{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# scram demonstration" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "- Using the [scram_docker container](https://hub.docker.com/r/sfletcher/scram_docker/)\n", "- Notebook started in the project root directory via (Windows):\n", "```\n", "docker run -it --rm -v ${PWD}:/work -p 8888:8888 sfletcher/scram_docker\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Set up the Jupyter environment (optional)" ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "collapsed": true, "scrolled": true }, "outputs": [], "source": [ "%matplotlib inline\n", "#To display pandas dataframes inline\n", "from IPython.core.interactiveshell import InteractiveShell\n", "InteractiveShell.ast_node_interactivity = \"all\"\n", "import pandas" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Example file and directory structure on the host" ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ ".\r\n", "├── license\r\n", "├── out_dir\r\n", "├── ref\r\n", "│   ├── GFP.fa\r\n", "│   ├── TAIR10_transposable_elements.fa\r\n", "│   └── ath_mir.fa\r\n", "├── scram_demonstration.ipynb\r\n", "└── seq\r\n", " ├── treatment_a_rep1.fa\r\n", " ├── treatment_a_rep2.fa\r\n", " ├── treatment_a_rep3.fa\r\n", " ├── treatment_b_rep1.fa\r\n", " ├── treatment_b_rep2.fa\r\n", " └── treatment_b_rep3.fa\r\n", "\r\n", "3 directories, 11 files\r\n" ] } ], "source": [ "! tree" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### scram help\n", "- The scram aligner is in the container path\n", "- In Jupyter notebook, use the ! symbol to run a non-Python CLI app" ] }, { "cell_type": "code", "execution_count": 32, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Fast and simple small RNA read alignment v0.2.0\r\n", "\r\n", "Usage:\r\n", " scram [command]\r\n", "\r\n", "Available Commands:\r\n", " compare Compare normalised alignment counts and standard errors for 2 read file sets\r\n", " help Help about any command\r\n", " profile Align reads of length l from 1 read file set to all sequences in a reference file\r\n", "\r\n", "Flags:\r\n", " --adapter string 3' adapter sequence to trim - FASTA & FASTQ only (default \"nil\")\r\n", " -r, --alignTo string path/to/FASTA reference file\r\n", " -1, --fastxSet1 string comma-separated path/to/read file set 1. GZIPped files must have .gz file extension\r\n", " -h, --help help for scram\r\n", " -l, --length string comma-separated read (sRNA) lengths to align\r\n", " --maxLen int Maximum read length to include for RPMR normalization (default 32)\r\n", " --minCount float Minimum read count for alignment and to include for RPMR normalization (default 1)\r\n", " --minLen int Minimum read length to include for RPMR normalization (default 18)\r\n", " --noNorm Do not normalize read counts by library size (i.e. reads per million reads)\r\n", " --noSplit Do not split alignment count for each read by the number of times it aligns\r\n", " -o, --outFilePrefix string path/to/outfile prefix (len.csv will be appended)\r\n", " -t, --readFileType string Read file type: cfa (collapsed FASTA), fa (FASTA), fq (FASTQ), clean (BGI clean.fa). (default \"cfa\")\r\n", "\r\n", "Use \"scram [command] --help\" for more information about a command.\r\n" ] } ], "source": [ "!scram -h" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Comparison alignments and scatter plots" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "- For comparing two treatments (e.g. wild-type verses mutant) - the output is the mean and standard error of the total alignments to each reference sequence\n", "- By default, the alignment count of multi-mapping reads is split evenly between the number of loci aligned to (both within and among all reference sequences). The -noSplit flag shows the maximum possible alignment count at each loci \n", "- Alignments are carried out seperately for each small RNA size (read length) entered in the -nt filed\n", "- The read length aligned is appended to the alignment csv file name" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Alignment of 2 x 3 replicates (treatment A & treatment B) x 3 read lengths (21, 22, 24 nt) to Arabidopsis transposable elements FASTA reference file\n", "- Read files are in collapsed FASTA format (generated by [FASTX-Toolkit](http://hannonlab.cshl.edu/fastx_toolkit/)), which is the default format for SCRAM \n", "- FASTQ or FASTA (non-collapsed) can also be used (with the readFileType flag). GZIP compressed input is fine. 3' Adapters can be trimmed on-the-fly from FASTA and FASTQ reads (with the adapter flag). Adapter trimming is quite stringent (12 5'adapter nucleotides must be all present, or the read is rejected), so a dedicated read QC/trimming software package may be desirable. " ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Loading reads\n", "\n", "\n", "SCRAM is attempting to load read files in the default collapsed FASTA format\n", "seq/treatment_a_rep1.fa - 7,916,958 reads processed\n", "seq/treatment_a_rep2.fa - 7,827,082 reads processed\n", "seq/treatment_a_rep3.fa - 7,897,787 reads processed\n", "\n", "SCRAM is attempting to load read files in the default collapsed FASTA format\n", "seq/treatment_b_rep3.fa - 9,185,811 reads processed\n", "seq/treatment_b_rep2.fa - 8,311,241 reads processed\n", "seq/treatment_b_rep1.fa - 8,203,718 reads processed\n", "\n", "Loading reference\n", "\n", "No. of reference sequences: 31189\n", "Combined length of reference sequences: 23,315,940 nt\n", "\n", "Aligning 21 nt reads\n", "\n", "Aligning 22 nt reads\n", "\n", "Aligning 24 nt reads\n", "\n", "Alignment complete. Total time taken = 15.746887639s\n" ] } ], "source": [ "!scram compare -r ref/TAIR10_transposable_elements.fa \\\n", " -1 seq/treatment_a_rep1.fa,seq/treatment_a_rep2.fa,seq/treatment_a_rep3.fa \\\n", " -2 seq/treatment_b_rep1.fa,seq/treatment_b_rep2.fa,seq/treatment_b_rep3.fa \\\n", " -l 21,22,24 -o out_dir/treatment_a_vs_b \n", " \n", " " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### The normalised alignment count (reads per million reads) and standard error for the two treatments (columns) aligned to each reference sequence (rows) are generated\n", "- data can be easily imported and manipulated in a Pandas dataframe\n", "- NOTE: There's no need for data manipulation in Pandas prior to plotting - it's just a demo" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [], "source": [ "comparison_alignment = pandas.read_csv('out_dir/treatment_a_vs_b_21.csv')" ] }, { "cell_type": "code", "execution_count": 35, "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/html": [ "
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HeaderMean count 1Std. err 1Mean count 2Std. err 2
0AT3TE56475|+|13785373|13785436|ATDNA12T3_2|DNA...0.4660.0173020.4270.022843
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2AT5TE53195|+|14754521|14755395|ATREP15|RC/Heli...0.0010.0000030.0000.000017
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" ], "text/plain": [ " Header Mean count 1 \\\n", "0 AT3TE56475|+|13785373|13785436|ATDNA12T3_2|DNA... 0.466 \n", "1 AT3TE55845|+|13718067|13718130|ATDNA12T3_2|DNA... 0.953 \n", "2 AT5TE53195|+|14754521|14755395|ATREP15|RC/Heli... 0.001 \n", "3 AT3TE45810|+|11021715|11022665|BOMZH1|DNA/MuDR... 0.034 \n", "4 AT3TE47200|-|11319279|11319496|HELITRONY3|RC/H... 0.039 \n", "\n", " Std. err 1 Mean count 2 Std. err 2 \n", "0 0.017302 0.427 0.022843 \n", "1 0.019223 0.920 0.040779 \n", "2 0.000003 0.000 0.000017 \n", "3 0.004299 0.027 0.004598 \n", "4 0.002143 0.037 0.002122 " ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "comparison_alignment.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### scram_plot.py compare can be used to generate interactive scatter plots using the bokeh plotting library\n", "- In Jupyter notebook, Python apps are executed using %run " ] }, { "cell_type": "code", "execution_count": 36, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "usage: scram_plot.py compare [-h] [-plot_type PLOT_TYPE] [-a ALIGNMENT]\n", " [-l LENGTH] [-xlab [X_LABEL [X_LABEL ...]]]\n", " [-ylab [Y_LABEL [Y_LABEL ...]]] [-html] [-pub]\n", " [-png] [-xylim XYLIM] [-fig_size FIG_SIZE]\n", "\n", "optional arguments:\n", " -h, --help show this help message and exit\n", " -plot_type PLOT_TYPE, --plot_type PLOT_TYPE\n", " Bokeh plot type to display (log, log_error or all)\n", " -a ALIGNMENT, --alignment ALIGNMENT\n", " sRNA alignment file prefix used by SCRAM profile (i.e.\n", " exclude _21.csv, _22.csv, _24.csv)\n", " -l LENGTH, --length LENGTH\n", " Comma-separated list of sRNA lengths to plot. SCRAM\n", " alignment files must be available for each sRNA\n", " length. For an miRNA alignment file, use 'mir' instead\n", " of an integer\n", " -xlab [X_LABEL [X_LABEL ...]], --x_label [X_LABEL [X_LABEL ...]]