{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "intrahost_final.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bGmGeK37JL9F"
      },
      "source": [
        "# Intrahost analysis in SARS-CoV-2 re-sequencing samples\n",
        "\n",
        "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/galaxyproject/SARS-CoV-2/blob/master/data/ipynb/intrahost.ipynb)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VWWDijVW51sq"
      },
      "source": [
        "## Run these first\n",
        "\n",
        "Three sections below are ingesting dependencies, initializating functions etc... So run it first!"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mWrJm5X0H5Ez"
      },
      "source": [
        "### Requirements"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ENWKo5zIIDjm",
        "outputId": "de1f75fa-f956-48b6-c42b-a75613f1790c"
      },
      "source": [
        "!pip install -U pandasql"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting pandasql\n",
            "  Downloading https://files.pythonhosted.org/packages/6b/c4/ee4096ffa2eeeca0c749b26f0371bd26aa5c8b611c43de99a4f86d3de0a7/pandasql-0.7.3.tar.gz\n",
            "Requirement already satisfied, skipping upgrade: numpy in /usr/local/lib/python3.7/dist-packages (from pandasql) (1.19.5)\n",
            "Requirement already satisfied, skipping upgrade: pandas in /usr/local/lib/python3.7/dist-packages (from pandasql) (1.1.5)\n",
            "Requirement already satisfied, skipping upgrade: sqlalchemy in /usr/local/lib/python3.7/dist-packages (from pandasql) (1.3.23)\n",
            "Requirement already satisfied, skipping upgrade: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas->pandasql) (2.8.1)\n",
            "Requirement already satisfied, skipping upgrade: pytz>=2017.2 in /usr/local/lib/python3.7/dist-packages (from pandas->pandasql) (2018.9)\n",
            "Requirement already satisfied, skipping upgrade: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas->pandasql) (1.15.0)\n",
            "Building wheels for collected packages: pandasql\n",
            "  Building wheel for pandasql (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for pandasql: filename=pandasql-0.7.3-cp37-none-any.whl size=26820 sha256=767c3136b6fc6e57fdd0a5b5742b9ba823198a9bc280b04e232eca84412a62ef\n",
            "  Stored in directory: /root/.cache/pip/wheels/53/6c/18/b87a2e5fa8a82e9c026311de56210b8d1c01846e18a9607fc9\n",
            "Successfully built pandasql\n",
            "Installing collected packages: pandasql\n",
            "Successfully installed pandasql-0.7.3\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pPkdwxd1H_Xj"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "from pandasql import sqldf\n",
        "pysqldf = lambda q: sqldf(q, globals())"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "K3HjNcTmJB5N"
      },
      "source": [
        "### Aux datasets"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4GeP3k6MIOk6"
      },
      "source": [
        "gnm_url = 'https://ftp.ncbi.nlm.nih.gov/genomes/all/GCF/009/858/895/GCF_009858895.2_ASM985889v3/GCF_009858895.2_ASM985889v3_genomic.fna.gz'\n",
        "gnm_file = gnm_url.split('/')[-1]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sDQGUEU-Id1a",
        "outputId": "ca567f20-720f-4522-c47d-563f3987fb28"
      },
      "source": [
        "# Get SARS-CoV-2 RefSeq genomes (in GenBank format) from NCBI\n",
        "import os.path\n",
        "from os import path\n",
        "if not path.exists(gnm_file[:-3]):\n",
        "    !wget -nc {gnm_url}\n",
        "    !gunzip {gnm_file}\n",
        "else:\n",
        "    print('File {} is already here\\nDoing nothing!'.format(gnm_file))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "--2021-03-24 15:51:40--  https://ftp.ncbi.nlm.nih.gov/genomes/all/GCF/009/858/895/GCF_009858895.2_ASM985889v3/GCF_009858895.2_ASM985889v3_genomic.fna.gz\n",
            "Resolving ftp.ncbi.nlm.nih.gov (ftp.ncbi.nlm.nih.gov)... 130.14.250.10, 130.14.250.11, 2607:f220:41e:250::10, ...\n",
            "Connecting to ftp.ncbi.nlm.nih.gov (ftp.ncbi.nlm.nih.gov)|130.14.250.10|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 9591 (9.4K) [application/x-gzip]\n",
            "Saving to: ‘GCF_009858895.2_ASM985889v3_genomic.fna.gz’\n",
            "\n",
            "\r          GCF_00985   0%[                    ]       0  --.-KB/s               \rGCF_009858895.2_ASM 100%[===================>]   9.37K  --.-KB/s    in 0s      \n",
            "\n",
            "2021-03-24 15:51:40 (104 MB/s) - ‘GCF_009858895.2_ASM985889v3_genomic.fna.gz’ saved [9591/9591]\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DGUP48yVIiMB"
      },
      "source": [
        "seq = \"\"\n",
        "with open(gnm_file[:-3],'r') as f:\n",
        "    for line in f:\n",
        "        if not line.startswith('>'):\n",
        "            seq += line.rstrip()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6TG1XhHDTz8G"
      },
      "source": [
        "annot = {\n",
        "    'start': [    265,    805,   2719,   8554,   10054,  10972,  11842,  12091,  12685,   13024,  13441,      16236,  18039,   19620,    20658,   13441,    21562,   25392, 26244, 26522, 27201,   27393,   27755,  27893, 28273, 29557],\n",
        "    'end':   [    805,   2719,   8554,  10054,   10972,  11842,  12091,  12685,  13024,   13441,  16236,      18039,  19620,   20658,    21552,   13480,    25384,   26220, 26472, 27191, 27387,   27759,   27887,  28259, 29533, 29674 ], \n",
        "    'func':  ['leader', 'nsp2', 'nsp3', 'nsp4', '3Cpro', 'nsp6', 'nsp7', 'nsp8', 'nsp9', 'nsp10', 'RdRp', 'helicase', 'ExoN', 'endoR', 'MethTr', 'nsp11', 'S', 'orf3a',   'E',   'M', 'orf6', 'orf7a', 'orf7b', 'orf8',  'N', 'orf10'], \n",
        "    }"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dmgYyVrtd925"
      },
      "source": [
        "gene_track = pd.DataFrame.from_dict(annot)[['start','end','func']].sort_values(by=['start']).reset_index()\n",
        "gene_track['top']= gene_track.index % 2\n",
        "gene_track['bottom'] = gene_track['top']-1\n",
        "gene_track.loc[gene_track['top'] == 0, 'color'] = 'red'\n",
        "gene_track.loc[gene_track['top'] != 0, 'color'] = 'blue'"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UT_10JCZWwM6"
      },
      "source": [
        "voc_url = 'https://github.com/galaxyproject/SARS-CoV-2/raw/master/data/voc/voc.tsv.gz'"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AIHd7KV_b8oF"
      },
      "source": [
        "# Sites under selection URL\n",
        "sel_url = 'https://github.com/galaxyproject/SARS-CoV-2/raw/master/data/selection/selection.tsv.gz'\n",
        "sel = pd.read_csv(sel_url,sep='\\t')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "M76zbHqhI96a"
      },
      "source": [
        "### Functions"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FQXgtsgyIkOJ"
      },
      "source": [
        "# Validation function for checking against genome\n",
        "\n",
        "def check_against_genome(seq,df,fields,name,debug=False):\n",
        "    \n",
        "    \"\"\" Takes sequence (seq), dataframe (df),\n",
        "    names of columns containing position and reference allele\n",
        "    (e.g., ['POS','REF']), and dataframe name.\n",
        "    Setting debud to True outputs a list of problematic sites.\n",
        "\n",
        "    Returns a dict with counts and list of wrong sites if any.\n",
        "    \"\"\"\n",
        "\n",
        "    df.name = df\n",
        "    wrong = []\n",
        "    bad = 0\n",
        "    good = 0\n",
        "    pb = df[fields].to_numpy()\n",
        "    for pos,ref in pb:\n",
        "        base = seq[pos:pos+len(ref)]\n",
        "        if base == ref:\n",
        "            good += 1\n",
        "        else:\n",
        "            bad += 1\n",
        "            wrong.append([pos,ref])\n",
        "    if debug is True:\n",
        "        return(wrong)\n",
        "    else:\n",
        "        return({\n",
        "            'name':name,\n",
        "            'good':good,\n",
        "            'bad':bad,\n",
        "            'num_sites':len(df)\n",
        "            })"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "trIQgKB6I020"
      },
      "source": [
        "class coordinateError(Exception):   \n",
        "    def __init__(self, data):    \n",
        "        self.data = data\n",
        "    def __str__(self):\n",
        "        return repr(self.data)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XPindc6qjSWm"
      },
      "source": [
        "# Computing poisson expectations\n",
        "import math\n",
        "\n",
        "def ps(l,s,N):\n",
        "    el = math.exp(-l)\n",
        "    lkf = 1\n",
        "    i = 0\n",
        "    sp = {'samples':[],'N':[]}\n",
        "    while (el*lkf*N)>0.1:\n",
        "        sp['samples'].append(i)\n",
        "        sp['N'].append((el*lkf*N))\n",
        "        i += 1\n",
        "        lkf *= l/i\n",
        "    return(sp)                 "
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "r9VK55w8qiyi"
      },
      "source": [
        "# Histogram generation\n",
        "\n",
        "def create_hist(df,col,bins=100):\n",
        "    hist, edges = np.histogram(df[col],bins)\n",
        "    hist_df = pd.DataFrame({col: hist, \"left\": edges[:-1], \"right\": edges[1:]})\n",
        "    hist_df[\"interval\"] = [\"%d to %d\" % (left, right) for left, right in zip(hist_df[\"left\"], hist_df[\"right\"])]\n",
        "    return(hist_df)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dR0rglPQt8Og"
      },
      "source": [
        "# Simple counts\n",
        "def site_stats(df):\n",
        "    tot_var = len(df)\n",
        "    tot_sites = len(df.groupby(['POS','ALT','REF']).groups)\n",
        "    tot_samples = df['Sample'].nunique()\n",
        "    return(tot_var,tot_sites,tot_samples)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GEMDYoZo3cNQ"
      },
      "source": [
        "# Plotting AF distribution for a partticular site\n",
        "\n",
        "import scipy.stats as stats\n",
        "from bokeh.models import Rect\n",
        "\n",
        "# non-parametric pdf\n",
        "def site_example(site):\n",
        "    af = var[var['POS']==site]['AF']\n",
        "    nparam_density = stats.kde.gaussian_kde(af.values.ravel())\n",
        "    x = np.linspace(0, 1, 100)\n",
        "    pdf = nparam_density(x)\n",
        "    plot = figure(\n",
        "        plot_height = 200, plot_width = 800,\n",
        "        title = 'Site {} ({} Samples)'.format(site,len(af)),\n",
        "        x_axis_label = 'AF',\n",
        "        y_axis_label = \"Density\",\n",
        "        x_range=Range1d(start=0, end=1,bounds=(0, 1)),\n",
        "        y_range=Range1d(start=0, end=5,bounds=(0, 30)),\n",
        "        toolbar_location=\"below\"\n",
        "        )  \n",
        "\n",
        "    ticks = ColumnDataSource({'tick':af.values.ravel()})\n",
        "    plot.line(\n",
        "        x=x, \n",
        "        y=pdf,\n",
        "        line_color='orange',\n",
        "        line_width=5\n",
        "        )\n",
        "    glyph = Rect(\n",
        "        x='tick',\n",
        "        y=0,\n",
        "        width=0.0001, \n",
        "        height=1,\n",
        "        line_color='red',\n",
        "        line_alpha=.5,\n",
        "        fill_alpha =.5)\n",
        "    plot.add_glyph(ticks,glyph)\n",
        "    show(plot)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "B_QE0TR31KmK"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pGk58UsXJYKj"
      },
      "source": [
        "## Ingesting and validating\n",
        "\n",
        "- Translate `FUNCLASS` names\n",
        "- Convert coordinates to 0-based (because VCFs are 1-based)\n",
        "- Validate all sites by comparing contains of `REF` field to genome"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zdF6zxa4KObD"
      },
      "source": [
        "# URL containing output of Galaxy workflow\n",
        "# These are stored here -> https://github.com/galaxyproject/SARS-CoV-2/tree/master/data\n",
        "per_sample_url = 'https://github.com/galaxyproject/SARS-CoV-2/raw/master/data/var/cog_20201120_by_sample.tsv.gz'\n",
        "per_variant_url = 'https://github.com/galaxyproject/SARS-CoV-2/raw/master/data/var/cog_20201120_by_var.tsv.gz'\n",
        "# Name of dataset that will be used in plots and reports\n",
        "dataset = 'COG-Post'"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HveB8NVdH3QR"
      },
      "source": [
        "# Read data into Pandas dataframe\n",
        "var = pd.read_csv(per_sample_url,sep='\\t')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MErz2NAAK030"
      },
      "source": [
        "# Humanize FUNCLASS names\n",
        "funclass_translation = {'SILENT':'Synonymous','MISSENSE':'Non-synonymous','NONSENSE':'Stop','.':'Non-coding','NONE':'Indel'}\n",
        "var = var.replace({'FUNCLASS':funclass_translation})"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ymMn9HkKLBK6"
      },
      "source": [
        "# Change coordinates to 0-based\n",
        "var['POS'] = var['POS']-1"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_WrL5E50LNbW"
      },
      "source": [
        "# Shorten names of some columns\n",
        "var = var.rename(columns={'countunique(change)':'unique_changes',    # Number of all samples\n",
        "                          'min(AF)':'mAF',                           # Minimum AF\n",
        "                          'max(AF)':'xAF',                           # Max AF\n",
        "                          'countunique(FUNCLASS)':'unique_funclass', # Accession numbers of samples with AF above threshold\n",
        "                          })"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MnitsWA0Q3uU",
        "outputId": "b963e897-b8e1-4344-9bef-2d324b991b2f"
      },
      "source": [
        "# Check against Genome\n",
        "# This step matches contect of REF field\n",
        "# Against genome\n",
        "# 'bad' should be 0\n",
        "\n",
        "outcome = check_against_genome(seq,var,['POS','REF'],'var')\n",
        "if outcome['bad'] > 0:\n",
        "    raise coordinateError(\"{} sites were not verified. Run check_agianst_genome with debig=True\".format(outcome['bad']))\n",
        "print(outcome)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "{'name': 'var', 'good': 38919, 'bad': 0, 'num_sites': 38919}\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:13: UserWarning: Pandas doesn't allow columns to be created via a new attribute name - see https://pandas.pydata.org/pandas-docs/stable/indexing.html#attribute-access\n",
            "  del sys.path[0]\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EVGxy0g48ylr",
        "outputId": "0edb84f3-14d8-4ef6-e883-ecc834a6fe5f"
      },
      "source": [
        "site_stats(var)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(38919, 5760, 1818)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "o9GRyUMOZizX"
      },
      "source": [
        "## Thresholding\n",
        "\n",
