC_011083.1:SEHA_RS00825:p.I23F c.67A>T p.I23F \n", " n.349640A>G \n", "hgvs:NC_011083.1:SEHA_RS06145:p.Q219Q c.657G>A p.Q219Q \n", "\n", " ID_HGVS.c \\\n", "ID_HGVS.p \n", "hgvs:NC_011083.1:SEHA_RS00825:p.I23F hgvs:NC_011083.1:SEHA_RS00825:c.67A>T \n", " hgvs:NC_011083.1:n.349640A>G \n", "hgvs:NC_011083.1:SEHA_RS06145:p.Q219Q hgvs:NC_011083.1:SEHA_RS06145:c.657G>A \n", "\n", " ID_HGVS_GN.c \\\n", "ID_HGVS.p \n", "hgvs:NC_011083.1:SEHA_RS00825:p.I23F hgvs_gn:NC_011083.1:SEHA_RS00825:c.67A>T \n", " hgvs_gn:NC_011083.1:n.349640A>G \n", "hgvs:NC_011083.1:SEHA_RS06145:p.Q219Q hgvs_gn:NC_011083.1:pqiA:c.657G>A \n", "\n", " ID_HGVS_GN.p \n", "ID_HGVS.p \n", "hgvs:NC_011083.1:SEHA_RS00825:p.I23F hgvs_gn:NC_011083.1:SEHA_RS00825:p.I23F \n", " \n", "hgvs:NC_011083.1:SEHA_RS06145:p.Q219Q hgvs_gn:NC_011083.1:pqiA:p.Q219Q \n", "\n", "[3 rows x 23 columns]" ] }, "execution_count": 58, "metadata": {}, "output_type": "execute_result" } ], "source": [ "o1_df = q_o1.features_summary(selection='unique').sort_values(['Count', 'Position'])\n", "o1_df[o1_df['Count'] == o1_df['Total']].set_index('ID_HGVS.p').head(3)" ] }, { "cell_type": "markdown", "id": "c04f73b8-1ad0-4860-b99e-0ec80b88f13f", "metadata": {}, "source": [ "We will highlight `hgvs:NC_011083.1:SEHA_RS00825:p.I23F` (`NC_011083.1:58804:T:A`) in the tree.\n", "\n", "Let's also select a unique MLST feature to highlight." ] }, { "cell_type": "markdown", "id": "1a6d8c60-794d-4104-8122-d207c85d935b", "metadata": {}, "source": [ "### 6.1.3. Select unique MLST features" ] }, { "cell_type": "code", "execution_count": 59, "id": "e0cc326c-35f6-40dd-9c25-88a9048d7257", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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SchemeLocusAlleleCountUnknown CountPresent and Unknown CountTotalPercentUnknown PercentPresent and Unknown Percent
MLST Feature
mlst:sistr_330:NZ_AOXE01000047.1_56:1179310307sistr_330NZ_AOXE01000047.1_5611793103072<NA><NA>1020.0<NA><NA>
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" ], "text/plain": [ " Scheme \\\n", "MLST Feature \n", "mlst:sistr_330:NZ_AOXE01000047.1_56:1179310307 sistr_330 \n", "\n", " Locus \\\n", "MLST Feature \n", "mlst:sistr_330:NZ_AOXE01000047.1_56:1179310307 NZ_AOXE01000047.1_56 \n", "\n", " Allele Count \\\n", "MLST Feature \n", "mlst:sistr_330:NZ_AOXE01000047.1_56:1179310307 1179310307 2 \n", "\n", " Unknown Count \\\n", "MLST Feature \n", "mlst:sistr_330:NZ_AOXE01000047.1_56:1179310307 \n", "\n", " Present and Unknown Count \\\n", "MLST Feature \n", "mlst:sistr_330:NZ_AOXE01000047.1_56:1179310307 \n", "\n", " Total Percent \\\n", "MLST Feature \n", "mlst:sistr_330:NZ_AOXE01000047.1_56:1179310307 10 20.0 \n", "\n", " Unknown Percent \\\n", "MLST Feature \n", "mlst:sistr_330:NZ_AOXE01000047.1_56:1179310307 \n", "\n", " Present and Unknown Percent \n", "MLST Feature \n", "mlst:sistr_330:NZ_AOXE01000047.1_56:1179310307 " ] }, "execution_count": 59, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q_o1.features_summary(kind='mlst', scheme='sistr_330',\n", " selection='unique').sort_values('Count', ascending=False)" ] }, { "cell_type": "markdown", "id": "8aede145-e09f-459a-8599-d2a76acb33b6", "metadata": {}, "source": [ "Here, we can see there's only one MLST feature to pick `mlst:sistr_330:NZ_AOXE01000047.1_56:1179310307` that's unique to **Outbreak 1** (but not unique to every sample in the outbreak). We will show this feature on the tree too." ] }, { "cell_type": "markdown", "id": "6a0612cb-c7e3-4b08-85da-d80c19499fb4", "metadata": {}, "source": [ "### 6.1.4 Highlight samples in **Outbreak 1** and display those with a particular mutation/MLST feature" ] }, { "cell_type": "code", "execution_count": 60, "id": "da47b564-e767-4a70-84b3-a1202ef9141f", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "execution_count": 60, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Use `highlight()` to highlight Outbreak 1\n", "# Chain with other `highlight()` methods to highlight other outbreak samples\n", "# Use `annotate()` to add a column indicating the presence/absence of '58804:T:A' mutation\n", "# Use another `annotate()` to add a column indicating the presence/absence of the MLST feature\n", "# Use `highlight_style` to change the color scheme of the highlights\n", "ts = q.tree_styler(annotate_show_box_label=True, legend_nsize=30, legend_fsize=14,\n", " show_legend_type_labels=False, legend_title='Legend')\\\n", " .highlight(q_o1, legend_label='Outbreak 1')\\\n", " .highlight(q.isa('2', isa_column='outbreak_number', kind='dataframe'), legend_label='Outbreak 2')\\\n", " .highlight(q.isa('3', isa_column='outbreak_number', kind='dataframe'), legend_label='Outbreak 3')\\\n", " .annotate(q.hasa('hgvs:NC_011083.1:SEHA_RS00825:p.I23F'), box_label='SEHA_RS00825:I23F')\\\n", " .annotate(q.hasa('mlst:sistr_330:NZ_AOXE01000047.1_56:1179310307'), box_label='mlst:1179310307')\n", "ts.render(w=600)" ] }, { "cell_type": "markdown", "id": "57315059-a889-4d6a-9d6f-2452b6b5372d", "metadata": {}, "source": [ "This shows the " ] }, { "cell_type": "markdown", "id": "cbb1c89b-4453-4534-ae88-f241e0333bdd", "metadata": {}, "source": [ "### 6.1.5: Save the output to a file" ] }, { "cell_type": "code", "execution_count": 61, "id": "b8558edc-1bac-43ec-a5dc-a0cfc196eb72", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Saved to output1.pdf\n" ] } ], "source": [ "# Save this to a PDF file\n", "file = 'output1.pdf'\n", "x = ts.render(file)\n", "print(f'Saved to {file}')\n", "# (I assign to x to surpress printing text when saving in Jupyter)" ] }, { "cell_type": "markdown", "id": "2b92246d-29eb-40b2-8371-8fd2d5e15b07", "metadata": {}, "source": [ "## 6.2: Working with mutations table\n", "\n", "### 6.2.1 Get mutations for all samples with Outbreak number `2`" ] }, { "cell_type": "code", "execution_count": 62, "id": "f6f2434a-8fa4-4d64-bae7-26dc5b56c5ab", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 62, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q = db.samples_query().join(metadata_df, sample_names_column='Sample Name Orig',\n", " default_isa_column='outbreak_number', default_isa_kind='dataframe')\n", "q.isa('2')" ] }, { "cell_type": "code", "execution_count": 63, "id": "201722a5-92c4-4b79-b33f-87f02fc6e09e", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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SequencePositionDeletionInsertionTypeCountUnknown CountPresent and Unknown CountTotalPercent...Gene_NameGene_IDFeature_TypeTranscript_BioTypeHGVS.cHGVS.pID_HGVS.cID_HGVS.pID_HGVS_GN.cID_HGVS_GN.p
Mutation
NC_011083.1:1947794:A:GNC_011083.11947794AGSNP8NaNNaN8100.0...SEHA_RS10125SEHA_RS10125transcriptprotein_codingc.181A>Gp.T61Ahgvs:NC_011083.1:SEHA_RS10125:c.181A>Ghgvs:NC_011083.1:SEHA_RS10125:p.T61Ahgvs_gn:NC_011083.1:SEHA_RS10125:c.181A>Ghgvs_gn:NC_011083.1:SEHA_RS10125:p.T61A
NC_011083.1:3945452:G:CNC_011083.13945452GCSNP8NaNNaN8100.0...ligBSEHA_RS19715transcriptprotein_codingc.400C>Gp.L134Vhgvs:NC_011083.1:SEHA_RS19715:c.400C>Ghgvs:NC_011083.1:SEHA_RS19715:p.L134Vhgvs_gn:NC_011083.1:ligB:c.400C>Ghgvs_gn:NC_011083.1:ligB:p.L134V
NC_011083.1:602044:T:GNC_011083.1602044TGSNP8NaNNaN8100.0...SEHA_RS03410SEHA_RS03410transcriptprotein_codingc.1163T>Gp.V388Ghgvs:NC_011083.1:SEHA_RS03410:c.1163T>Ghgvs:NC_011083.1:SEHA_RS03410:p.V388Ghgvs_gn:NC_011083.1:SEHA_RS03410:c.1163T>Ghgvs_gn:NC_011083.1:SEHA_RS03410:p.V388G
NC_011083.1:2209731:A:CNC_011083.12209731ACSNP8NaNNaN8100.0...SEHA_RS11560SEHA_RS11560transcriptprotein_codingc.250T>Gp.W84Ghgvs:NC_011083.1:SEHA_RS11560:c.250T>Ghgvs:NC_011083.1:SEHA_RS11560:p.W84Ghgvs_gn:NC_011083.1:SEHA_RS11560:c.250T>Ghgvs_gn:NC_011083.1:SEHA_RS11560:p.W84G
NC_011083.1:2225479:G:TNC_011083.12225479GTSNP8NaNNaN8100.0...rfbBSEHA_RS11635transcriptprotein_codingc.721C>Ap.R241Shgvs:NC_011083.1:SEHA_RS11635:c.721C>Ahgvs:NC_011083.1:SEHA_RS11635:p.R241Shgvs_gn:NC_011083.1:rfbB:c.721C>Ahgvs_gn:NC_011083.1:rfbB:p.R241S
..................................................................
NC_011083.1:1514675:G:ANC_011083.11514675GASNP1NaNNaN812.5...purR-SEHA_RS08035SEHA_RS08030-SEHA_RS08035intergenic_region<NA>n.1514675G>A<NA>hgvs:NC_011083.1:n.1514675G>A<NA>hgvs_gn:NC_011083.1:n.1514675G>A<NA>
NC_011083.1:2010696:G:TNC_011083.12010696GTSNP1NaNNaN812.5...SEHA_RS25120-SEHA_RS10450SEHA_RS25120-SEHA_RS10450intergenic_region<NA>n.2010696G>T<NA>hgvs:NC_011083.1:n.2010696G>T<NA>hgvs_gn:NC_011083.1:n.2010696G>T<NA>
NC_011083.1:4800575:C:TNC_011083.14800575CTSNP1NaNNaN812.5...SEHA_RS23755-SEHA_RS23765SEHA_RS23755-SEHA_RS23765intergenic_region<NA>n.4800575C>T<NA>hgvs:NC_011083.1:n.4800575C>T<NA>hgvs_gn:NC_011083.1:n.4800575C>T<NA>
NC_011083.1:1310359:T:GNC_011083.11310359TGSNP1NaNNaN812.5...nagKSEHA_RS06940transcriptprotein_codingc.175T>Gp.S59Ahgvs:NC_011083.1:SEHA_RS06940:c.175T>Ghgvs:NC_011083.1:SEHA_RS06940:p.S59Ahgvs_gn:NC_011083.1:nagK:c.175T>Ghgvs_gn:NC_011083.1:nagK:p.S59A