\n", " x label - corresponds to -s1 treatment in SCRAM\n", " arguments\n", " -ylab [Y_LABEL [Y_LABEL ...]], --y_label [Y_LABEL [Y_LABEL ...]]\n", " y label - corresponds to -s2 treatment in SCRAM\n", " arguments\n", " -html, --html If not using Jupyter Notebook, output interactive plot\n", " to browser as save to .html\n", " -pub, --publish Remove all labels from profiles for editing for\n", " publication\n", " -png, --png Export plot/s as 300 dpi .png file/s\n", " -xylim XYLIM, --xylim XYLIM\n", " x and y max. axis limits\n", " -fig_size FIG_SIZE, --fig_size FIG_SIZE\n", " Output plot dimensions\n" ] } ], "source": [ "%run /scram_plot/scram_plot.py compare -h" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### 2 plot types - log axis with standard error bars (deafult) or log axis\n", "- plots are interactive - hover over each point of interest to identify header\n", "- 21nt plots are green, 22nt pink, and 24nt blue\n", "- standard error bars are shown (x -> Treatment A, y -> Treatment b) in the default log + se bars plot" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Log plot with x,y standard error bars (default plot)" ] }, { "cell_type": "code", "execution_count": 37, "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/html": [] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", "(function(global) {\n", " function now() {\n", " return new Date();\n", " }\n", "\n", " var force = true;\n", "\n", " if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n", " window._bokeh_onload_callbacks = [];\n", " window._bokeh_is_loading = undefined;\n", " }\n", "\n", "\n", " \n", " if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n", " window._bokeh_timeout = Date.now() + 5000;\n", " window._bokeh_failed_load = false;\n", " }\n", "\n", " var NB_LOAD_WARNING = {'data': {'text/html':\n", " \"
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\n", "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%run /scram_plot/scram_plot.py compare -a out_dir/treatment_a_vs_b \\\n", " -l 24 \\\n", " -xlab Treatment A (RPMR) \\\n", " -ylab Treatment B (RPMR)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## miRNA comparison alignments / plots are a special case\n", "- For the aligner, the ```--mir``` flag is required, and the ```-l``` flag and arguments are not - all lengths are aligned" ] }, { "cell_type": "code", "execution_count": 38, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Loading reads\n", "\n", "\n", "SCRAM is attempting to load read files in the default collapsed FASTA format\n", "seq/treatment_a_rep3.fa - 7,897,787 reads processed\n", "seq/treatment_a_rep1.fa - 7,916,958 reads processed\n", "seq/treatment_a_rep2.fa - 7,827,082 reads processed\n", "\n", "SCRAM is attempting to load read files in the default collapsed FASTA format\n", "seq/treatment_b_rep3.fa - 9,185,811 reads processed\n", "seq/treatment_b_rep1.fa - 8,203,718 reads processed\n", "seq/treatment_b_rep2.fa - 8,311,241 reads processed\n", "\n", "Loading reference\n", "\n", "\n", "Alignment complete. Total time taken = 3.632545103s\n" ] } ], "source": [ "!scram compare -r ref/ath_mir.fa \\\n", " -1 seq/treatment_a_rep1.fa,seq/treatment_a_rep2.fa,seq/treatment_a_rep3.fa \\\n", " -2 seq/treatment_b_rep1.fa,seq/treatment_b_rep2.fa,seq/treatment_b_rep3.fa \\\n", " -o out_dir/treatment_a_vs_b_mir \\\n", " --mir" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### mir argument after the ```-l``` flag\n", "- Instead of entering the read lengths for seperate plots after ```-l```, enter ```mir``` as the argument, so all miRNA alignments are shown in a single plot" ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [ { "data": { "text/html": [] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", "(function(global) {\n", " function now() {\n", " return new Date();\n", " }\n", "\n", " var force = true;\n", "\n", " if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n", " window._bokeh_onload_callbacks = [];\n", " window._bokeh_is_loading = undefined;\n", " }\n", "\n", "\n", " \n", " if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n", " window._bokeh_timeout = Date.now() + 5000;\n", " window._bokeh_failed_load = false;\n", " }\n", "\n", " var NB_LOAD_WARNING = {'data': {'text/html':\n", " \"