        "Here we assess how common variants are (how many samples contain each variant) and compute threshold of how many samples should share a variants for us to consider it in future analysis"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ssk4SJLKZyJU"
      },
      "source": [
        "For thresholding we only select sites with allele frequencing between 5% and 50% because these are more likely to be erroneous than sites with allele frequencies between 50% and 100%."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_cCTEgXEOW_3"
      },
      "source": [
        "# For each genome position count how many unique samples contain a variant at that position woth freq < 0.5\n",
        "# This is very slow approach (make it faster in the future)\n",
        "\n",
        "cpb = []\n",
        "for i in range(len(seq)):\n",
        "    cpb.append(len( np.unique( var[ ( var['POS']==i ) & ( var['AF']<=0.5 ) ]['Sample'].values ) ) )"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ms_ssnxoVnye"
      },
      "source": [
        "# Poisson lambda\n",
        "l = np.sum(cpb)/len(seq)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NUmhcg693lyt",
        "outputId": "7e7d1309-bb19-42f6-a462-575984dae33d"
      },
      "source": [
        "print(l)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "0.1502190415677357\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "biYeGiuATXgy"
      },
      "source": [
        "# Aggregate sample counts\n",
        "# How many sites are found in 1, 2, 3, 4 and so on samples\n",
        "unique, counts = np.unique(cpb, return_counts=True)\n",
        "bySiteCount = {'samples':unique,'N':counts}"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VDD8Rnw4qpvj"
      },
      "source": [
        "# Compute Poisson estimate (see \"Functions' section below)\n",
        "estimate = ps(l,bySiteCount.values(),len(seq))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 317
        },
        "id": "Fa-pqRq8q5nx",
        "outputId": "aead2fe3-f03f-4a80-973a-ae1950b84285"
      },
      "source": [
        "import bokeh.io\n",
        "import bokeh.plotting\n",
        "from bokeh.models import ColumnDataSource,Range1d\n",
        "from bokeh.plotting import figure, show,output_file,save\n",
        "bokeh.io.output_notebook()\n",
        "\n",
        "exp = ColumnDataSource(estimate)\n",
        "obs = ColumnDataSource(bySiteCount)\n",
        "p = figure(plot_width=600, \n",
        "           plot_height=300,\n",
        "           y_axis_type='log',\n",
        "            x_axis_type='linear',\n",
        "\n",
        "           y_axis_label='# Individual variants',\n",
        "           x_axis_label='# Samples sharing a variant',\n",
        "            x_range=Range1d(start=0, end=20,bounds=(0, 100)),\n",
        "            y_range=Range1d(start=0, end=100000,bounds=(0, 100000)),\n",
        "           \n",
        "           )\n",
        "p.line(y='N',x='samples',source=obs,line_color='red')\n",
        "p.circle(y='N',x='samples',source=obs,line_color='red')\n",
        "p.line(x='samples',y='N',source=exp,line_color='orange')\n",
        "output_file(\"thresholding_{}.html\".format(dataset))\n",
        "show(p)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
              "\n",
              "(function(root) {\n",
              "  function now() {\n",
              "    return new Date();\n",
              "  }\n",
              "\n",
              "  var force = true;\n",
              "\n",
              "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
              "    root._bokeh_onload_callbacks = [];\n",
              "    root._bokeh_is_loading = undefined;\n",
              "  }\n",
              "\n",
              "  var JS_MIME_TYPE = 'application/javascript';\n",
              "  var HTML_MIME_TYPE = 'text/html';\n",
              "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
              "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
              "\n",
              "  /**\n",
              "   * Render data to the DOM node\n",
              "   */\n",
              "  function render(props, node) {\n",
              "    var script = document.createElement(\"script\");\n",
              "    node.appendChild(script);\n",
              "  }\n",
              "\n",
              "  /**\n",
              "   * Handle when an output is cleared or removed\n",
              "   */\n",
              "  function handleClearOutput(event, handle) {\n",
              "    var cell = handle.cell;\n",
              "\n",
              "    var id = cell.output_area._bokeh_element_id;\n",
              "    var server_id = cell.output_area._bokeh_server_id;\n",
              "    // Clean up Bokeh references\n",
              "    if (id != null && id in Bokeh.index) {\n",
              "      Bokeh.index[id].model.document.clear();\n",
              "      delete Bokeh.index[id];\n",
              "    }\n",
              "\n",
              "    if (server_id !== undefined) {\n",
              "      // Clean up Bokeh references\n",
              "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
              "      cell.notebook.kernel.execute(cmd, {\n",
              "        iopub: {\n",
              "          output: function(msg) {\n",
              "            var id = msg.content.text.trim();\n",
              "            if (id in Bokeh.index) {\n",
              "              Bokeh.index[id].model.document.clear();\n",
              "              delete Bokeh.index[id];\n",
              "            }\n",
              "          }\n",
              "        }\n",
              "      });\n",
              "      // Destroy server and session\n",
              "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
              "      cell.notebook.kernel.execute(cmd);\n",
              "    }\n",
              "  }\n",
              "\n",
              "  /**\n",
              "   * Handle when a new output is added\n",
              "   */\n",
              "  function handleAddOutput(event, handle) {\n",
              "    var output_area = handle.output_area;\n",
              "    var output = handle.output;\n",
              "\n",
              "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
              "    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
              "      return\n",
              "    }\n",
              "\n",
              "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
              "\n",
              "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
              "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
              "      // store reference to embed id on output_area\n",
              "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
              "    }\n",
              "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
              "      var bk_div = document.createElement(\"div\");\n",
              "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
              "      var script_attrs = bk_div.children[0].attributes;\n",
              "      for (var i = 0; i < script_attrs.length; i++) {\n",
              "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
              "        toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n",
              "      }\n",
              "      // store reference to server id on output_area\n",
              "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
              "    }\n",
              "  }\n",
              "\n",
              "  function register_renderer(events, OutputArea) {\n",
              "\n",
              "    function append_mime(data, metadata, element) {\n",
              "      // create a DOM node to render to\n",
              "      var toinsert = this.create_output_subarea(\n",
              "        metadata,\n",
              "        CLASS_NAME,\n",
              "        EXEC_MIME_TYPE\n",
              "      );\n",
              "      this.keyboard_manager.register_events(toinsert);\n",
              "      // Render to node\n",
              "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
              "      render(props, toinsert[toinsert.length - 1]);\n",
              "      element.append(toinsert);\n",
              "      return toinsert\n",
              "    }\n",
              "\n",
              "    /* Handle when an output is cleared or removed */\n",
              "    events.on('clear_output.CodeCell', handleClearOutput);\n",
              "    events.on('delete.Cell', handleClearOutput);\n",
              "\n",
              "    /* Handle when a new output is added */\n",
              "    events.on('output_added.OutputArea', handleAddOutput);\n",
              "\n",
              "    /**\n",
              "     * Register the mime type and append_mime function with output_area\n",
              "     */\n",
              "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
              "      /* Is output safe? */\n",
              "      safe: true,\n",
              "      /* Index of renderer in `output_area.display_order` */\n",
              "      index: 0\n",
              "    });\n",
              "  }\n",
              "\n",
              "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
              "  if (root.Jupyter !== undefined) {\n",
              "    var events = require('base/js/events');\n",
              "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
              "\n",
              "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
              "      register_renderer(events, OutputArea);\n",
              "    }\n",
              "  }\n",
              "\n",
              "  \n",
              "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
              "    root._bokeh_timeout = Date.now() + 5000;\n",
              "    root._bokeh_failed_load = false;\n",
              "  }\n",
              "\n",
              "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
              "     \"<div style='background-color: #fdd'>\\n\"+\n",
              "     \"<p>\\n\"+\n",
              "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
              "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
              "     \"</p>\\n\"+\n",
              "     \"<ul>\\n\"+\n",
              "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
              "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
              "     \"</ul>\\n\"+\n",
              "     \"<code>\\n\"+\n",
              "     \"from bokeh.resources import INLINE\\n\"+\n",
              "     \"output_notebook(resources=INLINE)\\n\"+\n",
              "     \"</code>\\n\"+\n",
              "     \"</div>\"}};\n",
              "\n",
              "  function display_loaded() {\n",
              "    var el = document.getElementById(null);\n",
              "    if (el != null) {\n",
              "      el.textContent = \"BokehJS is loading...\";\n",
              "    }\n",
              "    if (root.Bokeh !== undefined) {\n",
              "      if (el != null) {\n",
              "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
              "      }\n",
              "    } else if (Date.now() < root._bokeh_timeout) {\n",
              "      setTimeout(display_loaded, 100)\n",
              "    }\n",
              "  }\n",
              "\n",
              "\n",
              "  function run_callbacks() {\n",
              "    try {\n",
              "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
              "        if (callback != null)\n",
              "          callback();\n",
              "      });\n",
              "    } finally {\n",
              "      delete root._bokeh_onload_callbacks\n",
              "    }\n",
              "    console.debug(\"Bokeh: all callbacks have finished\");\n",
              "  }\n",
              "\n",
              "  function load_libs(css_urls, js_urls, callback) {\n",
              "    if (css_urls == null) css_urls = [];\n",
              "    if (js_urls == null) js_urls = [];\n",
              "\n",
              "    root._bokeh_onload_callbacks.push(callback);\n",
              "    if (root._bokeh_is_loading > 0) {\n",
              "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
              "      return null;\n",
              "    }\n",
              "    if (js_urls == null || js_urls.length === 0) {\n",
              "      run_callbacks();\n",
              "      return null;\n",
              "    }\n",
              "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
              "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
              "\n",
              "    function on_load() {\n",
              "      root._bokeh_is_loading--;\n",
              "      if (root._bokeh_is_loading === 0) {\n",
              "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
              "        run_callbacks()\n",
              "      }\n",
              "    }\n",
              "\n",
              "    function on_error() {\n",
              "      console.error(\"failed to load \" + url);\n",
              "    }\n",
              "\n",
              "    for (var i = 0; i < css_urls.length; i++) {\n",
              "      var url = css_urls[i];\n",
              "      const element = document.createElement(\"link\");\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error;\n",
              "      element.rel = \"stylesheet\";\n",
              "      element.type = \"text/css\";\n",
              "      element.href = url;\n",
              "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
              "      document.body.appendChild(element);\n",
              "    }\n",
              "\n",
              "    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n",
              "\n",
              "    for (var i = 0; i < js_urls.length; i++) {\n",
              "      var url = js_urls[i];\n",
              "      var element = document.createElement('script');\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error;\n",
              "      element.async = false;\n",
              "      element.src = url;\n",
              "      if (url in hashes) {\n",
              "        element.crossOrigin = \"anonymous\";\n",
              "        element.integrity = \"sha384-\" + hashes[url];\n",
              "      }\n",
              "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
              "      document.head.appendChild(element);\n",
              "    }\n",
              "  };\n",
              "\n",
              "  function inject_raw_css(css) {\n",
              "    const element = document.createElement(\"style\");\n",
              "    element.appendChild(document.createTextNode(css));\n",
              "    document.body.appendChild(element);\n",
              "  }\n",
              "\n",
              "  \n",
              "  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n",
              "  var css_urls = [];\n",
              "  \n",
              "\n",
              "  var inline_js = [\n",
              "    function(Bokeh) {\n",