NC_011083.1:1691486:G:CNC_011083.11691486GCSNP1NaNNaN812.5...SEHA_RS08920SEHA_RS08920transcriptprotein_codingc.781C>Gp.Q261Ehgvs:NC_011083.1:SEHA_RS08920:c.781C>Ghgvs:NC_011083.1:SEHA_RS08920:p.Q261Ehgvs_gn:NC_011083.1:SEHA_RS08920:c.781C>Ghgvs_gn:NC_011083.1:SEHA_RS08920:p.Q261E
\n", "

151 rows × 24 columns

\n", "
" ], "text/plain": [ " Sequence Position Deletion Insertion Type Count \\\n", "Mutation \n", "NC_011083.1:1947794:A:G NC_011083.1 1947794 A G SNP 8 \n", "NC_011083.1:3945452:G:C NC_011083.1 3945452 G C SNP 8 \n", "NC_011083.1:602044:T:G NC_011083.1 602044 T G SNP 8 \n", "NC_011083.1:2209731:A:C NC_011083.1 2209731 A C SNP 8 \n", "NC_011083.1:2225479:G:T NC_011083.1 2225479 G T SNP 8 \n", "... ... ... ... ... ... ... \n", "NC_011083.1:1514675:G:A NC_011083.1 1514675 G A SNP 1 \n", "NC_011083.1:2010696:G:T NC_011083.1 2010696 G T SNP 1 \n", "NC_011083.1:4800575:C:T NC_011083.1 4800575 C T SNP 1 \n", "NC_011083.1:1310359:T:G NC_011083.1 1310359 T G SNP 1 \n", "NC_011083.1:1691486:G:C NC_011083.1 1691486 G C SNP 1 \n", "\n", " Unknown Count Present and Unknown Count Total \\\n", "Mutation \n", "NC_011083.1:1947794:A:G NaN NaN 8 \n", "NC_011083.1:3945452:G:C NaN NaN 8 \n", "NC_011083.1:602044:T:G NaN NaN 8 \n", "NC_011083.1:2209731:A:C NaN NaN 8 \n", "NC_011083.1:2225479:G:T NaN NaN 8 \n", "... ... ... ... \n", "NC_011083.1:1514675:G:A NaN NaN 8 \n", "NC_011083.1:2010696:G:T NaN NaN 8 \n", "NC_011083.1:4800575:C:T NaN NaN 8 \n", "NC_011083.1:1310359:T:G NaN NaN 8 \n", "NC_011083.1:1691486:G:C NaN NaN 8 \n", "\n", " Percent ... Gene_Name \\\n", "Mutation ... \n", "NC_011083.1:1947794:A:G 100.0 ... SEHA_RS10125 \n", "NC_011083.1:3945452:G:C 100.0 ... ligB \n", "NC_011083.1:602044:T:G 100.0 ... SEHA_RS03410 \n", "NC_011083.1:2209731:A:C 100.0 ... SEHA_RS11560 \n", "NC_011083.1:2225479:G:T 100.0 ... rfbB \n", "... ... ... ... \n", "NC_011083.1:1514675:G:A 12.5 ... purR-SEHA_RS08035 \n", "NC_011083.1:2010696:G:T 12.5 ... SEHA_RS25120-SEHA_RS10450 \n", "NC_011083.1:4800575:C:T 12.5 ... SEHA_RS23755-SEHA_RS23765 \n", "NC_011083.1:1310359:T:G 12.5 ... nagK \n", "NC_011083.1:1691486:G:C 12.5 ... SEHA_RS08920 \n", "\n", " Gene_ID Feature_Type \\\n", "Mutation \n", "NC_011083.1:1947794:A:G SEHA_RS10125 transcript \n", "NC_011083.1:3945452:G:C SEHA_RS19715 transcript \n", "NC_011083.1:602044:T:G SEHA_RS03410 transcript \n", "NC_011083.1:2209731:A:C SEHA_RS11560 transcript \n", "NC_011083.1:2225479:G:T SEHA_RS11635 transcript \n", "... ... ... \n", "NC_011083.1:1514675:G:A SEHA_RS08030-SEHA_RS08035 intergenic_region \n", "NC_011083.1:2010696:G:T SEHA_RS25120-SEHA_RS10450 intergenic_region \n", "NC_011083.1:4800575:C:T SEHA_RS23755-SEHA_RS23765 intergenic_region \n", "NC_011083.1:1310359:T:G SEHA_RS06940 transcript \n", "NC_011083.1:1691486:G:C SEHA_RS08920 transcript \n", "\n", " Transcript_BioType HGVS.c HGVS.p \\\n", "Mutation \n", "NC_011083.1:1947794:A:G protein_coding