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\n", "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%run /scram_plot/scram_plot.py compare -a out_dir/treatment_a_vs_b_mir \\\n", " -l mir \\\n", " -xlab Treatment A (RPMR) \\\n", " -ylab Treatment B (RPMR)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Profile alignments and profile plots\n", "- For aligning reads from one of more replicate read files to one or more reference sequences on a position-by-position basis\n", "- The reference sequence header, reference sequence length, read aligned, position, strand, count, standard error and the number of loci the read aligns to (Times aligned) are returned\n", "- The alignment position is the distance from the 5' end of the reference sequence (with 1 the first position). This distance is to the 5' end of the read of it aligns in the sense orientation, and the 3' end if it alignsin the anitsense orientation." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Alignment of a set of 3 replicates (treatment A) x 3 read lengths (21, 22, 24 nt) to reference sequences in the Arabidopsis transposable elements FASTA file (31,189 sequences)" ] }, { "cell_type": "code", "execution_count": 40, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Loading reads\n", "\n", "\n", "SCRAM is attempting to load read files in the default collapsed FASTA format\n", "seq/treatment_a_rep2.fa - 7,827,082 reads processed\n", "seq/treatment_a_rep3.fa - 7,897,787 reads processed\n", "seq/treatment_a_rep1.fa - 7,916,958 reads processed\n", "\n", "Loading reference\n", "\n", "No. of reference sequences: 31189\n", "Combined length of reference sequences: 23,315,940 nt\n", "\n", "Aligning 21 nt reads\n", "\n", "Aligning 22 nt reads\n", "\n", "Aligning 24 nt reads\n", "\n", "Alignment complete. Total time taken = 9.131281456s\n" ] } ], "source": [ "!scram profile -r ref/TAIR10_transposable_elements.fa \\\n", " -1 seq/treatment_a_rep1.fa,seq/treatment_a_rep2.fa,seq/treatment_a_rep3.fa \\\n", " -l 21,22,24 -o out_dir/treatment_a_profile\n", " " ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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HeaderlensRNAPositionStrandCountStd. ErrTimes aligned
0AT1TE52125|-|15827287|15838845|ATHILA2|LTR/Gyp...11559AAAAGGTCAAGAGACAAAGAT3237-0.0040.00062170
1AT1TE52125|-|15827287|15838845|ATHILA2|LTR/Gyp...11559TAATCCGGATTTCTCTTTATC4253+0.0030.00000999
2AT1TE52125|-|15827287|15838845|ATHILA2|LTR/Gyp...11559AGAAAACCTACTGTAAACTGT11514-0.0680.0082585
3AT1TE53750|-|16325184|16327367|ATREP3|RC/Helit...2184ACTAGATTTTAACCCGCGGTA65+0.0020.000265164
4AT1TE53750|-|16325184|16327367|ATREP3|RC/Helit...2184AAAAATAAATCGTCCCGCGGT87-0.0070.00002437
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" ], "text/plain": [ " Header len \\\n", "0 AT1TE52125|-|15827287|15838845|ATHILA2|LTR/Gyp... 11559 \n", "1 AT1TE52125|-|15827287|15838845|ATHILA2|LTR/Gyp... 11559 \n", "2 AT1TE52125|-|15827287|15838845|ATHILA2|LTR/Gyp... 11559 \n", "3 AT1TE53750|-|16325184|16327367|ATREP3|RC/Helit... 2184 \n", "4 AT1TE53750|-|16325184|16327367|ATREP3|RC/Helit... 2184 \n", "\n", " sRNA Position Strand Count Std. Err Times aligned \n", "0 AAAAGGTCAAGAGACAAAGAT 3237 - 0.004 0.000621 70 \n", "1 TAATCCGGATTTCTCTTTATC 4253 + 0.003 0.000009 99 \n", "2 AGAAAACCTACTGTAAACTGT 11514 - 0.068 0.008258 5 \n", "3 ACTAGATTTTAACCCGCGGTA 65 + 0.002 0.000265 164 \n", "4 AAAAATAAATCGTCCCGCGGT 87 - 0.007 0.000024 37 " ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" } ], "source": [ "comparison_alignment = pandas.read_csv('out_dir/treatment_a_profile_21.csv')\n", "comparison_alignment.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### scram_plot.py profileplots can be used to generate plots using the matplotlib plotting library\n", "- All profiles that meet the search criterea will be displayed. This includes and search term in the reference header and those with a minimum alignment count in the most abundent read length (for multi plots) is over the cutoff (to filter out low abundence background alignments)\n", "- The y-axis shows smoothed coverage (the number of reads covering each position)\n", "- A window size of 1 (-win 1) shows coverage with no smoothing\n", "- Input read lengths are plotted on the same graph providing the alignment files are present\n", "- For very long reference sequences (e.g. a chromosome), the -bin_reads flag assigns alinged reads to 10,000 bins prior to smoothing and plotting." ] }, { "cell_type": "code", "execution_count": 42, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "usage: scram_plot.py profile [-h] [-a ALIGNMENT] [-cutoff CUTOFF]\n", " [-s [SEARCH [SEARCH ...]]] [-l LENGTH]\n", " [-ylim YLIM] [-win WIN] [-pub] [-png]\n", " [-bin_reads]\n", "\n", "optional arguments:\n", " -h, --help show this help message and exit\n", " -a ALIGNMENT, --alignment ALIGNMENT\n", " sRNA alignment file prefix used by SCRAM profile (i.e.