              "      Bokeh.set_log_level(\"info\");\n",
              "    },\n",
              "    function(Bokeh) {\n",
              "    \n",
              "    \n",
              "    }\n",
              "  ];\n",
              "\n",
              "  function run_inline_js() {\n",
              "    \n",
              "    if (root.Bokeh !== undefined || force === true) {\n",
              "      \n",
              "    for (var i = 0; i < inline_js.length; i++) {\n",
              "      inline_js[i].call(root, root.Bokeh);\n",
              "    }\n",
              "    } else if (Date.now() < root._bokeh_timeout) {\n",
              "      setTimeout(run_inline_js, 100);\n",
              "    } else if (!root._bokeh_failed_load) {\n",
              "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
              "      root._bokeh_failed_load = true;\n",
              "    } else if (force !== true) {\n",
              "      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n",
              "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
              "    }\n",
              "\n",
              "  }\n",
              "\n",
              "  if (root._bokeh_is_loading === 0) {\n",
              "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
              "    run_inline_js();\n",
              "  } else {\n",
              "    load_libs(css_urls, js_urls, function() {\n",
              "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
              "      run_inline_js();\n",
              "    });\n",
              "  }\n",
              "}(window));"
            ],
            "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(null);\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      if (url in hashes) {\n        element.crossOrigin = \"anonymous\";\n        element.integrity = \"sha384-\" + hashes[url];\n      }\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  \n  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n  var css_urls = [];\n  \n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    function(Bokeh) {\n    \n    \n    }\n  ];\n\n  function run_inline_js() {\n    \n    if (root.Bokeh !== undefined || force === true) {\n      \n    for (var i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "\n",
              "\n",
              "\n",
              "\n",
              "\n",
              "  <div class=\"bk-root\" id=\"8260b7af-73c1-4fb5-b336-3bc8f1da8fee\" data-root-id=\"1005\"></div>\n"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
              "(function(root) {\n",
              "  function embed_document(root) {\n",
              "    \n",
              "  var docs_json = {\"217437e2-4abc-4215-a5e8-21c1d02cbb6e\":{\"roots\":{\"references\":[{\"attributes\":{\"below\":[{\"id\":\"1012\"}],\"center\":[{\"id\":\"1015\"},{\"id\":\"1019\"}],\"left\":[{\"id\":\"1016\"}],\"plot_height\":300,\"renderers\":[{\"id\":\"1037\"},{\"id\":\"1042\"},{\"id\":\"1047\"}],\"title\":{\"id\":\"1049\"},\"toolbar\":{\"id\":\"1027\"},\"x_range\":{\"id\":\"1003\"},\"x_scale\":{\"id\":\"1008\"},\"y_range\":{\"id\":\"1004\"},\"y_scale\":{\"id\":\"1010\"}},\"id\":\"1005\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"bounds\":[0,100],\"end\":20},\"id\":\"1003\",\"type\":\"Range1d\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_inspect\":\"auto\",\"active_multi\":null,\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"1020\"},{\"id\":\"1021\"},{\"id\":\"1022\"},{\"id\":\"1023\"},{\"id\":\"1024\"},{\"id\":\"1025\"}]},\"id\":\"1027\",\"type\":\"Toolbar\"},{\"attributes\":{\"data\":{\"N\":[26821,2601,329,78,31,10,10,6,3,2,2,1,1,1,1,1,1,1,1,1,1],\"samples\":[0,1,2,3,4,5,6,7,8,10,14,20,21,23,26,27,71,73,85,124,181]},\"selected\":{\"id\":\"1055\"},\"selection_policy\":{\"id\":\"1056\"}},\"id\":\"1002\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"1020\",\"type\":\"PanTool\"},{\"attributes\":{\"line_color\":\"orange\",\"x\":{\"field\":\"samples\"},\"y\":{\"field\":\"N\"}},\"id\":\"1045\",\"type\":\"Line\"},{\"attributes\":{},\"id\":\"1021\",\"type\":\"WheelZoomTool\"},{\"attributes\":{},\"id\":\"1008\",\"type\":\"LinearScale\"},{\"attributes\":{\"ticker\":null},\"id\":\"1052\",\"type\":\"LogTickFormatter\"},{\"attributes\":{\"overlay\":{\"id\":\"1026\"}},\"id\":\"1022\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"axis_label\":\"# Samples sharing a 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variants\",\"formatter\":{\"id\":\"1052\"},\"ticker\":{\"id\":\"1017\"}},\"id\":\"1016\",\"type\":\"LogAxis\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"#1f77b4\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"red\"},\"x\":{\"field\":\"samples\"},\"y\":{\"field\":\"N\"}},\"id\":\"1041\",\"type\":\"Circle\"},{\"attributes\":{\"line_alpha\":0.1,\"line_color\":\"orange\",\"x\":{\"field\":\"samples\"},\"y\":{\"field\":\"N\"}},\"id\":\"1046\",\"type\":\"Line\"},{\"attributes\":{\"data\":{\"N\":[25732.11359918629,3865.453442381862,290.33235566965396,14.537816068266125,0.5459641990657412],\"samples\":[0,1,2,3,4]},\"selected\":{\"id\":\"1057\"},\"selection_policy\":{\"id\":\"1058\"}},\"id\":\"1001\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"data_source\":{\"id\":\"1002\"},\"glyph\":{\"id\":\"1035\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1036\"},\"selection_glyph\":null,\"view\":{\"id\":\"1038\"}},\"id\":\"1037\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"1054\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"fill_color\":{\"value\":\"#1f77b4\"},\"line_color\":{\"value\":\"red\"},\"x\":{\"field\":\"samples\"},\"y\":{\"field\":\"N\"}},\"id\":\"1040\",\"type\":\"Circle\"},{\"attributes\":{\"line_alpha\":0.1,\"line_color\":\"red\",\"x\":{\"field\":\"samples\"},\"y\":{\"field\":\"N\"}},\"id\":\"1036\",\"type\":\"Line\"},{\"attributes\":{\"source\":{\"id\":\"1002\"}},\"id\":\"1038\",\"type\":\"CDSView\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":0.5,\"fill_color\":\"lightgrey\",\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":1.0,\"line_color\":\"black\",\"line_dash\":[4,4],\"line_width\":2,\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"1026\",\"type\":\"BoxAnnotation\"},{\"attributes\":{},\"id\":\"1057\",\"type\":\"Selection\"}],\"root_ids\":[\"1005\"]},\"title\":\"Bokeh Application\",\"version\":\"2.1.1\"}};\n",
              "  var render_items = [{\"docid\":\"217437e2-4abc-4215-a5e8-21c1d02cbb6e\",\"root_ids\":[\"1005\"],\"roots\":{\"1005\":\"8260b7af-73c1-4fb5-b336-3bc8f1da8fee\"}}];\n",
              "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
              "\n",
              "  }\n",
              "  if (root.Bokeh !== undefined) {\n",
              "    embed_document(root);\n",
              "  } else {\n",
              "    var attempts = 0;\n",
              "    var timer = setInterval(function(root) {\n",
              "      if (root.Bokeh !== undefined) {\n",
              "        clearInterval(timer);\n",
              "        embed_document(root);\n",
              "      } else {\n",
              "        attempts++;\n",
              "        if (attempts > 100) {\n",
              "          clearInterval(timer);\n",
              "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
              "        }\n",
              "      }\n",
              "    }, 10, root)\n",
              "  }\n",
              "})(window);"
            ],
            "application/vnd.bokehjs_exec.v0+json": ""
          },
          "metadata": {
            "tags": [],
            "application/vnd.bokehjs_exec.v0+json": {
              "id": "1005"
            }
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ciqLP2d3Zf48",
        "outputId": "81d67584-31d3-4856-ba36-fb4065718b0c"
      },
      "source": [
        "for i,item in enumerate(zip(estimate['N'],bySiteCount['N'])):\n",
        "    if i > 0 and item[0]<item[1]:\n",
        "        cutOff = i\n",
        "        print('Sample count cutOff is {}'.format(cutOff))\n",
        "        break\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Sample count cutOff is 2\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4ycuCPJfyJxF"
      },
      "source": [
        "af_by_var = var.groupby(['POS','REF','ALT']).agg({'AF':[np.max],'Sample':['nunique']}).reset_index()\n",
        "# Flatten column index\n",
        "af_by_var.columns = [''.join(col).strip() for col in af_by_var.columns.values]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "132me9FszxaB"
      },
      "source": [
        "var = pd.merge(var,af_by_var, how='left', left_on=['POS','REF','ALT'], right_on=['POS','REF','ALT'])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XIVJPVpy3Nyj"
      },
      "source": [
        "# Use cutOff value to filter varinats using the following logic\n",
        "# If maxAF for a site is < 0.5 and Sample count is below cutOff -> remove this site\n",
        "# Remove ALL sites where sample count is less than 2\n",
        "var = var[~((var['AFamax']<0.5) & (var['Samplenunique']<=cutOff))]\n",
        "var = var[var['Samplenunique']>1]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XJqJwxwpPSYK"
      },
      "source": [
        "# Create site-specific table\n",
        "sites = var.groupby(['POS','REF','ALT','FUNCLASS','TRID','GENE','AA','change']).agg({'DP':[list],'AF':[list,np.std,np.min,np.max,np.mean],'Sample':[list,'nunique']}).reset_index()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "x1xx5sM2Z1cq"
      },
      "source": [
        "# Flatten column index\n",
        "sites.columns = [''.join(col).strip() for col in sites.columns.values]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "718xRL8HaXaZ"
      },
      "source": [
        "# Compute Coefficient of Variation (CoV)\n",
        "sites['CoV'] = sites['AFstd']/sites['AFmean']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MeZNPTtht5v5"
      },
      "source": [
        "## Descriptive stats"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "i1agZpgS7OuP",
        "outputId": "d9fc2d80-0fe5-4ad3-b872-6cb21334a7d7"
      },
      "source": [
        "# Numbers of variants, sites, samples:\n",
        "site_stats(var)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(34813, 1795, 1818)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "p93_-WoiseIW"
      },
      "source": [
        "changes = sites[( sites['REF'].str.len()==1 ) & (sites['ALT'].str.len()==1)].groupby(['REF','ALT']).agg({'Samplenunique':np.sum}).reset_index()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 421
        },
        "id": "QyBBmaYSuBch",
        "outputId": "30b7cac0-c4d6-4706-9809-833a00515f42"
      },
      "source": [
        "changes"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>REF</th>\n",
              "      <th>ALT</th>\n",
              "      <th>Samplenunique</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>A</td>\n",
              "      <td>C</td>\n",
              "      <td>79</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>A</td>\n",
              "      <td>G</td>\n",
              "      <td>2965</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>A</td>\n",
              "      <td>T</td>\n",
              "      <td>361</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>C</td>\n",
              "      <td>A</td>\n",
              "      <td>307</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>C</td>\n",
              "      <td>G</td>\n",
              "      <td>1281</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>C</td>\n",
              "      <td>T</td>\n",
              "      <td>18521</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>G</td>\n",
              "      <td>A</td>\n",
              "      <td>1318</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>G</td>\n",
              "      <td>C</td>\n",
              "      <td>1900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>G</td>\n",
              "      <td>T</td>\n",
              "      <td>4867</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>T</td>\n",
              "      <td>A</td>\n",
              "      <td>147</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>T</td>\n",
              "      <td>C</td>\n",
              "      <td>2318</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>T</td>\n",
              "      <td>G</td>\n",
              "      <td>75</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   REF ALT  Samplenunique\n",
              "0    A   C             79\n",
              "1    A   G           2965\n",
              "2    A   T            361\n",
              "3    C   A            307\n",
              "4    C   G           1281\n",
              "5    C   T          18521\n",
              "6    G   A           1318\n",
              "7    G   C           1900\n",
              "8    G   T           4867\n",
              "9    T   A            147\n",
              "10   T   C           2318\n",
              "11   T   G             75"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 317
        },
        "id": "3g0-JhYRt0j3",
        "outputId": "2c910a0b-03c3-47bd-a16e-39fe9df04c01"
      },
      "source": [
        "from bokeh.palettes import Viridis256\n",
        "from bokeh.models.annotations import Title,Label, LabelSet\n",
        "from bokeh.transform import transform\n",
        "\n",
        "from bokeh.models import (BasicTicker, ColorBar, ColumnDataSource,\n",
        "                          LogColorMapper, PrintfTickFormatter,LinearColorMapper,ContinuousColorMapper,LogTicker)\n",
        "\n",
        "colors_tile = list(reversed(Viridis256))\n",
        "colors_font = Viridis256\n",
        "\n",
        "source=ColumnDataSource(changes)\n",
        "mapper_tile = LogColorMapper(palette=colors_tile, low=changes['Samplenunique'].min(), high=changes['Samplenunique'].max())\n",
        "mapper_font = LogColorMapper(palette=colors_font, low=changes['Samplenunique'].min(), high=changes['Samplenunique'].max())\n",
        "\n",
        "TOOLTIPS = [\n",
        "            (\"Count\",\"@Samplenunique\")\n",
        "]\n",
        "p = figure(\n",
        "    plot_width=400,\n",
        "    plot_height=300,\n",
        "    x_range=['A','C','T','G'],\n",
        "    y_range=['A','C','T','G'],\n",
        "    x_axis_label = 'Reference base',\n",
        "    y_axis_label = 'Alternative base',\n",
        "    tooltips=TOOLTIPS,\n",
        "\n",
        "\n",
        ")\n",
        "\n",
        "p.rect(\n",
        "    x='REF',\n",
        "    y='ALT',\n",
        "    source=source,\n",
        "    width=1, \n",
        "    height=1, \n",
        "    line_color=None,\n",
        "    fill_color=transform('Samplenunique', mapper_tile)\n",
        ")\n",
        "color_bar = ColorBar(\n",
        "    color_mapper=mapper_tile, \n",
        "    location=(0, 0),\n",
        "    ticker=LogTicker(),\n",
        "    label_standoff=12,\n",
        "    formatter=PrintfTickFormatter(format=\"%d\")\n",
        "    )\n",
        "t = Title()\n",
        "t.text = \"Frequencies of different substitutions in {} dataset\".format(dataset.capitalize())\n",
        "p.title = t\n",
