CLIPper Read Counting Error.ipynb

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 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pybedtools"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "clipper_reads = pybedtools.BedTool(\"/nas3/gpratt/projects/encode/analysis/meeting/IMP1_A.peaks.bed\")\n",
      "\n",
      "bamtool = pybedtools.BedTool(\"/nas3/gpratt/projects/encode/analysis/meeting/IMP1_A.bam\")\n",
      "bedtool = pybedtools.BedTool(\"/nas3/gpratt/projects/encode/analysis/meeting/IMP1_A.peaks.bed\")\n",
      "\n",
      "cov = bamtool.coverage(bedtool, s=True, counts=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#Number of Reads CLIPper Counts"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sum([float(interval.name.split(\"_\")[2]) for interval in clipper_reads])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "1897585.0"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#Number of Reads Counted by Coverage Bed"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sum([float(interval[-1]) for interval in cov])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 4,
       "text": [
        "7277837.0"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print cov[0]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "chr1\t39469042\t39469077\tENSG00000174574.11_1_81\t1.60552581193e-69\t+\t39469061\t39469065\t139\n",
        "\n"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print clipper_reads[0]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "chr1\t138780\t138800\tENSG00000237683.5_3_14\t6.50888314231e-08\t-\t138787\t138791\n",
        "\n"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "clipper_reads = clipper_reads.sort().saveas()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "cov = cov.sort().saveas()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 11
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print clipper_reads[0]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "chr1\t138780\t138800\tENSG00000237683.5_3_14\t6.50888314231e-08\t-\t138787\t138791\n",
        "\n"
       ]
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print cov[0]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "chr1\t138780\t138800\tENSG00000237683.5_3_14\t6.50888314231e-08\t-\t138787\t138791\t43\n",
        "\n"
       ]
      }
     ],
     "prompt_number": 14
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print cov[1]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "chr1\t139039\t139064\tENSG00000237683.5_4_33\t2.78293661534e-34\t-\t139055\t139059\t62\n",
        "\n"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import seaborn as sns"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "/nas/nas0/gpratt/virtualenvs/default/lib/python2.7/site-packages/pandas/io/excel.py:626: UserWarning: Installed openpyxl is not supported at this time. Use >=1.6.1 and <2.0.0.\n",
        "  .format(openpyxl_compat.start_ver, openpyxl_compat.stop_ver))\n"
       ]
      }
     ],
     "prompt_number": 17
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import matplotlib as mpl\n",
      "import matplotlib.pyplot as plt"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 25
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%matplotlib inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 27
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import os\n",
      "img_dir = \".\"\n",
      "import gscripts.general.dataviz as dataviz"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 42
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from collections import Counter "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 45
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "foo = Counter([len(interval) for interval in cov])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 47
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "with dataviz.Figure(os.path.join(img_dir, \"foo.svg\"), figsize=(3,3)) as fig:\n",
      "    ax = fig.add_subplot(1,1,1)\n",
      "    ax.plot(foo.keys(), foo.values())\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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L1rq9ysSJEykoKHBqrJiYGFJSrJ26Q0NDSU5Opry83O3xbOOAtUa40WikR48e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\nIHiACEgQPOD/AxgQBKl6DD6oAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x2aaaac947d10>"
       ]
      }
     ],
     "prompt_number": 48
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}