\n", " exclude _21.csv, _22.csv, _24.csv)\n", " -cutoff CUTOFF, --cutoff CUTOFF\n", " Min. alignment RPMR from the most abundant profile (if\n", " multi) to generate plot\n", " -s [SEARCH [SEARCH ...]], --search [SEARCH [SEARCH ...]]\n", " Full header or substring of header. Without flag, all\n", " headers will be plotted\n", " -l LENGTH, --length LENGTH\n", " Comma-separated list of sRNA lengths to plot. SCRAM\n", " alignment files must be available for each sRNA length\n", " -ylim YLIM, --ylim YLIM\n", " +/- y axis limit\n", " -win WIN, --win WIN Smoothing window size (default=auto)\n", " -pub, --publish Remove all labels from profiles for editing for\n", " publication\n", " -png, --png Export plot/s as 300 dpi .png file/s\n", " -bin_reads, --bin_reads\n", " For plotting large profiles (i.e. chromosomes).\n", " Assigns reads to 10,000 bins prior to smoothing.\n", " X-axis shows bin, not reference position\n" ] } ], "source": [ "%run /scram_plot/scram_plot.py profile -h" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### 21, 22 and 24 nt profile plots with the search term \"helitron\"" ] }, { "cell_type": "code", "execution_count": 43, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Loading scram alignment files:\n", "\n", "out_dir/treatment_a_profile_21.csv \n", "\n", "out_dir/treatment_a_profile_22.csv \n", "\n", "out_dir/treatment_a_profile_24.csv \n", "\n", "Extracting headers:\n", "\n", "Plotting:\n", "\n", "AT3TE33205|-|7920884|7922456|ATREP10B|RC/Helitron|1573 bp\n" ] }, { "data": { "image/png": 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oiqLUQ7nq0X9l5keKPL+NmS9x16z2wnjTOjuPf95UCzdbMYIRbaba9eDBRlvUXoyMAN/5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\nFrb99y9awqAIOjuLlmBscvzxcOSRvoAm3PpBEIwF4qushcya5RP09u1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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Plotting:\n", "\n", "AT5TE60080|+|16641990|16642980|ATREP10D|RC/Helitron|991 bp\n" ] }, { "data": { "image/png": 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hJGiPAP+Puz/d1/HLly/3TZs2FTFCGa62Nrjxqwk6f/cSDbPuZsOnfsY1M67h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\ndZN0e7jHcjGznfHbImkVPni2p6jl0YrH47wNbJO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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Plotting:\n", "\n", "AT4TE60630|-|12956832|12957720|ATREP3|RC/Helitron|889 bp\n" ] }, { "data": { "image/png": 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LEZiIiOSmRi2dqNX0u2exiAyWngYTrAbeAW4izFfWFm2fDeDuTxYgPhGRYa26\nOiRZ7v2fB62tLZw7YkRuYxOR/OupRm01YZTnSdEjkwPH5ykmERGJlJeHRK29vWOlgr5qbw+JWlVV\nbmMTkfzraR61OQWMQ0REulBWFhK11tb+J2qtrUrUROKq28EEZjbNzG4zs+fM7NdmpjU3RUQKLF2j\nNpC51NI1apWVuYtLRAqjp1Gf1wF3AfOBJwkT1IqISAGVl4evra39LyPdR03Tc4jET08V6SPd/afR\n8x+YmQYPiIgUWLpGbSCJWktLmDy3rCx3cYlIYfSUqFWY2WGEJaMAKjNfa9SniEj+ZfZR66+mplCj\n1t8+biIyeHr62G4Arsh4/WbGa436FBEpgLKyMDVHS0v/y0gnaqWluYtLRAqjp1GfcwsZiIiI7K6k\nJCRqA1nvs7k5NH2qRk0kfnpcQqorZnaimd2bj2BERGRXJSWh6XMgiVq62VSJmkj89DQ9x/Fm9pKZ\n1ZvZ/5rZIWa2DPge8JPChSgiMnwlEqFGramp/2W0tqpGTSSueqpRu5ywdNSewM3Aw8D17v4+d7+l\nEMGJiAx36abPhob+l5Huo5ZM5i4uESmMnv6/cnd/MHp+m5mtc/erCxCTiIhEEomQZO3Y0f8y0ola\nf9cKFZHB01OiNtrMTs88NvO1atVERPIvnaht397/MhoblaSJxFVPidqfgY9mvP5LxmsHlKiJiORZ\nIhEeA61RE5F46ml6ji8UMhAREdmd2cATtcbGUIaIxI8+uiIiRSy99FMq1b/z3cM8ahpIIBJPStRE\nRIpYejH19vb+nZ9KhaZPJWoi8aRETUSkiCUSYWH2/iZq6TnY1PQpEk/d9lHrNOJzNxr1KSKSf+lE\nrbm5f+enUmGdUNWoicRTT6M+0yM89wKOAh6IXs8F/oZGfYqIFERlJWzd2r9zU6lQq1ZVlduYRKQw\neh31aWb3ADPdfUP0ejxwfUGiExERKir6P5gglQoPJWoi8ZRNr4XJ6SQt8hYwJU/xiIhIJxUV/T83\nXaNWXZ27eESkcLJZovd+M/sT8Ovo9aeA+/IXkoiIZErXqKVSfR8U4K6mT5E46zVRc/dzzew04Nho\n07Xufmt+wxIRkbTS0pBstbf3PVFTjZpIvGX7kX8SuMvdLwD+ZGYjB3JRM/uBmb1gZs+Y2a1mNjpj\n38VmtsrMXjSzkwZyHRGRoaC8PCRcra19Pzc9rcdAmk9FZPD0mqiZ2ZeAm4H/jjZNBG4b4HXvBQ52\n90OBl4Abf8ICAAAgAElEQVSLo2vNBM4EZgHzgB+bmQaVi8iwlq5Ra2vr+7nt7R2T5opI/GRTo3YO\ncDSwDcDdXyZM2dFv7n6Pu6d/5TwCTIqenwrc5O7N7v4asAo4fCDXEhGJu9LS/teotbaGRK28PPdx\niUj+ZZOoNbt7S/qFmZUAnsMYvgjcHT2fCKzJ2Lc22iYiMmyVlfW/Rq2lJSRqJdkMHRORopPNR/fP\nZvZNoNLMTgS+Bvyht5PM7D5gny52fcvdb4+O+RbQBtyYfcg7y18ILASYMkWzhYjI0DWQRK25WYma\nSJxl89H9BnA28CzwZWAx8LPeTnL3E3rab2afBz4CfNDd0zV064DJGYdNirZ1Vf61wLUAdXV1uazh\nExEpKmVloelTNWoiw08203OkgJ9Gj5wws3nAPwPHuXtDxq47gF+Z2RXABGAa8FiurisiEkcDGUyg\nGjWReOv1o2tmRwOXAPtGxxvg7v6eAVz3aqAcuNfMAB5x96+4+/Nm9ltgBaFJ9Bx3bx/AdUREYq+8\nPCRqAxlMoEXZReIpm/+xfg5cADwB5CRpcvcDeth3KXBpLq4jIjIUpEd9trT0fmxnqlETibdsPrrv\nuvvdvR8mIiL5kEyGGrWmpr6f29oaVjNQoiYST91+dM1sdvR0iZn9ALgFaE7vd/cn8xybiIjQ0Wy5\nY0ffz003lypRE4mnnj66l3d6XZfx3IHjcx+OiIh0ZhYe/UnUNOpTJN66/ei6+1wAM3uPu7+auc/M\nBjKQQERE+iCRCI+Ght6P7SydqGkwgUg8ZbMywc1dbPtdrgMREZGupWvU+pOoNTeHJC8MsBeRuOmp\nj9p0wuLoo8zs9IxdNYCW9xURKZB0otWfRK2xMffxiEjh9NRr4SDCygGjgY9mbN8OfCmfQYmISId0\notbXPmrpkaJq9hSJr576qN0O3G5mR7r7wwWMSUREMpiFZaT6ujJBe3voo5bIppOLiBSlbD6+a8zs\nVjPbGD1+b2aT8h6ZiIgAIdFKr/fZF+6hj5pq1ETiK5tE7ReENTgnRI8/RNtERKQAzMIyUu19XBsm\nlepYmUBE4imbRG0vd/+Fu7dFj+uBcXmOS0REIulErT81ai0tqlETibNsErW3zezTZpaMHp8GNuc7\nMBERCRIJqKjoex+1VCqsTKBETSS+sknUvgh8EngzepwBfCGfQYmISIeBNH2mUlBVlZ+4RCT/el1U\nxN1fBz5WgFhERKQblZWhKdM9+z5nqVQ4vrIyv7GJSP70WqNmZpM06lNEZHCVlYUatb70U0snaiNG\n5C8uEckvjfoUEYmB0tLwtS/91NzV9CkSd9kkauM06lNEZHCVlnYMDsiWatRE4i+bRG2zRn2KiAyu\nsrLwta81au5QXZ2fmEQk//o66nMDGvUpIlJwJSWhhqwviVpzc0jUysvzF5eI5JdGfYqIxEB6Cam+\nJmqJREjyRCSeev34mtl+wHnA1Mzj3V3Jm4hIgZSWhtqxviRqLS1hKg9NeCsSX9n8n3Ub8HPCaM8+\nLmAiIiK5kB5M0NdEDVSjJhJn2Xx8m9z9qrxHIiIi3aqoCF/7U6OmRE0kvrL5+F5pZv8G3AM0pze6\n+5N5i0pERHbRnz5qavoUib9sErVDgM8Ax9PR9OnRaxERKYD09Bx9mUetuVk1aiJxl83H9xPAe9y9\nJd/BiIhI19J91Fr68Js4ndSpRk0kvrKZR+05YHS+AxERke6VlISpNpqasj+npUXTc4jEXTYf39HA\nC2b2OLv2UdP0HCIiBZJMhmbMHTuyP6e1NUzpoRo1kfjKJlH7t1xf1Mz+AziV0OdtI/B5d18f7bsY\nOBtoB8539z/l+voiInGTSIRErb4++3M04a1I/GXT9LkM+Ku7/5mwhNQo4G8DvO4P3P1Qd68F7gT+\nFcDMZgJnArOAecCPzUz/C4rIsGcWkq6GhuyOT0+Oq8EEIvGWTaL2F6DCzCYSpuj4DHD9QC7q7tsy\nXo4gjCKFUMt2k7s3u/trwCrg8IFcS0RkKEjXqGWbqKVSoelTiZpIvGWTqJm7NwCnAz92908ABw/0\nwmZ2qZmtARYQ1agBE4E1GYetjbaJiAxr/alRa20N56iPmkh8ZZWomdmRhITqrmzPM7P7zOy5Lh6n\nArj7t9x9MnAjcG5fAzezhWa2zMyWbdq0qa+ni4jESrpGrbExu+NTqdBHLT0IQUTiKZsK8a8DFwO3\nuvvzZvYeYElvJ7n7CVnGcCOwmDBoYR0wOWPfpGhbV+VfC1wLUFdX510dIyIyVCQSYS61bCe8TSdq\niWz+HReRotVroubufyH0U0u/fhU4fyAXNbNp7v5y9PJU4IXo+R3Ar8zsCmACMA14bCDXEhEZCsyg\nvBza27M7PpUKc64pUROJt24TNTP7KXCVuz/bxb4RwKeAZne/sR/X/Z6ZHUSYnuN14CsAUY3db4EV\nQBtwjrtn+WtJRGToSiTCMlLZTnibXsVA/dNE4q2nGrVrgH8xs0MIqxNsAioItVw1wHWEZss+c/f5\nPey7FLi0P+WKiAxVZlBR0bfBBE1NUFOT37hEJL+6TdTc/Sngk2ZWDdQB44FGYKW7v1ig+EREhI5E\nrb09JGG9DRBobw/zqJWWFiY+EcmPbPqo1QMP5j8UERHpTnowQXt7ePQ2N5p7aP6srCxMfCKSH+pm\nKiISA2ahj1pbW3YjP1OpkKyNGJH/2EQkf5SoiYjERFlZx4oDvUnXqFVV5T8uEcmfrBM1M9PHXURk\nEPUlUWttDU2kStRE4i2bFQaOMrMVRHOdmdl7zezHeY9MRER2UVbWsdh6b1pbw7Hl5fmPS0TyJ5sa\ntR8BJwGbAdz9aeDYfAYlIiK7Sydq2dSotbSE2reKivzHJSL5k1XTp7uv6bRJk9CKiBRYaWlIvrKp\nUWtpCUmdEjWReMtmrc81ZnYU4GZWSlj7c2V+wxIRkc7SU3JkU6PW3By+ah41kXjLpkbtK8A5wETC\nAum10WsRESmg9Fqf2TZ9Qu/zrYlIcctmwtu3gQUFiEVERHrQlz5qTU1h7jUlaiLx1utH2Myu6mLz\nu8Ayd7899yGJiEhXysrC13SzZk+am5WoiQwF2TR9VhCaO1+OHocCk4CzzWxRHmMTEZEMJSUh+dqx\no/dj08mcEjWReMvmI3wocLS7twOY2U+AvwLHAM/mMTYREclQWgrJJDQ29n5suo9aMpnfmEQkv7Kp\nUdsDqM54PQIYEyVuWVTAi4hILpSWhhq13hK1VCokamYa9SkSd9nUqF0GPGVmDwJGmOz2P81sBHBf\nHmMTEZEMpaWQSEBDQ8/HpZeZSiTU9CkSd9mM+vy5mS0GDo82fdPd10fPL8pbZCIisou+1qgpUROJ\nv2wXZW8CNgBbgQPMTEtIiYgUWElJ6HPW22ACJWoiQ0c203P8A2E1gknAU8D7gYeB4/MbmoiIZDIL\nj96aPtvbQ6KWTCpRE4m7bGrUvg78HfC6u88FDgPeyWtUIiKym/S8aGr6FBk+sknUmty9CcDMyt39\nBeCg/IYlIiKdJRJhkfXeFmVPpcI8akrUROIvm4/wWjMbDdwG3GtmW4HX8xuWiIh0ZhZWJ2hpCc2b\n3c2Rlk7U0n3aRCS+shn1eVr09BIzWwKMAv6Y16hERGQ3iUQY+dnWFqbf6C4Ja28PiVp5eWHjE5Hc\n6zFRM7Mk8Ly7Twdw9z8XJCoREdlNOlFLDxaoqOj6uPQ8ajU1hY1PRHKvxz5q0eoDL5rZlALFIyIi\n3UivNNDW1rFEVFdaWkKy1l0iJyLxkU0ftT2A583sMWDn7D3u/rG8RSUiIrtJJEIftXTTZneam8Mx\navoUib9sErV/yXsUIiLSq/RggnQfte40N4catbKywsUmIvmRzWCCP5vZvsA0d7/PzKoAjSMSESmw\n9HQb2dSopVKqURMZCnqdR83MvgTcDPx3tGkiYaqOATOz/2NmbmZjM7ZdbGarzOxFMzspF9cRERkK\nEomQfKUHE3SnqUmJmshQkU3T5zmEBdkfBXD3l81sr4Fe2MwmAx8C3sjYNhM4E5gFTADuM7MDo0EN\nIiLDXnl5SMJ6Wp0g3UetsrJwcYlIfmSzMkGzu+/8383MSgDPwbV/BPxzp7JOBW5y92Z3fw1YRUgS\nRUSEkKglEj0vzK6mT5GhI5tE7c9m9k2g0sxOBH4H/GEgFzWzU4F17v50p10TgTUZr9dG20REhDA9\nhxls3979MekataqqwsUlIvmRTdPnN4CzgWeBLwOLgZ/1dpKZ3Qfs08WubwHfJDR79puZLQQWAkyZ\nomneRGR4KCsLAwq6S9Ta2zuaRdX0KRJ/2SRqHwf+x91/2peC3f2Errab2SHAfsDTZgYwCXjSzA4H\n1gGTMw6fFG3rqvxrgWsB6urqctEUKyJS9EpKskvUkklNzyEyFGTT9PlR4CUzu8HMPhL1Ues3d3/W\n3fdy96nuPpXQvDnb3d8E7gDONLNyM9sPmAY8NpDriYgMJeXlIVGrr+96f3t7GPWZTIZmUhGJt14T\nNXf/AnAAoW/aWcArZtZr02d/uPvzwG+BFYSF38/RiE8RkQ6lpSFRa2joen97e9iXPk5E4i2rj7G7\nt5rZ3YQRmpWE5tB/yEUAUa1a5utLgUtzUbaIyFCT7qPW0ADuYWBBpvRkuCUlqlETGQqymfD2ZDO7\nHngZmE8YSNDVIAEREcmzsrKQnKVSXa9OkK5RS/dlE5F4y+Zj/FngN8CX3b2HRUtERCTfyss7atKa\nm6GiYtf9bW1h1YLSUtWoiQwF2az1eZaZ7Q2cGI3SfMzdN+Y9MhER2U16HrX06gSjRu26v7Ex1Kpp\nMIHI0JBN0+cnCCMvPwF8EnjUzM7Id2AiIrK70tKwMkF3y0jV14f96WNFJN6yafr8NvB36Vo0MxsH\n3EdYqF1ERAookQj91LZt63rkZ319qHEzU6ImMhRkM49aolNT5+YszxMRkRxLT2SbSoVkrbMdOzpG\ngipRE4m/bGrU/mhmfwJ+Hb3+FHB3/kISEZHumIVELZGAzZt3379jR0ji1EdNZGjIZjDBRWZ2OnBM\ntOlad781v2GJiEhX0jVqJSWwdeuu+9raQr+1VCosyN55jjURiZ9uEzUzOwDY292XuvstwC3R9mPM\nbH93f6VQQYqISGDWMUda5xq11tawBmgiEabxEJH466mv2SKgix4QvBvtExGRAksmQxJWVhYSNfeO\nfS0tod9aMrn7/GoiEk89JWp7u/uznTdG26bmLSIREelWZh+15uZdVydobQ2JWiKhRE1kqOgpURvd\nw77KXAciIiK9S/dRg1Cbljnys6EBmppCMlep39IiQ0JPidoyM/tS541m9g/AE/kLSUREumPWsYxU\nezu8+27Hvs2bQ9+19nYlaiJDRU+jPv8RuNXMFtCRmNUBZcBp+Q5MRES6VlHRMant+vUwbVpI3DZu\nDDVuLS1h1KeIxF+3iZq7vwUcZWZzgYOjzXe5+wMFiUxERLqUbvqsqoJXX4XjjgvJ2datIXlra1Oi\nJjJUZDOP2hJgSQFiERGRLKSn3hg5ElavDvOmNTSEGrXKypCwjRw5qCGKSI5oKSgRkZhJj+gcMSKs\n7blxY+if9tZbYZtGfYoMHdksISUiIkWkoiLUopWUhKbOpUtDTVpJ9BtdE96KDB1K1EREYqaysmOi\n28mT4W9/g+pqGDUqbE+PDBWR+FOiJiISM+katfTz/fYLr8vLw6CC9KS4IhJ/StRERGImnaila89K\nSzv2pVJK1ESGEg0mEBGJmdLSkIila9UypZtENZhAZGhQoiYiEjOJREjW2tp235dO1FSjJjI0KFET\nEYmZZDL0R2tv331fW1tI4jKbQ0UkvpSoiYjETElJGPnZ2rr7vtbWsCqBWeHjEpHcU6ImIhIzJSUh\nGeuq6bO1VasSiAwlStRERGImmQw1akrURIY+JWoiIjFjFia47S5RGzWq8DGJSH4MSqJmZpeY2Toz\neyp6fDhj38VmtsrMXjSzkwYjPhGRYldZ2fX21lYYPbqwsYhI/gzmhLc/cvcfZm4ws5nAmcAsYAJw\nn5kd6O5djG0SERm+RozYfVt6EtyamsLHIyL5UWxNn6cCN7l7s7u/BqwCDh/kmEREis6IEbtPeJtK\nhf5rXSVxIhJPg5monWdmz5jZdWa2R7RtIrAm45i10TYREckwatTufdRSqTAZbnX14MQkIrmXt0TN\nzO4zs+e6eJwK/AR4D1ALbAAu70f5C81smZkt27RpU46jFxEpbumRnZm1au3tHQMNRGRoyFsfNXc/\nIZvjzOynwJ3Ry3XA5Izdk6JtXZV/LXAtQF1dnfc/UhGR+CkvD02cLS0d63qmEzU1fYoMHYM16nN8\nxsvTgOei53cAZ5pZuZntB0wDHit0fCIixa60NNSctbR0bGttDaNBtXyUyNAxWKM+LzOzWsCB1cCX\nAdz9eTP7LbACaAPO0YhPEZHdlZaG0Z0bNnRsa2iA8eO7P0dE4mdQEjV3/0wP+y4FLi1gOCIisZNM\nwt57w+rVHdsaG2Hy5G5PEZEYKrbpOUREJEt77tnxvL09PCZqnLzIkKJETUQkpvbaK/RLcw9fS0pg\nzJjBjkpEckmJmohITO21Vxjx2dwcHiUloTlURIYOJWoiIjE1YgRMmgTvvAPbtoX+aempOkRkaFCi\nJiISU4kEvO99IVFrbIQjjxzsiEQk1wZzUXYRERmg974Xjj02NH3OnDnY0YhIrilRExGJsUQCTjtt\nsKMQkXxR06eIiIhIkVKiJiIiIlKklKiJiIiIFCklaiIiIiJFSomaiIiISJFSoiYiIiJSpJSoiYiI\niBQpJWoiIiIiRUqJmoiIiEiRUqImIiIiUqTM3Qc7hgEzs03A6wW41Fjg7QJcR/JL93Fo0H0cGnQf\nhw7dy+zt6+7jsjlwSCRqhWJmy9y9brDjkIHRfRwadB+HBt3HoUP3Mj/U9CkiIiJSpJSoiYiIiBQp\nJWp9c+1gByA5ofs4NOg+Dg26j0OH7mUeqI+aiIiISJFSjZqIiIhIkVKilgUzm2dmL5rZKjP7xmDH\nI90zs8lmtsTMVpjZ82b29Wj7GDO718xejr7ukXHOxdG9fdHMThq86KUzM0ua2XIzuzN6rfsYQ2Y2\n2sxuNrMXzGylmR2pexk/ZnZB9Hv1OTP7tZlV6D7mnxK1XphZErgGOBmYCZxlZjMHNyrpQRvwf9x9\nJvB+4Jzofn0DuN/dpwH3R6+J9p0JzALmAT+O7rkUh68DKzNe6z7G05XAH919OvBewj3VvYwRM5sI\nnA/UufvBQJJwn3Qf80yJWu8OB1a5+6vu3gLcBJw6yDFJN9x9g7s/GT3fTviDMJFwz34ZHfZL4OPR\n81OBm9y92d1fA1YR7rkMMjObBJwC/Cxjs+5jzJjZKOBY4OcA7t7i7u+gexlHJUClmZUAVcB6dB/z\nTola7yYCazJer422SZEzs6nAYcCjwN7uviHa9Sawd/Rc97d4LQL+GUhlbNN9jJ/9gE3AL6Jm7J+Z\n2Qh0L2PF3dcBPwTeADYA77r7Peg+5p0SNRmSzKwa+D3wj+6+LXOfh6HOGu5cxMzsI8BGd3+iu2N0\nH2OjBJgN/MTdDwN2EDWPpeleFr+o79mphMR7AjDCzD6deYzuY34oUevdOmByxutJ0TYpUmZWSkjS\nbnT3W6LNb5nZ+Gj/eGBjtF33tzgdDXzMzFYTuhscb2b/i+5jHK0F1rr7o9HrmwmJm+5lvJwAvObu\nm9y9FbgFOArdx7xTota7x4FpZrafmZUROkfeMcgxSTfMzAh9YVa6+xUZu+4APhc9/xxwe8b2M82s\n3Mz2A6YBjxUqXumau1/s7pPcfSrhM/eAu38a3cfYcfc3gTVmdlC06YPACnQv4+YN4P1mVhX9nv0g\noQ+w7mOelQx2AMXO3dvM7FzgT4RRLte5+/ODHJZ072jgM8CzZvZUtO2bwPeA35rZ2cDrwCcB3P15\nM/st4Q9HG3COu7cXPmzJku5jPJ0H3Bj9s/sq8AVCRYHuZUy4+6NmdjPwJOG+LCesRFCN7mNeaWUC\nERERkSKlpk8RERGRIqVETURERKRIKVETERERKVJK1ERERESKlBI1ERERkSKlRE1ERESkSClRk9gw\ns4+bmZvZ9Oj1IWb2VPTYYmavRc/vyzinxszWmtnV0etbo2NWmdm7GecfZWYPmtmLGdtuzijnk2a2\nwsyeN7NfZWz/nJm9HD0+l7HdzOxSM3vJzFaa2fnR9lPN7Jmo/GVmdkzGOfOi668ys29kbP+8mV3S\nzfdk5z4z29PMlphZffr9RturzOwuM3shiv97Gfv2NbP7o5gejBZCT+9rz/he3JGxvbv3NsrM/mBm\nT0fX+UK0vcLMHsvY/p2Msn4QxfVMdG9GZ+xbnfH8UjNbY2b1nd7/hdF9eSZ6H/tm7Pu+mT0XPT6V\nsf36jJ+Vp8ysNtp+Uca256L3P8bMDsrY/pSZbTOzf8wi/ouje/mimZ3U6fpzOr2Pp8zspozX10Tb\nVphZY8a1z+gU/9Nm9sGM87r8GTazS8x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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Plotting:\n", "\n", "AT3TE41655|+|10008501|10009413|ATREP5|RC/Helitron|913 bp\n" ] }, { "data": { "image/png": 