kasey ontology.ipynb

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  "name": ""
 },
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 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import scipy\n",
      "import matplotlib.gridspec as gridspec\n",
      "path = '/home/lovci/fonts/HelveticaLight.ttf'\n",
      "import matplotlib.font_manager as fm\n",
      "\n",
      "helvetica = fm.FontProperties(fname=path)\n",
      "def clusterGram(data, colLabels, rowLabels, distance_metric = 'euclidean', linkage_method = 'average', \n",
      "             clusterRows=True, clusterCols=True, timeSeries=False, doCovar=False, realdata=None):\n",
      "\n",
      "    \"\"\"\n",
      "\n",
      "    Run hierarchical clustering on data. Creates a heatmap of cluster-ordered data\n",
      "    heavy-lifting is done by:\n",
      "    \n",
      "    gets distances between rows/columns\n",
      "    \n",
      "    y_events = scipy.spatial.distance.pdist(data, distance_metric)\n",
      "\n",
      "    calculates the closest rows/columns\n",
      "\n",
      "    Z_events = scipy.cluster.hierarchy.linkage(y_events, linkage_method)\n",
      "\n",
      "    genereates dendrogram (tree)\n",
      "\n",
      "    d_events = scipy.cluster.hierarchy.dendrogram(Z_events, no_labels=True) \n",
      "    \n",
      "    set outfile == \"None\" to inibit saving an eps file (only show it, don't save it)\n",
      "\n",
      "    \"\"\"\n",
      "    \n",
      "    if clusterRows:\n",
      "        print \"getting row distance matrix\"\n",
      "        y_events = scipy.spatial.distance.pdist(data, distance_metric)\n",
      "        print \"calculating linkages\"\n",
      "        Z_events = scipy.cluster.hierarchy.linkage(y_events, linkage_method, metric=distance_metric)\n",
      "\n",
      "    if clusterCols:\n",
      "        print \"getting column distance matrix\"    \n",
      "        y_samples = scipy.spatial.distance.pdist(np.transpose(data), distance_metric)\n",
      "        print \"calculating linkages\"    \n",
      "        Z_samples = scipy.cluster.hierarchy.linkage(y_samples, linkage_method, metric=distance_metric)\n",
      "    else:\n",
      "        if doCovar:\n",
      "            raise ValueError\n",
      "\n",
      "    fig = pylab.figure(figsize=(12,30))\n",
      "\n",
      "    gs = gridspec.GridSpec(12,16)\n",
      "\n",
      "    ax1 = pylab.subplot(gs[1:11, 1:3])\n",
      "\n",
      "    ax1.set_xticks([])\n",
      "    ax1.set_yticks([])\n",
      "    ax1.set_axis_off()\n",
      "    nRow, nCol = data.shape\n",
      "    print \"nRow: %d\" %nRow\n",
      "    if realdata != None:\n",
      "        print realdata.shape\n",
      "        print data.shape\n",
      "\n",
      "        assert realdata.shape == data.shape\n",
      "\n",
      "        reordered = realdata\n",
      "    else:\n",
      "        reordered = data\n",
      "        \n",
      "    event_order = range(nRow)\n",
      "    if clusterRows:\n",
      "        d_events = scipy.cluster.hierarchy.dendrogram(Z_events, orientation='right', no_labels=True)\n",
      "        event_order = d_events['leaves']\n",
      "        reordered = reordered[event_order,:]\n",
      "        \n",
      "    ax2 = pylab.subplot(gs[0:1, 3:9])\n",
      "\n",
      "    ax2.set_xticks([])\n",
      "    ax2.set_yticks([])\n",
      "    ax2.set_axis_off()\n",
      "    sample_order = range(nCol)\n",
      "    if clusterCols:\n",
      "        d_samples = scipy.cluster.hierarchy.dendrogram(Z_samples, no_labels=True)    \n",
      "        sample_order = d_samples['leaves']\n",
      "        reordered = reordered[:,sample_order]\n",
      "    axmatrix = pylab.subplot(gs[1:11, 3:9])\n",
      "    bds = np.max(abs(reordered))\n",
      "    if timeSeries:\n",
      "        norm = mpl.colors.Normalize(vmin=-bds, vmax=bds)\n",
      "    else:\n",
      "        norm = None\n",
      "        \n",
      "\n",
      "    cmap = pylab.cm.bone_r\n",
      "        \n",
      "    im = axmatrix.matshow(reordered, aspect='auto', origin='lower', cmap=cmap, norm=norm)\n",
      "    axmatrix.set_xticks([])\n",
      "    axmatrix.yaxis.tick_right()\n",
      "    axmatrix.set_yticks(range(nRow))\n",
      "    axmatrix.set_yticklabels([rowLabels[i] for i in event_order], fontsize=8, fontproperties=helvetica)\n",
      "    axcolor = pylab.subplot(gs[1:11, 0])\n",
      "\n",
      "    #\n",
      "    cbTicks = [np.min(data), np.mean(data), np.max(data)]\n",
      "    cb = pylab.colorbar(im, cax=axcolor, ticks=cbTicks, use_gridspec=True)\n",
      "    cb.ax.set_yticklabels(map(lambda x: \"%.2f\" %x, cbTicks), fontproperties=helvetica)\n",
      "    axcolor.yaxis.tick_left()\n",