        "labels = LabelSet(x='REF', y='ALT', text='Samplenunique',\n",
        "              x_offset=-15, y_offset=15, source=source, render_mode='canvas',text_color='white',text_font_size='7pt',)\n",
        "p.add_layout(labels)\n",
        "\n",
        "p.add_layout(color_bar, 'right')\n",
        "p.axis.axis_line_color = None\n",
        "p.axis.major_tick_line_color = None\n",
        "p.ygrid.grid_line_color = None\n",
        "p.xgrid.grid_line_color = None\n",
        "output_file(\"substitutions_types_{}.html\".format(dataset))\n",
        "show(p)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
              "\n",
              "(function(root) {\n",
              "  function now() {\n",
              "    return new Date();\n",
              "  }\n",
              "\n",
              "  var force = true;\n",
              "\n",
              "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
              "    root._bokeh_onload_callbacks = [];\n",
              "    root._bokeh_is_loading = undefined;\n",
              "  }\n",
              "\n",
              "  var JS_MIME_TYPE = 'application/javascript';\n",
              "  var HTML_MIME_TYPE = 'text/html';\n",
              "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
              "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
              "\n",
              "  /**\n",
              "   * Render data to the DOM node\n",
              "   */\n",
              "  function render(props, node) {\n",
              "    var script = document.createElement(\"script\");\n",
              "    node.appendChild(script);\n",
              "  }\n",
              "\n",
              "  /**\n",
              "   * Handle when an output is cleared or removed\n",
              "   */\n",
              "  function handleClearOutput(event, handle) {\n",
              "    var cell = handle.cell;\n",
              "\n",
              "    var id = cell.output_area._bokeh_element_id;\n",
              "    var server_id = cell.output_area._bokeh_server_id;\n",
              "    // Clean up Bokeh references\n",
              "    if (id != null && id in Bokeh.index) {\n",
              "      Bokeh.index[id].model.document.clear();\n",
              "      delete Bokeh.index[id];\n",
              "    }\n",
              "\n",
              "    if (server_id !== undefined) {\n",
              "      // Clean up Bokeh references\n",
              "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
              "      cell.notebook.kernel.execute(cmd, {\n",
              "        iopub: {\n",
              "          output: function(msg) {\n",
              "            var id = msg.content.text.trim();\n",
              "            if (id in Bokeh.index) {\n",
              "              Bokeh.index[id].model.document.clear();\n",
              "              delete Bokeh.index[id];\n",
              "            }\n",
              "          }\n",
              "        }\n",
              "      });\n",
              "      // Destroy server and session\n",
              "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
              "      cell.notebook.kernel.execute(cmd);\n",
              "    }\n",
              "  }\n",
              "\n",
              "  /**\n",
              "   * Handle when a new output is added\n",
              "   */\n",
              "  function handleAddOutput(event, handle) {\n",
              "    var output_area = handle.output_area;\n",
              "    var output = handle.output;\n",
              "\n",
              "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
              "    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
              "      return\n",
              "    }\n",
              "\n",
              "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
              "\n",
              "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
              "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
              "      // store reference to embed id on output_area\n",
              "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
              "    }\n",
              "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
              "      var bk_div = document.createElement(\"div\");\n",
              "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
              "      var script_attrs = bk_div.children[0].attributes;\n",
              "      for (var i = 0; i < script_attrs.length; i++) {\n",
              "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
              "        toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n",
              "      }\n",
              "      // store reference to server id on output_area\n",
              "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
              "    }\n",
              "  }\n",
              "\n",
              "  function register_renderer(events, OutputArea) {\n",
              "\n",
              "    function append_mime(data, metadata, element) {\n",
              "      // create a DOM node to render to\n",
              "      var toinsert = this.create_output_subarea(\n",
              "        metadata,\n",
              "        CLASS_NAME,\n",
              "        EXEC_MIME_TYPE\n",
              "      );\n",
              "      this.keyboard_manager.register_events(toinsert);\n",
              "      // Render to node\n",
              "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
              "      render(props, toinsert[toinsert.length - 1]);\n",
              "      element.append(toinsert);\n",
              "      return toinsert\n",
              "    }\n",
              "\n",
              "    /* Handle when an output is cleared or removed */\n",
              "    events.on('clear_output.CodeCell', handleClearOutput);\n",
              "    events.on('delete.Cell', handleClearOutput);\n",
              "\n",
              "    /* Handle when a new output is added */\n",
              "    events.on('output_added.OutputArea', handleAddOutput);\n",
              "\n",
              "    /**\n",
              "     * Register the mime type and append_mime function with output_area\n",
              "     */\n",
              "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
              "      /* Is output safe? */\n",
              "      safe: true,\n",
              "      /* Index of renderer in `output_area.display_order` */\n",
              "      index: 0\n",
              "    });\n",
              "  }\n",
              "\n",
              "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
              "  if (root.Jupyter !== undefined) {\n",
              "    var events = require('base/js/events');\n",
              "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
              "\n",
              "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
              "      register_renderer(events, OutputArea);\n",
              "    }\n",
              "  }\n",
              "\n",
              "  \n",
              "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
              "    root._bokeh_timeout = Date.now() + 5000;\n",
              "    root._bokeh_failed_load = false;\n",
              "  }\n",
              "\n",
              "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
              "     \"<div style='background-color: #fdd'>\\n\"+\n",
              "     \"<p>\\n\"+\n",
              "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
              "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
              "     \"</p>\\n\"+\n",
              "     \"<ul>\\n\"+\n",
              "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
              "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
              "     \"</ul>\\n\"+\n",
              "     \"<code>\\n\"+\n",
              "     \"from bokeh.resources import INLINE\\n\"+\n",
              "     \"output_notebook(resources=INLINE)\\n\"+\n",
              "     \"</code>\\n\"+\n",
              "     \"</div>\"}};\n",
              "\n",
              "  function display_loaded() {\n",
              "    var el = document.getElementById(null);\n",
              "    if (el != null) {\n",
              "      el.textContent = \"BokehJS is loading...\";\n",
              "    }\n",
              "    if (root.Bokeh !== undefined) {\n",
              "      if (el != null) {\n",
              "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
              "      }\n",
              "    } else if (Date.now() < root._bokeh_timeout) {\n",
              "      setTimeout(display_loaded, 100)\n",
              "    }\n",
              "  }\n",
              "\n",
              "\n",
              "  function run_callbacks() {\n",
              "    try {\n",
              "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
              "        if (callback != null)\n",
              "          callback();\n",
              "      });\n",
              "    } finally {\n",
              "      delete root._bokeh_onload_callbacks\n",
              "    }\n",
              "    console.debug(\"Bokeh: all callbacks have finished\");\n",
              "  }\n",
              "\n",
              "  function load_libs(css_urls, js_urls, callback) {\n",
              "    if (css_urls == null) css_urls = [];\n",
              "    if (js_urls == null) js_urls = [];\n",
              "\n",
              "    root._bokeh_onload_callbacks.push(callback);\n",
              "    if (root._bokeh_is_loading > 0) {\n",
              "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
              "      return null;\n",
              "    }\n",
              "    if (js_urls == null || js_urls.length === 0) {\n",
              "      run_callbacks();\n",
              "      return null;\n",
              "    }\n",
              "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
              "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
              "\n",
              "    function on_load() {\n",
              "      root._bokeh_is_loading--;\n",
              "      if (root._bokeh_is_loading === 0) {\n",
              "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
              "        run_callbacks()\n",
              "      }\n",
              "    }\n",
              "\n",
              "    function on_error() {\n",
              "      console.error(\"failed to load \" + url);\n",
              "    }\n",
              "\n",
              "    for (var i = 0; i < css_urls.length; i++) {\n",
              "      var url = css_urls[i];\n",
              "      const element = document.createElement(\"link\");\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error;\n",
              "      element.rel = \"stylesheet\";\n",
              "      element.type = \"text/css\";\n",
              "      element.href = url;\n",
              "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
              "      document.body.appendChild(element);\n",
              "    }\n",
              "\n",
              "    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n",
              "\n",
              "    for (var i = 0; i < js_urls.length; i++) {\n",
              "      var url = js_urls[i];\n",
              "      var element = document.createElement('script');\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error;\n",
              "      element.async = false;\n",
              "      element.src = url;\n",
              "      if (url in hashes) {\n",
              "        element.crossOrigin = \"anonymous\";\n",
              "        element.integrity = \"sha384-\" + hashes[url];\n",
              "      }\n",
              "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
              "      document.head.appendChild(element);\n",
              "    }\n",
              "  };\n",
              "\n",
              "  function inject_raw_css(css) {\n",
              "    const element = document.createElement(\"style\");\n",
              "    element.appendChild(document.createTextNode(css));\n",
              "    document.body.appendChild(element);\n",
              "  }\n",
              "\n",
              "  \n",
              "  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n",
              "  var css_urls = [];\n",
              "  \n",
              "\n",
              "  var inline_js = [\n",
              "    function(Bokeh) {\n",
              "      Bokeh.set_log_level(\"info\");\n",
              "    },\n",
              "    function(Bokeh) {\n",
              "    \n",
              "    \n",
              "    }\n",
              "  ];\n",
              "\n",
              "  function run_inline_js() {\n",
              "    \n",
              "    if (root.Bokeh !== undefined || force === true) {\n",
              "      \n",
              "    for (var i = 0; i < inline_js.length; i++) {\n",
              "      inline_js[i].call(root, root.Bokeh);\n",
              "    }\n",
              "    } else if (Date.now() < root._bokeh_timeout) {\n",
              "      setTimeout(run_inline_js, 100);\n",
              "    } else if (!root._bokeh_failed_load) {\n",
              "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
              "      root._bokeh_failed_load = true;\n",
              "    } else if (force !== true) {\n",
              "      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n",
              "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
              "    }\n",
              "\n",
              "  }\n",
              "\n",
              "  if (root._bokeh_is_loading === 0) {\n",
              "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
              "    run_inline_js();\n",
              "  } else {\n",
              "    load_libs(css_urls, js_urls, function() {\n",
              "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
              "      run_inline_js();\n",
              "    });\n",
              "  }\n",
              "}(window));"
            ],
            "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(null);\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      if (url in hashes) {\n        element.crossOrigin = \"anonymous\";\n        element.integrity = \"sha384-\" + hashes[url];\n      }\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  \n  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n  var css_urls = [];\n  \n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    function(Bokeh) {\n    \n    \n    }\n  ];\n\n  function run_inline_js() {\n    \n    if (root.Bokeh !== undefined || force === true) {\n      \n    for (var i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "\n",
              "\n",
              "\n",
              "\n",
              "\n",
              "  <div class=\"bk-root\" id=\"6e518510-66d3-4364-a769-70ece7a486c8\" data-root-id=\"1251\"></div>\n"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
              "(function(root) {\n",
              "  function embed_document(root) {\n",
              "    \n",