c.181A>G p.T61A \n", "NC_011083.1:3945452:G:C protein_coding c.400C>G p.L134V \n", "NC_011083.1:602044:T:G protein_coding c.1163T>G p.V388G \n", "NC_011083.1:2209731:A:C protein_coding c.250T>G p.W84G \n", "NC_011083.1:2225479:G:T protein_coding c.721C>A p.R241S \n", "... ... ... ... \n", "NC_011083.1:1514675:G:A n.1514675G>A \n", "NC_011083.1:2010696:G:T n.2010696G>T \n", "NC_011083.1:4800575:C:T n.4800575C>T \n", "NC_011083.1:1310359:T:G protein_coding c.175T>G p.S59A \n", "NC_011083.1:1691486:G:C protein_coding c.781C>G p.Q261E \n", "\n", " ID_HGVS.c \\\n", "Mutation \n", "NC_011083.1:1947794:A:G hgvs:NC_011083.1:SEHA_RS10125:c.181A>G \n", "NC_011083.1:3945452:G:C hgvs:NC_011083.1:SEHA_RS19715:c.400C>G \n", "NC_011083.1:602044:T:G hgvs:NC_011083.1:SEHA_RS03410:c.1163T>G \n", "NC_011083.1:2209731:A:C hgvs:NC_011083.1:SEHA_RS11560:c.250T>G \n", "NC_011083.1:2225479:G:T hgvs:NC_011083.1:SEHA_RS11635:c.721C>A \n", "... ... \n", "NC_011083.1:1514675:G:A hgvs:NC_011083.1:n.1514675G>A \n", "NC_011083.1:2010696:G:T hgvs:NC_011083.1:n.2010696G>T \n", "NC_011083.1:4800575:C:T hgvs:NC_011083.1:n.4800575C>T \n", "NC_011083.1:1310359:T:G hgvs:NC_011083.1:SEHA_RS06940:c.175T>G \n", "NC_011083.1:1691486:G:C hgvs:NC_011083.1:SEHA_RS08920:c.781C>G \n", "\n", " ID_HGVS.p \\\n", "Mutation \n", "NC_011083.1:1947794:A:G hgvs:NC_011083.1:SEHA_RS10125:p.T61A \n", "NC_011083.1:3945452:G:C hgvs:NC_011083.1:SEHA_RS19715:p.L134V \n", "NC_011083.1:602044:T:G hgvs:NC_011083.1:SEHA_RS03410:p.V388G \n", "NC_011083.1:2209731:A:C hgvs:NC_011083.1:SEHA_RS11560:p.W84G \n", "NC_011083.1:2225479:G:T hgvs:NC_011083.1:SEHA_RS11635:p.R241S \n", "... ... \n", "NC_011083.1:1514675:G:A \n", "NC_011083.1:2010696:G:T \n", "NC_011083.1:4800575:C:T \n", "NC_011083.1:1310359:T:G hgvs:NC_011083.1:SEHA_RS06940:p.S59A \n", "NC_011083.1:1691486:G:C hgvs:NC_011083.1:SEHA_RS08920:p.Q261E \n", "\n", " ID_HGVS_GN.c \\\n", "Mutation \n", "NC_011083.1:1947794:A:G hgvs_gn:NC_011083.1:SEHA_RS10125:c.181A>G \n", "NC_011083.1:3945452:G:C hgvs_gn:NC_011083.1:ligB:c.400C>G \n", "NC_011083.1:602044:T:G hgvs_gn:NC_011083.1:SEHA_RS03410:c.1163T>G \n", "NC_011083.1:2209731:A:C hgvs_gn:NC_011083.1:SEHA_RS11560:c.250T>G \n", "NC_011083.1:2225479:G:T hgvs_gn:NC_011083.1:rfbB:c.721C>A \n", "... ... \n", "NC_011083.1:1514675:G:A hgvs_gn:NC_011083.1:n.1514675G>A \n", "NC_011083.1:2010696:G:T hgvs_gn:NC_011083.1:n.2010696G>T \n", "NC_011083.1:4800575:C:T hgvs_gn:NC_011083.1:n.4800575C>T \n", "NC_011083.1:1310359:T:G hgvs_gn:NC_011083.1:nagK:c.175T>G \n", "NC_011083.1:1691486:G:C hgvs_gn:NC_011083.1:SEHA_RS08920:c.781C>G \n", "\n", " ID_HGVS_GN.p \n", "Mutation \n", "NC_011083.1:1947794:A:G hgvs_gn:NC_011083.1:SEHA_RS10125:p.T61A \n", "NC_011083.1:3945452:G:C hgvs_gn:NC_011083.1:ligB:p.L134V \n", "NC_011083.1:602044:T:G hgvs_gn:NC_011083.1:SEHA_RS03410:p.V388G \n", "NC_011083.1:2209731:A:C hgvs_gn:NC_011083.1:SEHA_RS11560:p.W84G \n", "NC_011083.1:2225479:G:T