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7qYFa3wIb98ETW+CPW2BrHbTn12l89NEhgctkChOziIhIHPJZRqQd+E70Ehky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\nzewoMyshPMh5zxDHJBEzM8IzOM+5+9d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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Plotting:\n", "\n", "AT2TE22655|+|5607445|5607739|ATREP10A|RC/Helitron|295 bp\n" ] }, { "data": { "image/png": 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CugN0pyAET4osRcKSJCxBIiQpwyhLlREPE4iFcygPccotToxY+pS5GeE6/Ckh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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%run /scram_plot/scram_plot.py profile -s helitron \\\n", " -a out_dir/treatment_a_profile -l 21,22,24\\\n", " -cutoff 30" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Alignment to GFP example" ] }, { "cell_type": "code", "execution_count": 44, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Loading reads\n", "\n", "\n", "SCRAM is attempting to load read files in the default collapsed FASTA format\n", "seq/treatment_a_rep3.fa - 7,897,787 reads processed\n", "seq/treatment_a_rep1.fa - 7,916,958 reads processed\n", "seq/treatment_a_rep2.fa - 7,827,082 reads processed\n", "\n", "Loading reference\n", "\n", "No. of reference sequences: 1\n", "Combined length of reference sequences: 987 nt\n", "\n", "Aligning 21 nt reads\n", "\n", "Aligning 22 nt reads\n", "\n", "Aligning 24 nt reads\n", "\n", "Alignment complete. Total time taken = 1.719335469s\n" ] } ], "source": [ "!scram profile -r ref/GFP.fa \\\n", " -1 seq/treatment_a_rep1.fa,seq/treatment_a_rep2.fa,seq/treatment_a_rep3.fa \\\n", " -l 21,22,24 -o out_dir/treatment_a_profile_GFP" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### 21, 22 and 24 nt GFP profile plots \n", "- Note: If only one reference is aligned to, no search term is required for the plot" ] }, { "cell_type": "code", "execution_count": 45, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Loading scram alignment files:\n", "\n", "out_dir/treatment_a_profile_GFP_21.csv \n", "\n", "out_dir/treatment_a_profile_GFP_22.csv \n", "\n", "out_dir/treatment_a_profile_GFP_24.csv \n", "\n", "Extracting headers:\n", "\n", "Plotting:\n", "\n", "GFP\n" ] }, { "data": { "image/png": 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Jrskcjh4e1D6yA02TGlXxKpzCmfS0Tscd73YyFKZP8ht+toa3YhEWjsaP0qw3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coR2qxt2vWMUC0MfVH2InKW47bh23B3Ek8ma9tlLXtWX9+V6jkdz6FChYpXuCh3ERszG/nU8U/x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\niUhrU2InIitGLszRG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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%run /scram_plot/scram_plot.py profile \\\n", " -a out_dir/treatment_a_profile_GFP -l 21,22,24" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### 22 nt GFP profile plot - with automatic smoothing" ] }, { "cell_type": "code", "execution_count": 46, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Loading scram alignment files:\n", "\n", "out_dir/treatment_a_profile_GFP_22.csv \n", "\n", "Extracting headers:\n", "\n", "Plotting:\n", "\n", "GFP\n" ] }, { "data": { "image/png": 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qMkM6JkI0O11j0v9tPhubAactfZqpfwZ45DzQPU2B+J4d1qaA6o1U+cvjjBQd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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%run /scram_plot/scram_plot.py profile \\\n", " -a out_dir/treatment_a_profile_GFP -l 22" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### 22 nt GFP profile plots - without smoothing" ] }, { "cell_type": "code", "execution_count": 47, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Loading scram alignment files:\n", "\n", "out_dir/treatment_a_profile_GFP_22.csv \n", "\n", "Extracting headers:\n", "\n", "Plotting:\n", "\n", "GFP\n" ] }, { "data": { "image/png": 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N873dWm0Gwun43WJoCnDccT3/BnAwzPNlZxc3j9l4/AJdw8XQH+ZmxUn8r83V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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%run /scram_plot/scram_plot.py profile \\\n", " -a out_dir/treatment_a_profile_GFP -l 22 -win 1" ] } ], "metadata": { "anaconda-cloud": {}, "kernelspec": { "display_name": "Python 3", "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": "3.6.0" } }, "nbformat": 4, "nbformat_minor": 2 }