              "  var docs_json = {\"3ec3c599-0517-43de-a889-96ceaa8e2f26\":{\"roots\":{\"references\":[{\"attributes\":{\"below\":[{\"id\":\"1260\"}],\"center\":[{\"id\":\"1262\"},{\"id\":\"1265\"},{\"id\":\"1294\"}],\"left\":[{\"id\":\"1263\"}],\"plot_height\":300,\"plot_width\":400,\"renderers\":[{\"id\":\"1285\"}],\"right\":[{\"id\":\"1289\"}],\"title\":{\"id\":\"1292\"},\"toolbar\":{\"id\":\"1274\"},\"x_range\":{\"id\":\"1252\"},\"x_scale\":{\"id\":\"1256\"},\"y_range\":{\"id\":\"1254\"},\"y_scale\":{\"id\":\"1258\"}},\"id\":\"1251\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"color_mapper\":{\"id\":\"1249\"},\"formatter\":{\"id\":\"1288\"},\"label_standoff\":12,\"location\":[0,0],\"ticker\":{\"id\":\"1287\"}},\"id\":\"1289\",\"type\":\"ColorBar\"},{\"attributes\":{\"overlay\":{\"id\":\"1272\"}},\"id\":\"1268\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"axis\":{\"id\":\"1263\"},\"dimension\":1,\"grid_line_color\":null,\"ticker\":null},\"id\":\"1265\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"1271\",\"type\":\"HelpTool\"},{\"attributes\":{},\"id\":\"1266\",\"type\":\"PanTool\"},{\"attributes\":{},\"id\":\"1270\",\"type\":\"ResetTool\"},{\"attributes\":{\"axis_label\":\"Alternative 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\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"field\":\"Samplenunique\",\"transform\":{\"id\":\"1249\"}},\"height\":{\"units\":\"data\",\"value\":1},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":null},\"width\":{\"units\":\"data\",\"value\":1},\"x\":{\"field\":\"REF\"},\"y\":{\"field\":\"ALT\"}},\"id\":\"1284\",\"type\":\"Rect\"},{\"attributes\":{\"data_source\":{\"id\":\"1248\"},\"glyph\":{\"id\":\"1283\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1284\"},\"selection_glyph\":null,\"view\":{\"id\":\"1286\"}},\"id\":\"1285\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"1287\",\"type\":\"LogTicker\"},{\"attributes\":{},\"id\":\"1312\",\"type\":\"Selection\"},{\"attributes\":{\"factors\":[\"A\",\"C\",\"T\",\"G\"]},\"id\":\"1252\",\"type\":\"FactorRange\"},{\"attributes\":{},\"id\":\"1256\",\"type\":\"CategoricalScale\"},{\"attributes\":{\"factors\":[\"A\",\"C\",\"T\",\"G\"]},\"id\":\"1254\",\"type\":\"FactorRange\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":0.5,\"fill_color\":\"lightgrey\",\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":1.0,\"line_color\":\"black\",\"line_dash\":[4,4],\"line_width\":2,\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"1272\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"source\":{\"id\":\"1248\"}},\"id\":\"1286\",\"type\":\"CDSView\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_inspect\":\"auto\",\"active_multi\":null,\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"1266\"},{\"id\":\"1267\"},{\"id\":\"1268\"},{\"id\":\"1269\"},{\"id\":\"1270\"},{\"id\":\"1271\"},{\"id\":\"1273\"}]},\"id\":\"1274\",\"type\":\"Toolbar\"},{\"attributes\":{\"text\":\"Frequencies of different substitutions in Cog-post dataset\"},\"id\":\"1292\",\"type\":\"Title\"},{\"attributes\":{},\"id\":\"1258\",\"type\":\"CategoricalScale\"},{\"attributes\":{\"axis\":{\"id\":\"1260\"},\"grid_line_color\":null,\"ticker\":null},\"id\":\"1262\",\"type\":\"Grid\"},{\"attributes\":{\"axis_label\":\"Reference base\",\"axis_line_color\":null,\"formatter\":{\"id\":\"1311\"},\"major_tick_line_color\":null,\"ticker\":{\"id\":\"1261\"}},\"id\":\"1260\",\"type\":\"CategoricalAxis\"},{\"attributes\":{},\"id\":\"1261\",\"type\":\"CategoricalTicker\"}],\"root_ids\":[\"1251\"]},\"title\":\"Bokeh Application\",\"version\":\"2.1.1\"}};\n",
              "  var render_items = [{\"docid\":\"3ec3c599-0517-43de-a889-96ceaa8e2f26\",\"root_ids\":[\"1251\"],\"roots\":{\"1251\":\"6e518510-66d3-4364-a769-70ece7a486c8\"}}];\n",
              "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
              "\n",
              "  }\n",
              "  if (root.Bokeh !== undefined) {\n",
              "    embed_document(root);\n",
              "  } else {\n",
              "    var attempts = 0;\n",
              "    var timer = setInterval(function(root) {\n",
              "      if (root.Bokeh !== undefined) {\n",
              "        clearInterval(timer);\n",
              "        embed_document(root);\n",
              "      } else {\n",
              "        attempts++;\n",
              "        if (attempts > 100) {\n",
              "          clearInterval(timer);\n",
              "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
              "        }\n",
              "      }\n",
              "    }, 10, root)\n",
              "  }\n",
              "})(window);"
            ],
            "application/vnd.bokehjs_exec.v0+json": ""
          },
          "metadata": {
            "tags": [],
            "application/vnd.bokehjs_exec.v0+json": {
              "id": "1251"
            }
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 317
        },
        "id": "5wN6DbVxUDgm",
        "outputId": "0600c089-2cc2-41de-e4aa-ba503f8919ca"
      },
      "source": [
        "import collections\n",
        "colors = {'Synonymous':'green','Non-synonymous':'orange','Stop':'red','Non-coding':'blue', 'Indel':'magenta'}\n",
        "\n",
        "srcs = {}\n",
        "\n",
        "for func in var['FUNCLASS'].unique():\n",
        "    srcs[func]=create_hist(var[var['FUNCLASS']==func],'AF')\n",
        "\n",
        "srcs = collections.OrderedDict(sorted(srcs.items()))\n",
        "\n",
        "plot = figure(\n",
        "    plot_height = 300, \n",
        "    plot_width = 600,\n",
        "    x_axis_label = 'AF',\n",
        "    y_axis_label = \"Count\"\n",
        "    )  \n",
        "\n",
        "site_count_total = 0\n",
        "unique_site_count_total = 0\n",
        "\n",
        "for i,key in enumerate(srcs):\n",
        "    site_count = len(var[var['FUNCLASS']==key])\n",
        "    #unique_site_count = len(pysqldf('select (POS || REF || ALT),count(distinct (POS || REF || ALT)) as N from var where FUNCLASS = \"{}\" group by POS, REF, ALT order by N desc'.format(key)))\n",
        "    unique_site_count = len(var[var['FUNCLASS']==key].groupby(['POS','ALT','REF']).groups)\n",
        "    plot.quad(\n",
        "        bottom = 0, \n",
        "        top = 'AF',\n",
        "        left = \"left\", \n",
        "        right = \"right\", \n",
        "        source = srcs[key], \n",
        "        fill_color = colors[key],\n",
        "        line_color = \"black\", \n",
        "        fill_alpha = 0.4,\n",
        "        legend_label='{} (all = {}, distinct = {})'.format(key,site_count,unique_site_count)\n",
        "        )\n",
        "    site_count_total += site_count\n",
        "    unique_site_count_total += unique_site_count\n",
        "plot.legend.click_policy=\"hide\"\n",
        "plot.legend.location = \"top_center\"\n",
        "t = Title()\n",
        "t.text = \"Histogram of Allele Frequencies for {} dataset (all = {}, distinct = {})\".format(dataset.capitalize(),site_count_total,unique_site_count_total)\n",
        "plot.title = t\n",
        "output_file(\"af_histogram_{}.html\".format(dataset))\n",
        "show(plot)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
              "\n",
              "(function(root) {\n",
              "  function now() {\n",
              "    return new Date();\n",
              "  }\n",
              "\n",
              "  var force = true;\n",
              "\n",
              "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
              "    root._bokeh_onload_callbacks = [];\n",
              "    root._bokeh_is_loading = undefined;\n",
              "  }\n",
              "\n",
              "  var JS_MIME_TYPE = 'application/javascript';\n",
              "  var HTML_MIME_TYPE = 'text/html';\n",
              "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
              "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
              "\n",
              "  /**\n",
              "   * Render data to the DOM node\n",
              "   */\n",
              "  function render(props, node) {\n",
              "    var script = document.createElement(\"script\");\n",
              "    node.appendChild(script);\n",
              "  }\n",
              "\n",
              "  /**\n",
              "   * Handle when an output is cleared or removed\n",
              "   */\n",
              "  function handleClearOutput(event, handle) {\n",
              "    var cell = handle.cell;\n",
              "\n",
              "    var id = cell.output_area._bokeh_element_id;\n",
              "    var server_id = cell.output_area._bokeh_server_id;\n",
              "    // Clean up Bokeh references\n",
              "    if (id != null && id in Bokeh.index) {\n",
              "      Bokeh.index[id].model.document.clear();\n",
              "      delete Bokeh.index[id];\n",
              "    }\n",
              "\n",
              "    if (server_id !== undefined) {\n",
              "      // Clean up Bokeh references\n",
              "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
              "      cell.notebook.kernel.execute(cmd, {\n",
              "        iopub: {\n",
              "          output: function(msg) {\n",
              "            var id = msg.content.text.trim();\n",
              "            if (id in Bokeh.index) {\n",
              "              Bokeh.index[id].model.document.clear();\n",
              "              delete Bokeh.index[id];\n",
              "            }\n",
              "          }\n",
              "        }\n",
              "      });\n",
              "      // Destroy server and session\n",
              "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
              "      cell.notebook.kernel.execute(cmd);\n",
              "    }\n",
              "  }\n",
              "\n",
              "  /**\n",
              "   * Handle when a new output is added\n",
              "   */\n",
              "  function handleAddOutput(event, handle) {\n",
              "    var output_area = handle.output_area;\n",
              "    var output = handle.output;\n",
              "\n",
              "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
              "    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
              "      return\n",
              "    }\n",
              "\n",
              "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
              "\n",
              "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
              "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
              "      // store reference to embed id on output_area\n",
              "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
              "    }\n",
              "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
              "      var bk_div = document.createElement(\"div\");\n",
              "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
              "      var script_attrs = bk_div.children[0].attributes;\n",
              "      for (var i = 0; i < script_attrs.length; i++) {\n",
              "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
              "        toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n",
              "      }\n",
              "      // store reference to server id on output_area\n",
              "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
              "    }\n",
              "  }\n",
              "\n",
              "  function register_renderer(events, OutputArea) {\n",
              "\n",
              "    function append_mime(data, metadata, element) {\n",
              "      // create a DOM node to render to\n",
              "      var toinsert = this.create_output_subarea(\n",
              "        metadata,\n",
              "        CLASS_NAME,\n",
              "        EXEC_MIME_TYPE\n",
              "      );\n",
              "      this.keyboard_manager.register_events(toinsert);\n",
              "      // Render to node\n",
              "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
              "      render(props, toinsert[toinsert.length - 1]);\n",
              "      element.append(toinsert);\n",
              "      return toinsert\n",
              "    }\n",
              "\n",
              "    /* Handle when an output is cleared or removed */\n",
              "    events.on('clear_output.CodeCell', handleClearOutput);\n",
              "    events.on('delete.Cell', handleClearOutput);\n",
              "\n",
              "    /* Handle when a new output is added */\n",
              "    events.on('output_added.OutputArea', handleAddOutput);\n",
              "\n",
              "    /**\n",
              "     * Register the mime type and append_mime function with output_area\n",
              "     */\n",
              "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
              "      /* Is output safe? */\n",
              "      safe: true,\n",
              "      /* Index of renderer in `output_area.display_order` */\n",
              "      index: 0\n",
              "    });\n",
              "  }\n",
              "\n",
              "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
              "  if (root.Jupyter !== undefined) {\n",
              "    var events = require('base/js/events');\n",
              "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
              "\n",
              "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
              "      register_renderer(events, OutputArea);\n",
              "    }\n",
              "  }\n",
              "\n",
              "  \n",
              "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
              "    root._bokeh_timeout = Date.now() + 5000;\n",
              "    root._bokeh_failed_load = false;\n",
              "  }\n",
              "\n",
              "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
              "     \"<div style='background-color: #fdd'>\\n\"+\n",
              "     \"<p>\\n\"+\n",
              "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
              "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
              "     \"</p>\\n\"+\n",
              "     \"<ul>\\n\"+\n",
              "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
              "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
              "     \"</ul>\\n\"+\n",
              "     \"<code>\\n\"+\n",
              "     \"from bokeh.resources import INLINE\\n\"+\n",
              "     \"output_notebook(resources=INLINE)\\n\"+\n",
              "     \"</code>\\n\"+\n",
              "     \"</div>\"}};\n",
              "\n",
              "  function display_loaded() {\n",
              "    var el = document.getElementById(null);\n",
              "    if (el != null) {\n",
              "      el.textContent = \"BokehJS is loading...\";\n",
              "    }\n",
              "    if (root.Bokeh !== undefined) {\n",
              "      if (el != null) {\n",
              "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