hgvs_gn:NC_011083.1:rfbB:p.R241S \n", "... ... \n", "NC_011083.1:1514675:G:A \n", "NC_011083.1:2010696:G:T \n", "NC_011083.1:4800575:C:T \n", "NC_011083.1:1310359:T:G hgvs_gn:NC_011083.1:nagK:p.S59A \n", "NC_011083.1:1691486:G:C hgvs_gn:NC_011083.1:SEHA_RS08920:p.Q261E \n", "\n", "[151 rows x 24 columns]" ] }, "execution_count": 63, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q.isa('2').features_summary().sort_values('Count', ascending=False)" ] }, { "cell_type": "markdown", "id": "2f714534-dabe-4aba-aba1-a55d35a6a462", "metadata": {}, "source": [ "### 6.2.2 Plot distribution of mutations on genome for outbreak `2`" ] }, { "cell_type": "code", "execution_count": 64, "id": "5a70ea60-803d-473d-94e2-a8daec3894aa", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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PositionCount
Position
70519705197
1406581406588
2032002032008
2316652316658
2726732726738
.........
486064148606418
487617648761768
488209948820998
488490948849098
488814048881408
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150 rows × 2 columns

\n", "
" ], "text/plain": [ " Position Count\n", "Position \n", "70519 70519 7\n", "140658 140658 8\n", "203200 203200 8\n", "231665 231665 8\n", "272673 272673 8\n", "... ... ...\n", "4860641 4860641 8\n", "4876176 4876176 8\n", "4882099 4882099 8\n", "4884909 4884909 8\n", "4888140 4888140 8\n", "\n", "[150 rows x 2 columns]" ] }, "execution_count": 64, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q_o2_positions = q.isa('2').features_summary()\\\n", " .groupby('Position')\\\n", " .agg({'Position': 'first', 'Count': 'sum'})\n", "q_o2_positions" ] }, { "cell_type": "code", "execution_count": 65, "id": "4e79b187-02bf-41a1-908c-050818fbe461", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0, 0.5, 'Count of mutation positions')" ] }, "execution_count": 65, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "\n", "reference_genome = db.reference_names()[0]\n", "\n", "# I'm just showing a histogram of positions, I'm ignoring sample counts\n", "q_o2_positions['Position'].hist(bins=100)\n", "\n", "plt.title('Distribution of mutations for Outbreak 2', fontdict={'size': 16})\n", "plt.xlabel(f'Position on {reference_genome} (bp)', fontdict={'size': 14})\n", "plt.ylabel('Count of mutation positions', fontdict={'size': 14})" ] }, { "cell_type": "markdown", "id": "016e0052-6bf4-4a6f-9a37-f3e8538b3558", "metadata": {}, "source": [ "### 6.2.3 Compare to distribution of mutations in outbreak 1 and 3\n", "\n", "We'll compare to outbreak 1 and 3 using the same histogram." ] }, { "cell_type": "code", "execution_count": 66, "id": "eaabf33b-db79-4711-bff8-d229326282ee", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " Position Count\n", "Position \n", "58804 58804 10\n", "63393 63393 10\n", "71448 71448 10\n", "140658 140658 10\n", "203200 203200 10\n", "... ... ...