              "      }\n",
              "    } else if (Date.now() < root._bokeh_timeout) {\n",
              "      setTimeout(display_loaded, 100)\n",
              "    }\n",
              "  }\n",
              "\n",
              "\n",
              "  function run_callbacks() {\n",
              "    try {\n",
              "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
              "        if (callback != null)\n",
              "          callback();\n",
              "      });\n",
              "    } finally {\n",
              "      delete root._bokeh_onload_callbacks\n",
              "    }\n",
              "    console.debug(\"Bokeh: all callbacks have finished\");\n",
              "  }\n",
              "\n",
              "  function load_libs(css_urls, js_urls, callback) {\n",
              "    if (css_urls == null) css_urls = [];\n",
              "    if (js_urls == null) js_urls = [];\n",
              "\n",
              "    root._bokeh_onload_callbacks.push(callback);\n",
              "    if (root._bokeh_is_loading > 0) {\n",
              "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
              "      return null;\n",
              "    }\n",
              "    if (js_urls == null || js_urls.length === 0) {\n",
              "      run_callbacks();\n",
              "      return null;\n",
              "    }\n",
              "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
              "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
              "\n",
              "    function on_load() {\n",
              "      root._bokeh_is_loading--;\n",
              "      if (root._bokeh_is_loading === 0) {\n",
              "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
              "        run_callbacks()\n",
              "      }\n",
              "    }\n",
              "\n",
              "    function on_error() {\n",
              "      console.error(\"failed to load \" + url);\n",
              "    }\n",
              "\n",
              "    for (var i = 0; i < css_urls.length; i++) {\n",
              "      var url = css_urls[i];\n",
              "      const element = document.createElement(\"link\");\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error;\n",
              "      element.rel = \"stylesheet\";\n",
              "      element.type = \"text/css\";\n",
              "      element.href = url;\n",
              "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
              "      document.body.appendChild(element);\n",
              "    }\n",
              "\n",
              "    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n",
              "\n",
              "    for (var i = 0; i < js_urls.length; i++) {\n",
              "      var url = js_urls[i];\n",
              "      var element = document.createElement('script');\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error;\n",
              "      element.async = false;\n",
              "      element.src = url;\n",
              "      if (url in hashes) {\n",
              "        element.crossOrigin = \"anonymous\";\n",
              "        element.integrity = \"sha384-\" + hashes[url];\n",
              "      }\n",
              "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
              "      document.head.appendChild(element);\n",
              "    }\n",
              "  };\n",
              "\n",
              "  function inject_raw_css(css) {\n",
              "    const element = document.createElement(\"style\");\n",
              "    element.appendChild(document.createTextNode(css));\n",
              "    document.body.appendChild(element);\n",
              "  }\n",
              "\n",
              "  \n",
              "  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n",
              "  var css_urls = [];\n",
              "  \n",
              "\n",
              "  var inline_js = [\n",
              "    function(Bokeh) {\n",
              "      Bokeh.set_log_level(\"info\");\n",
              "    },\n",
              "    function(Bokeh) {\n",
              "    \n",
              "    \n",
              "    }\n",
              "  ];\n",
              "\n",
              "  function run_inline_js() {\n",
              "    \n",
              "    if (root.Bokeh !== undefined || force === true) {\n",
              "      \n",
              "    for (var i = 0; i < inline_js.length; i++) {\n",
              "      inline_js[i].call(root, root.Bokeh);\n",
              "    }\n",
              "    } else if (Date.now() < root._bokeh_timeout) {\n",
              "      setTimeout(run_inline_js, 100);\n",
              "    } else if (!root._bokeh_failed_load) {\n",
              "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
              "      root._bokeh_failed_load = true;\n",
              "    } else if (force !== true) {\n",
              "      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n",
              "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
              "    }\n",
              "\n",
              "  }\n",
              "\n",
              "  if (root._bokeh_is_loading === 0) {\n",
              "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
              "    run_inline_js();\n",
              "  } else {\n",
              "    load_libs(css_urls, js_urls, function() {\n",
              "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
              "      run_inline_js();\n",
              "    });\n",
              "  }\n",
              "}(window));"
            ],
            "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(null);\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      if (url in hashes) {\n        element.crossOrigin = \"anonymous\";\n        element.integrity = \"sha384-\" + hashes[url];\n      }\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  \n  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n  var css_urls = [];\n  \n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    function(Bokeh) {\n    \n    \n    }\n  ];\n\n  function run_inline_js() {\n    \n    if (root.Bokeh !== undefined || force === true) {\n      \n    for (var i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
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            "tags": []
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          "data": {
            "text/html": [
              "\n",
              "\n",
              "\n",
              "\n",
              "\n",
              "\n",
              "  <div class=\"bk-root\" id=\"5fdb3a8f-5ff0-4339-bf25-884bcc385ed6\" data-root-id=\"1468\"></div>\n"
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          },
          "metadata": {
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Application\",\"version\":\"2.1.1\"}};\n",
              "  var render_items = [{\"docid\":\"625ab808-e5ec-4921-8795-519bd387638e\",\"root_ids\":[\"1468\"],\"roots\":{\"1468\":\"5fdb3a8f-5ff0-4339-bf25-884bcc385ed6\"}}];\n",
              "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
              "\n",
              "  }\n",
              "  if (root.Bokeh !== undefined) {\n",
              "    embed_document(root);\n",
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              "        attempts++;\n",
              "        if (attempts > 100) {\n",
              "          clearInterval(timer);\n",
              "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
              "        }\n",
              "      }\n",
              "    }, 10, root)\n",
              "  }\n",
              "})(window);"
            ],
            "application/vnd.bokehjs_exec.v0+json": ""
          },
          "metadata": {
            "tags": [],
            "application/vnd.bokehjs_exec.v0+json": {
              "id": "1468"
            }
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "u5FSHmoGkPU6",
        "outputId": "9d9489cc-4400-4775-fcde-27b5edf9274a"
      },
      "source": [
        "for bounds in [[0,0.1],[0.1,0.8],[0.8,1]]:\n",
        "    print(pysqldf('select Sample, count(*) as \"{0}-{1}\" from var where AF >= {0} and AF < {1} group by Sample '.format(bounds[0],bounds[1])).describe().loc[['count','mean','min','max']].T.to_markdown())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "|       |   count |    mean |   min |   max |\n",
            "|:------|--------:|--------:|------:|------:|\n",
            "| 0-0.1 |     474 | 1.98734 |     1 |    17 |\n",
            "|         |   count |    mean |   min |   max |\n",
            "|:--------|--------:|--------:|------:|------:|\n",
            "| 0.1-0.8 |    1789 | 3.77306 |     1 |    29 |\n",
            "|       |   count |    mean |   min |   max |\n",
            "|:------|--------:|--------:|------:|------:|\n",
            "| 0.8-1 |    1818 | 14.8839 |     3 |    34 |\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sZIbTbxmLKni"
      },
      "source": [
        "## Distribution of AFs across samples"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "B0DQi0T7Gxz7",
        "outputId": "998b8254-4e23-4f62-c25f-6702bc222ae5"
      },
      "source": [
        "# DataFrame for plotting AF stats\n",
        "af_plot_data = sites[['POS','REF','ALT','FUNCLASS','AFmean','CoV','Samplenunique']]\n",
        "# Fraction of sample containing a given varinat (aka polulation frequency)\n",
        "af_plot_data.loc[:,('frac')]=af_plot_data['Samplenunique']/var['Sample'].nunique()\n",
        "for key in colors:\n",
        "    af_plot_data.loc[(af_plot_data['FUNCLASS']==key),'color'] = colors[key]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/pandas/core/indexing.py:1596: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  self.obj[key] = _infer_fill_value(value)\n",
            "/usr/local/lib/python3.7/dist-packages/pandas/core/indexing.py:1743: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  isetter(ilocs[0], value)\n",
            "/usr/local/lib/python3.7/dist-packages/pandas/core/indexing.py:1763: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  isetter(loc, value)\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 817
        },
        "id": "w9chlP3pYRVM",
        "outputId": "beb49ff2-e2b1-43bc-8104-40bcec9ffcdd"
      },
      "source": [
        "from bokeh.layouts import row,column\n",
        "\n",
        "af_cov_sample = ColumnDataSource(af_plot_data)\n",
        "\n",
        "TOOLTIPS_p1 = [\n",
        "    (\"(mean,cov)\", \"(@AFmean{(0.000)}, @CoV{(0.000)})\"),\n",
        "    (\"Position\",\"@POS{0,0}\"),\n",
        "    (\"Funclass\",'@FUNCLASS'),\n",
        "    (\"# Samples\",\"@Samplenunique\")\n",
        "]\n",
        "\n",
        "TOOLTIPS_p2 = [\n",
        "        (\"(CoV,PF)\", \"(@CoV{(0.000)}, @frac{(0.000)})\"),\n",
        "        (\"Position\",\"@POS{0,0}\"),\n",
        "        (\"Funclass\",'@FUNCLASS'),\n",
        "        (\"# Samples\",\"@Samplenunique\")\n",
        "]\n",
        "\n",
        "p1 = figure(\n",
        "    plot_height = 400, plot_width = 400,\n",
        "    title = \"AF: Mean versus CoV\",\n",
        "    y_axis_label = 'Coefficient of Variation for AF',\n",
        "    x_axis_label = \"Mean AF\",\n",
        "    tooltips=TOOLTIPS_p1,\n",
        "    #tools='save'\n",
        "    )\n",
        "\n",
        "p1.circle(\n",
        "    y='CoV',\n",
        "    x='AFmean',\n",
        "    color='color',\n",
        "    alpha=.5,\n",
        "    source=af_cov_sample,\n",
        "    size=8\n",
        "    )\n",
        "\n",
        "p2 = figure(\n",
        "    plot_height = 400, \n",
        "    plot_width = 400,\n",
        "    title = \"AF: CoV versus PF\",\n",
        "    x_axis_label = 'Fraction of samples containing a variant (aka PF)',\n",
        "    y_axis_label = 'Coefficient of Variation for AF',\n",
        "    tooltips=TOOLTIPS_p2,\n",
        "    y_range=p1.y_range\n",
        "    #tools='save'\n",
        "    )\n",
        "        \n",
        "p2.circle(\n",
        "    y='CoV',\n",
        "    x='frac',\n",
        "    line_color=None,\n",
        "    fill_color='color',\n",
        "    alpha=.5,\n",
        "    source=af_cov_sample,\n",
        "    size=8\n",
        "    )\n",
        "output_file(\"cov_vs_pf_{}.html\".format(dataset))\n",
        "show(column(p1,p2))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
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              "(function(root) {\n",
              "  function now() {\n",
              "    return new Date();\n",
              "  }\n",
              "\n",
              "  var force = true;\n",
              "\n",
              "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
              "    root._bokeh_onload_callbacks = [];\n",
              "    root._bokeh_is_loading = undefined;\n",
              "  }\n",
              "\n",
              "  var JS_MIME_TYPE = 'application/javascript';\n",
              "  var HTML_MIME_TYPE = 'text/html';\n",
              "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
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              "   */\n",
              "  function render(props, node) {\n",
              "    var script = document.createElement(\"script\");\n",
              "    node.appendChild(script);\n",
              "  }\n",
              "\n",
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              "   * Handle when an output is cleared or removed\n",
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              "\n",
              "    var id = cell.output_area._bokeh_element_id;\n",
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              "    // Clean up Bokeh references\n",
              "    if (id != null && id in Bokeh.index) {\n",
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              "      // Clean up Bokeh references\n",
              "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
              "      cell.notebook.kernel.execute(cmd, {\n",
              "        iopub: {\n",
              "          output: function(msg) {\n",
              "            var id = msg.content.text.trim();\n",
              "            if (id in Bokeh.index) {\n",
              "              Bokeh.index[id].model.document.clear();\n",
              "              delete Bokeh.index[id];\n",
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              "      // Destroy server and session\n",
              "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
              "      cell.notebook.kernel.execute(cmd);\n",
              "    }\n",
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              "    var output_area = handle.output_area;\n",
              "    var output = handle.output;\n",
              "\n",
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              "\n",
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              "\n",
              "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
              "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
              "      // store reference to embed id on output_area\n",