\n", "4860641 4860641 10\n", "4876176 4876176 10\n", "4882099 4882099 10\n", "4884909 4884909 10\n", "4888140 4888140 10\n", "\n", "[137 rows x 2 columns]" ] }, "execution_count": 66, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q_o1_positions = q.isa('1').features_summary()\\\n", " .groupby('Position')\\\n", " .agg({'Position': 'first', 'Count': 'sum'})\n", "q_o1_positions" ] }, { "cell_type": "code", "execution_count": 67, "id": "6f3ddc10-5d51-4067-90c5-1f7f3df01b09", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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149 rows × 2 columns

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" ], "text/plain": [ " Position Count\n", "Position \n", "140658 140658 28\n", "203200 203200 28\n", "231665 231665 28\n", "298472 298472 28\n", "298943 298943 26\n", "... ... ...\n", "4860641 4860641 28\n", "4876176 4876176 28\n", "4882099 4882099 28\n", "4884909 4884909 28\n", "4888140 4888140 28\n", "\n", "[149 rows x 2 columns]" ] }, "execution_count": 67, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q_o3_positions = q.isa('3').features_summary()\\\n", " .groupby('Position')\\\n", " .agg({'Position': 'first', 'Count': 'sum'})\n", "q_o3_positions" ] }, { "cell_type": "code", "execution_count": 68, "id": "a3ffae8e-e67e-45d2-99c9-5c18a4ae8c45", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0, 0.5, 'Count of mutation positions')" ] }, "execution_count": 68, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "o1_positions_list = q_o1_positions['Position'].tolist()\n", "o2_positions_list = q_o2_positions['Position'].tolist()\n", "o3_positions_list = q_o3_positions['Position'].tolist()\n", "data = [o1_positions_list, o2_positions_list, o3_positions_list]\n", "labels = ['Outbreak 1', 'Outbreak 2', 'Outbreak 3']\n", "colors = ['#a6cee3', '#1f78b4', '#b2df8a']\n", "\n", "# Create histogram\n", "plt.figure(figsize=(15,6))\n", "plt.hist(data,\n", " label=labels, color=colors, edgecolor='black',\n", " bins=25)\n", "\n", "plt.legend(prop={'size': 14})\n", "plt.title('Distribution of mutations for Outbreaks 1,2, and 3', fontdict={'size': 16})\n", "plt.xlabel(f'Position on {reference_genome} (bp)', fontdict={'size': 14})\n", "plt.ylabel('Count of mutation positions', fontdict={'size': 14})" ] }, { "cell_type": "markdown", "id": "ff2cc2b1-75c7-4948-9372-2926516f79de", "metadata": {}, "source": [ "### 6.2.4 (Optional) View distribution of only unique mutations in each outbreak\n", "\n", "Try replacing `features_summary()` with `features_summary(selection='unique')`. This will change the plot from a distribution of all mutations in each outbreak to only a distribution of the mutations uniquely found in each outbreak." ] }, { "cell_type": "markdown", "id": "e888112a-975c-4b3f-a14d-691f53c05d13", "metadata": {}, "source": [ "# 6. End\n", "\n", "You've made it to the end. You are amazing 😀🥳. Way to go. I hope you enjoyed the tutorial." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.15" } }, "nbformat": 4, "nbformat_minor": 5 }