              "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
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              "        toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n",
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              "  function register_renderer(events, OutputArea) {\n",
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              "    function append_mime(data, metadata, element) {\n",
              "      // create a DOM node to render to\n",
              "      var toinsert = this.create_output_subarea(\n",
              "        metadata,\n",
              "        CLASS_NAME,\n",
              "        EXEC_MIME_TYPE\n",
              "      );\n",
              "      this.keyboard_manager.register_events(toinsert);\n",
              "      // Render to node\n",
              "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
              "      render(props, toinsert[toinsert.length - 1]);\n",
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              "\n",
              "    /* Handle when an output is cleared or removed */\n",
              "    events.on('clear_output.CodeCell', handleClearOutput);\n",
              "    events.on('delete.Cell', handleClearOutput);\n",
              "\n",
              "    /* Handle when a new output is added */\n",
              "    events.on('output_added.OutputArea', handleAddOutput);\n",
              "\n",
              "    /**\n",
              "     * Register the mime type and append_mime function with output_area\n",
              "     */\n",
              "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
              "      /* Is output safe? */\n",
              "      safe: true,\n",
              "      /* Index of renderer in `output_area.display_order` */\n",
              "      index: 0\n",
              "    });\n",
              "  }\n",
              "\n",
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              "  if (root.Jupyter !== undefined) {\n",
              "    var events = require('base/js/events');\n",
              "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
              "\n",
              "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
              "      register_renderer(events, OutputArea);\n",
              "    }\n",
              "  }\n",
              "\n",
              "  \n",
              "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
              "    root._bokeh_timeout = Date.now() + 5000;\n",
              "    root._bokeh_failed_load = false;\n",
              "  }\n",
              "\n",
              "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
              "     \"<div style='background-color: #fdd'>\\n\"+\n",
              "     \"<p>\\n\"+\n",
              "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
              "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
              "     \"</p>\\n\"+\n",
              "     \"<ul>\\n\"+\n",
              "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
              "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
              "     \"</ul>\\n\"+\n",
              "     \"<code>\\n\"+\n",
              "     \"from bokeh.resources import INLINE\\n\"+\n",
              "     \"output_notebook(resources=INLINE)\\n\"+\n",
              "     \"</code>\\n\"+\n",
              "     \"</div>\"}};\n",
              "\n",
              "  function display_loaded() {\n",
              "    var el = document.getElementById(null);\n",
              "    if (el != null) {\n",
              "      el.textContent = \"BokehJS is loading...\";\n",
              "    }\n",
              "    if (root.Bokeh !== undefined) {\n",
              "      if (el != null) {\n",
              "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
              "      }\n",
              "    } else if (Date.now() < root._bokeh_timeout) {\n",
              "      setTimeout(display_loaded, 100)\n",
              "    }\n",
              "  }\n",
              "\n",
              "\n",
              "  function run_callbacks() {\n",
              "    try {\n",
              "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
              "        if (callback != null)\n",
              "          callback();\n",
              "      });\n",
              "    } finally {\n",
              "      delete root._bokeh_onload_callbacks\n",
              "    }\n",
              "    console.debug(\"Bokeh: all callbacks have finished\");\n",
              "  }\n",
              "\n",
              "  function load_libs(css_urls, js_urls, callback) {\n",
              "    if (css_urls == null) css_urls = [];\n",
              "    if (js_urls == null) js_urls = [];\n",
              "\n",
              "    root._bokeh_onload_callbacks.push(callback);\n",
              "    if (root._bokeh_is_loading > 0) {\n",
              "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
              "      return null;\n",
              "    }\n",
              "    if (js_urls == null || js_urls.length === 0) {\n",
              "      run_callbacks();\n",
              "      return null;\n",
              "    }\n",
              "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
              "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
              "\n",
              "    function on_load() {\n",
              "      root._bokeh_is_loading--;\n",
              "      if (root._bokeh_is_loading === 0) {\n",
              "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
              "        run_callbacks()\n",
              "      }\n",
              "    }\n",
              "\n",
              "    function on_error() {\n",
              "      console.error(\"failed to load \" + url);\n",
              "    }\n",
              "\n",
              "    for (var i = 0; i < css_urls.length; i++) {\n",
              "      var url = css_urls[i];\n",
              "      const element = document.createElement(\"link\");\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error;\n",
              "      element.rel = \"stylesheet\";\n",
              "      element.type = \"text/css\";\n",
              "      element.href = url;\n",
              "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
              "      document.body.appendChild(element);\n",
              "    }\n",
              "\n",
              "    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n",
              "\n",
              "    for (var i = 0; i < js_urls.length; i++) {\n",
              "      var url = js_urls[i];\n",
              "      var element = document.createElement('script');\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error;\n",
              "      element.async = false;\n",
              "      element.src = url;\n",
              "      if (url in hashes) {\n",
              "        element.crossOrigin = \"anonymous\";\n",
              "        element.integrity = \"sha384-\" + hashes[url];\n",
              "      }\n",
              "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
              "      document.head.appendChild(element);\n",
              "    }\n",
              "  };\n",
              "\n",
              "  function inject_raw_css(css) {\n",
              "    const element = document.createElement(\"style\");\n",
              "    element.appendChild(document.createTextNode(css));\n",
              "    document.body.appendChild(element);\n",
              "  }\n",
              "\n",
              "  \n",
              "  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n",
              "  var css_urls = [];\n",
              "  \n",
              "\n",
              "  var inline_js = [\n",
              "    function(Bokeh) {\n",
              "      Bokeh.set_log_level(\"info\");\n",
              "    },\n",
              "    function(Bokeh) {\n",
              "    \n",
              "    \n",
              "    }\n",
              "  ];\n",
              "\n",
              "  function run_inline_js() {\n",
              "    \n",
              "    if (root.Bokeh !== undefined || force === true) {\n",
              "      \n",
              "    for (var i = 0; i < inline_js.length; i++) {\n",
              "      inline_js[i].call(root, root.Bokeh);\n",
              "    }\n",
              "    } else if (Date.now() < root._bokeh_timeout) {\n",
              "      setTimeout(run_inline_js, 100);\n",
              "    } else if (!root._bokeh_failed_load) {\n",
              "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
              "      root._bokeh_failed_load = true;\n",
              "    } else if (force !== true) {\n",
              "      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n",
              "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
              "    }\n",
              "\n",
              "  }\n",
              "\n",
              "  if (root._bokeh_is_loading === 0) {\n",
              "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
              "    run_inline_js();\n",
              "  } else {\n",
              "    load_libs(css_urls, js_urls, function() {\n",
              "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
              "      run_inline_js();\n",
              "    });\n",
              "  }\n",
              "}(window));"
            ],
            "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(null);\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      if (url in hashes) {\n        element.crossOrigin = \"anonymous\";\n        element.integrity = \"sha384-\" + hashes[url];\n      }\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  \n  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n  var css_urls = [];\n  \n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    function(Bokeh) {\n    \n    \n    }\n  ];\n\n  function run_inline_js() {\n    \n    if (root.Bokeh !== undefined || force === true) {\n      \n    for (var i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "\n",
              "\n",
              "\n",
              "\n",
              "\n",
              "  <div class=\"bk-root\" id=\"2d1ad63e-26da-4673-94bf-825cb3616b9d\" data-root-id=\"2022\"></div>\n"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
              "(function(root) {\n",
              "  function embed_document(root) {\n",
              "    \n",
              "  var docs_json = {\"ab13fb15-417f-43a2-8d17-91bb0722b6e6\":{\"roots\":{\"references\":[{\"attributes\":{\"children\":[{\"id\":\"1943\"},{\"id\":\"1983\"}]},\"id\":\"2022\",\"type\":\"Column\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"field\":\"color\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":null},\"size\":{\"units\":\"screen\",\"value\":8},\"x\":{\"field\":\"frac\"},\"y\":{\"field\":\"CoV\"}},\"id\":\"2019\",\"type\":\"Circle\"},{\"attributes\":{},\"id\":\"1986\",\"type\":\"DataRange1d\"},{\"attributes\":{\"data_source\":{\"id\":\"1942\"},\"glyph\":{\"id\":\"2018\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"2019\"},\"selection_glyph\":null,\"view\":{\"id\":\"2021\"}},\"id\":\"2020\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"2069\",\"type\":\"UnionRenderers\"},{\"attributes\":{\"below\":[{\"id\":\"1993\"}],\"center\":[{\"id\":\"1996\"},{\"id\":\"2000\"}],\"left\":[{\"id\":\"1997\"}],\"plot_height\":400,\"plot_width\":400,\"renderers\":[{\"id\":\"2020\"}],\"title\":{\"id\":\"1984\"},\"toolbar\":{\"id\":\"2009\"},\"x_range\":{\"id\":\"1986\"},\"x_scale\":{\"id\":\"1989\"},\"y_range\":{\"id\":\"1948\"},\"y_scale\":{\"id\":\"1991\"}},\"id\":\"1983\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"field\":\"color\"},\"line_alpha\":{\"value\":0.5},\"line_color\":{\"value\":null},\"size\":{\"units\":\"screen\",\"value\":8},\"x\":{\"field\":\"frac\"},\"y\":{\"field\":\"CoV\"}},\"id\":\"2018\",\"type\":\"Circle\"},{\"attributes\":{},\"id\":\"2068\",\"type\":\"Selection\"},{\"attributes\":{\"below\":[{\"id\":\"1954\"}],\"center\":[{\"id\":\"1957\"},{\"id\":\"1961\"}],\"left\":[{\"id\":\"1958\"}],\"plot_height\":400,\"plot_width\":400,\"renderers\":[{\"id\":\"1981\"}],\"title\":{\"id\":\"1944\"},\"toolbar\":{\"id\":\"1970\"},\"x_range\":{\"id\":\"1946\"},\"x_scale\":{\"id\":\"1950\"},\"y_range\":{\"id\":\"1948\"},\"y_scale\":{\"id\":\"1952\"}},\"id\":\"1943\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":0.5,\"fill_color\":\"lightgrey\",\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":1.0,\"line_color\":\"black\",\"line_dash\":[4,4],\"line_width\":2,\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"2007\",\"type\":\"BoxAnnotation\"},{\"attributes\":{},\"id\":\"1946\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"1950\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"2067\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"axis_label\":\"Coefficient 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PF)\",\"formatter\":{\"id\":\"2067\"},\"ticker\":{\"id\":\"1994\"}},\"id\":\"1993\",\"type\":\"LinearAxis\"},{\"attributes\":{\"axis\":{\"id\":\"1954\"},\"ticker\":null},\"id\":\"1957\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"1963\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"axis_label\":\"Mean AF\",\"formatter\":{\"id\":\"2063\"},\"ticker\":{\"id\":\"1955\"}},\"id\":\"1954\",\"type\":\"LinearAxis\"},{\"attributes\":{\"text\":\"AF: Mean versus 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              "  var render_items = [{\"docid\":\"ab13fb15-417f-43a2-8d17-91bb0722b6e6\",\"root_ids\":[\"2022\"],\"roots\":{\"2022\":\"2d1ad63e-26da-4673-94bf-825cb3616b9d\"}}];\n",
              "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
              "\n",
              "  }\n",
              "  if (root.Bokeh !== undefined) {\n",
              "    embed_document(root);\n",
              "  } else {\n",
              "    var attempts = 0;\n",
              "    var timer = setInterval(function(root) {\n",
              "      if (root.Bokeh !== undefined) {\n",
              "        clearInterval(timer);\n",
              "        embed_document(root);\n",
              "      } else {\n",
              "        attempts++;\n",
              "        if (attempts > 100) {\n",
              "          clearInterval(timer);\n",
              "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
              "        }\n",
              "      }\n",
              "    }, 10, root)\n",
              "  }\n",
              "})(window);"
            ],
            "application/vnd.bokehjs_exec.v0+json": ""
          },
          "metadata": {
            "tags": [],
            "application/vnd.bokehjs_exec.v0+json": {
              "id": "2022"
            }
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "J7EaSRqEPRrl"
      },
      "source": [
        "## Distribution across genome"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "v0np2v6cP0I4"
      },
      "source": [
        "for key in colors:\n",
        "    sites.loc[(sites['FUNCLASS']==key),'color'] = colors[key]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 317
        },
        "id": "SlDIpL8kIrda",
        "outputId": "e523f8c0-b8fe-4448-8e90-b0604b426d21"
      },
      "source": [
        "source = ColumnDataSource(sites)\n",
        "TOOLTIPS = [\n",
        "    (\"Position\", \"@POS{0,0}\"),\n",
        "    (\"GENE\",\"@TRID\"),\n",
        "    (\"min(AF)\",\"@AFamin{(0.000)}\"),\n",
        "    (\"max(AF)\",\"@AFamax{(0.000)}\"),\n",
        "    (\"# samples\",\"@Samplenunique\"),\n",
        "    ('AA','@AA'),\n",
        "    ('REF','@REF'),\n",
        "    ('ALT','@ALT')\n",
        "]\n",
        "p = figure(\n",
        "    plot_height=300,\n",
        "    plot_width=600,\n",
        "    y_range=sorted(sites['FUNCLASS'].unique(),key=str.lower),\n",
        "    tooltips = TOOLTIPS,\n",
        "    x_range=Range1d(\n",
        "        start=0, \n",
        "        end=30000,\n",
        "        bounds=(0, 30000)\n",
        "        )\n",
        "    )\n",
        "glyph_p = Rect(\n",
        "    x='POS',\n",
        "    y='FUNCLASS',\n",
        "    width=100, \n",
        "    height='CoV',\n",
        "    fill_alpha=.75,\n",
        "    line_color=None,\n",
        "    fill_color='color'\n",
        "    )\n",
        "p.add_glyph(source,glyph_p)\n",
        "output_file(\"genomic_dist_{}.html\".format(dataset))\n",
        "show(p)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
              "\n",
              "(function(root) {\n",
              "  function now() {\n",
              "    return new Date();\n",
              "  }\n",
              "\n",
              "  var force = true;\n",
              "\n",
              "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
              "    root._bokeh_onload_callbacks = [];\n",
              "    root._bokeh_is_loading = undefined;\n",
              "  }\n",
              "\n",
              "  var JS_MIME_TYPE = 'application/javascript';\n",
              "  var HTML_MIME_TYPE = 'text/html';\n",
              "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
              "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
              "\n",
              "  /**\n",
              "   * Render data to the DOM node\n",
              "   */\n",
              "  function render(props, node) {\n",
              "    var script = document.createElement(\"script\");\n",
              "    node.appendChild(script);\n",
              "  }\n",
              "\n",
              "  /**\n",
              "   * Handle when an output is cleared or removed\n",
              "   */\n",
              "  function handleClearOutput(event, handle) {\n",
              "    var cell = handle.cell;\n",
              "\n",
              "    var id = cell.output_area._bokeh_element_id;\n",
              "    var server_id = cell.output_area._bokeh_server_id;\n",
              "    // Clean up Bokeh references\n",
              "    if (id != null && id in Bokeh.index) {\n",
              "      Bokeh.index[id].model.document.clear();\n",
              "      delete Bokeh.index[id];\n",
              "    }\n",
              "\n",
              "    if (server_id !== undefined) {\n",
              "      // Clean up Bokeh references\n",
              "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
              "      cell.notebook.kernel.execute(cmd, {\n",
              "        iopub: {\n",
              "          output: function(msg) {\n",
              "            var id = msg.content.text.trim();\n",
              "            if (id in Bokeh.index) {\n",
              "              Bokeh.index[id].model.document.clear();\n",
              "              delete Bokeh.index[id];\n",
              "            }\n",
              "          }\n",
              "        }\n",
              "      });\n",
              "      // Destroy server and session\n",
              "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
              "      cell.notebook.kernel.execute(cmd);\n",
              "    }\n",
              "  }\n",
              "\n",
              "  /**\n",
              "   * Handle when a new output is added\n",
              "   */\n",
              "  function handleAddOutput(event, handle) {\n",
              "    var output_area = handle.output_area;\n",
              "    var output = handle.output;\n",
              "\n",
              "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
              "    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
              "      return\n",
              "    }\n",
              "\n",
              "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
              "\n",
              "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
              "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
              "      // store reference to embed id on output_area\n",
              "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
              "    }\n",
              "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
              "      var bk_div = document.createElement(\"div\");\n",
              "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
              "      var script_attrs = bk_div.children[0].attributes;\n",
              "      for (var i = 0; i < script_attrs.length; i++) {\n",
              "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
              "        toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n",
              "      }\n",
              "      // store reference to server id on output_area\n",
              "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
              "    }\n",
              "  }\n",
              "\n",
              "  function register_renderer(events, OutputArea) {\n",
              "\n",
              "    function append_mime(data, metadata, element) {\n",
              "      // create a DOM node to render to\n",
              "      var toinsert = this.create_output_subarea(\n",
              "        metadata,\n",
              "        CLASS_NAME,\n",
              "        EXEC_MIME_TYPE\n",
              "      );\n",
              "      this.keyboard_manager.register_events(toinsert);\n",
              "      // Render to node\n",
              "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
              "      render(props, toinsert[toinsert.length - 1]);\n",
              "      element.append(toinsert);\n",
              "      return toinsert\n",
              "    }\n",
              "\n",
              "    /* Handle when an output is cleared or removed */\n",
              "    events.on('clear_output.CodeCell', handleClearOutput);\n",
              "    events.on('delete.Cell', handleClearOutput);\n",
              "\n",
              "    /* Handle when a new output is added */\n",
              "    events.on('output_added.OutputArea', handleAddOutput);\n",
              "\n",
              "    /**\n",
              "     * Register the mime type and append_mime function with output_area\n",
              "     */\n",
              "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
              "      /* Is output safe? */\n",
              "      safe: true,\n",
              "      /* Index of renderer in `output_area.display_order` */\n",
              "      index: 0\n",
              "    });\n",
              "  }\n",
              "\n",
              "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
              "  if (root.Jupyter !== undefined) {\n",
              "    var events = require('base/js/events');\n",
              "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
              "\n",
              "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
              "      register_renderer(events, OutputArea);\n",
              "    }\n",
              "  }\n",
              "\n",
              "  \n",
              "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
              "    root._bokeh_timeout = Date.now() + 5000;\n",
              "    root._bokeh_failed_load = false;\n",
              "  }\n",
              "\n",
              "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
              "     \"<div style='background-color: #fdd'>\\n\"+\n",
              "     \"<p>\\n\"+\n",
              "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
              "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
              "     \"</p>\\n\"+\n",
              "     \"<ul>\\n\"+\n",
              "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
              "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
              "     \"</ul>\\n\"+\n",
              "     \"<code>\\n\"+\n",
              "     \"from bokeh.resources import INLINE\\n\"+\n",
              "     \"output_notebook(resources=INLINE)\\n\"+\n",
              "     \"</code>\\n\"+\n",
              "     \"</div>\"}};\n",
              "\n",
              "  function display_loaded() {\n",
              "    var el = document.getElementById(null);\n",
              "    if (el != null) {\n",
              "      el.textContent = \"BokehJS is loading...\";\n",
              "    }\n",
              "    if (root.Bokeh !== undefined) {\n",
              "      if (el != null) {\n",
              "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
              "      }\n",
              "    } else if (Date.now() < root._bokeh_timeout) {\n",
              "      setTimeout(display_loaded, 100)\n",
              "    }\n",
              "  }\n",
              "\n",
              "\n",
              "  function run_callbacks() {\n",
              "    try {\n",
              "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
              "        if (callback != null)\n",
              "          callback();\n",
              "      });\n",
              "    } finally {\n",
              "      delete root._bokeh_onload_callbacks\n",
              "    }\n",
              "    console.debug(\"Bokeh: all callbacks have finished\");\n",
              "  }\n",
              "\n",
              "  function load_libs(css_urls, js_urls, callback) {\n",
              "    if (css_urls == null) css_urls = [];\n",
              "    if (js_urls == null) js_urls = [];\n",
              "\n",
              "    root._bokeh_onload_callbacks.push(callback);\n",
              "    if (root._bokeh_is_loading > 0) {\n",
              "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
              "      return null;\n",
              "    }\n",
              "    if (js_urls == null || js_urls.length === 0) {\n",
              "      run_callbacks();\n",
              "      return null;\n",
              "    }\n",
              "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
              "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
              "\n",
              "    function on_load() {\n",
              "      root._bokeh_is_loading--;\n",
              "      if (root._bokeh_is_loading === 0) {\n",
              "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
              "        run_callbacks()\n",
              "      }\n",
              "    }\n",
              "\n",
              "    function on_error() {\n",
              "      console.error(\"failed to load \" + url);\n",
              "    }\n",
              "\n",
              "    for (var i = 0; i < css_urls.length; i++) {\n",
              "      var url = css_urls[i];\n",
              "      const element = document.createElement(\"link\");\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error;\n",
              "      element.rel = \"stylesheet\";\n",
              "      element.type = \"text/css\";\n",
              "      element.href = url;\n",
              "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
              "      document.body.appendChild(element);\n",
              "    }\n",
              "\n",
              "    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n",
              "\n",
              "    for (var i = 0; i < js_urls.length; i++) {\n",
              "      var url = js_urls[i];\n",
              "      var element = document.createElement('script');\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error;\n",
              "      element.async = false;\n",
              "      element.src = url;\n",
              "      if (url in hashes) {\n",
              "        element.crossOrigin = \"anonymous\";\n",
              "        element.integrity = \"sha384-\" + hashes[url];\n",
              "      }\n",
              "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
              "      document.head.appendChild(element);\n",
              "    }\n",
              "  };\n",
              "\n",
              "  function inject_raw_css(css) {\n",
              "    const element = document.createElement(\"style\");\n",
              "    element.appendChild(document.createTextNode(css));\n",
              "    document.body.appendChild(element);\n",
              "  }\n",
              "\n",
              "  \n",
              "  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n",
              "  var css_urls = [];\n",
              "  \n",
              "\n",
              "  var inline_js = [\n",
              "    function(Bokeh) {\n",
              "      Bokeh.set_log_level(\"info\");\n",
              "    },\n",
              "    function(Bokeh) {\n",
              "    \n",
              "    \n",
              "    }\n",
              "  ];\n",
              "\n",
              "  function run_inline_js() {\n",
              "    \n",
              "    if (root.Bokeh !== undefined || force === true) {\n",
              "      \n",
              "    for (var i = 0; i < inline_js.length; i++) {\n",
              "      inline_js[i].call(root, root.Bokeh);\n",
              "    }\n",
              "    } else if (Date.now() < root._bokeh_timeout) {\n",
              "      setTimeout(run_inline_js, 100);\n",
              "    } else if (!root._bokeh_failed_load) {\n",
              "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
              "      root._bokeh_failed_load = true;\n",
              "    } else if (force !== true) {\n",
              "      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n",
              "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
              "    }\n",
              "\n",
              "  }\n",
              "\n",
              "  if (root._bokeh_is_loading === 0) {\n",
              "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
              "    run_inline_js();\n",
              "  } else {\n",
              "    load_libs(css_urls, js_urls, function() {\n",
              "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
              "      run_inline_js();\n",
              "    });\n",
              "  }\n",
              "}(window));"
            ],
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Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(null);\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; 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