      "    #axRowLabel = pylab.subplot(gs[1:6, 9:13])\n",
      "    #print nRow\n",
      "\n",
      "\n",
      "    #axRowLabel.set_yticks(map(lambda x: x+.5, range(nRow)))\n",
      "        \n",
      "    \n",
      "    \n",
      "    axlabel = pylab.subplot(gs[11:, 3:9]) \n",
      "\n",
      "    step = 1./nCol\n",
      "    for i, ind in enumerate(sample_order):\n",
      "        xpos = (i*step)+(step/2)\n",
      "        pylab.text(xpos,1, colLabels[ind] , rotation=90,verticalalignment='top', horizontalalignment='center', fontproperties=helvetica)\n",
      "    axlabel.set_xticks([])\n",
      "    axlabel.set_yticks([])\n",
      "    axlabel.set_axis_off()\n",
      "    \n",
      "    #    fig.show()\n",
      "    #pylab.tight_layout()\n",
      "\n",
      "    if doCovar:\n",
      "        cluster_covariance(data, colLabels, distance_metric = distance_metric, linkage_method = linkage_method)\n",
      "        \n",
      "    return event_order, sample_order"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 56
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from gscripts.general.dataviz import *"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 15
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from gscripts.GO import hg19GO\n",
      "go = hg19GO()\n",
      "import pandas as pd\n",
      "import os"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "os.chdir(\"/nas3/khutt/KK_RNAseq/MN_data/gene_lists/down50\")\n",
      "bg = pd.read_table('all_bg', names=['bg'])\n",
      "from glob import glob as glob\n",
      "gene_lists = glob(\"*.txt\")\n",
      "lists = {}\n",
      "for l in gene_lists:\n",
      "    x = pd.read_table(l, names=['geneId', 'null'])\n",
      "    lists[os.path.basename(l).replace('.txt', '')] = x['geneId']\n",
      "\n",
      "e = pd.ExcelWriter(\"GOresults.xls\")\n",
      "\n",
      "ontologyObjects = [(cat, go.enrichment(list(lists[cat]), \n",
      "                   background=list(bg['bg']))) for cat in lists.keys()]\n",
      "\n",
      "ontologyObjects.append((\"Summary\", None))\n",
      "\n",
      "TOC = np.array([(\"sheet\"+ str(i+1), j[0]) for i, j in enumerate(ontologyObjects)])\n",
      "\n",
      "indexSheet = pd.DataFrame(TOC[:,1], index = TOC[:,0] )\n",
      "\n",
      "indexSheet.to_excel(e, sheet_name=\"Table of Contents\")\n",
      "\n",
      "\n",
      "index = set()\n",
      "[index.update(j.index) for i, j in ontologyObjects[:-1]]\n",
      "summaryCols = [i for i, j in ontologyObjects[:-1]]\n",
      "\n",
      "summarySheet = pd.DataFrame(columns=summaryCols, index=index)\n",
      "\n",
      "\n",
      "for i, (sheetName, sheet) in enumerate(ontologyObjects):\n",
      "    if sheet is None:\n",
      "        summarySheet.to_excel(e, sheet_name= \"sheet\" + str(i+1), na_rep='notest')\n",
      "        break\n",
      "    sheet.to_excel(e, sheet_name = \"sheet\" + str(i+1), na_rep='na')\n",
      "    summarySheet[sheetName] = sheet.get(\"Bonferroni-corrected Hypergeometric p-Value\")\n",
      "\n",
      "e.save()\n",
      "\n",
      "thisDf = summarySheet\n",
      "\n",
      "names = lists.keys()\n",
      "\n",
      "thisDfmod = thisDf.fillna(np.mean(np.array(thisDf.get(names).dropna())))\n",
      "thisDfmodR = thisDf.fillna(1)\n",
      "anySig = thisDfmod[np.any(np.array(thisDfmod) <= 0.00001, axis=1)]\n",
      "anySigR = thisDfmodR[np.any(np.array(thisDfmodR) <= 0.00001, axis=1)]\n",
      "clusterMe = -np.log10(np.array(anySig) + 0.000001) \n",
      "clusterMeR = -np.log10(np.array(anySigR) + 0.000001) \n",
      "\n",
      "rowNames = [\"|\".join(go.GO[i]['name']) for i in anySig.index]\n",
      "a = clusterGram(clusterMe, anySig.columns, rowNames, realdata = clusterMeR)\n",
      "pylab.savefig(\"kasey_ontology.pdf\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "getting row distance matrix\n",
        "calculating linkages\n",
        "getting column distance matrix\n",
        "calculating linkages\n",
        "nRow: 108"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "(108, 5)\n",
        "(108, 5)\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "/nas3/yeolab/Software/Python-2.7.5/lib/python2.7/site-packages/scipy/spatial/distance.py:1176: DeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n",
        "  dm = np.zeros((m * (m - 1) / 2,), dtype=np.double)\n",
        "/nas3/yeolab/Software/Python-2.7.5/lib/python2.7/site-packages/scipy/spatial/distance.py:1176: DeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n",
        "  dm = np.zeros((m * (m - 1) / 2,), dtype=np.double)\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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LqxQRub4mEJxFRKQ52717N1OmTCEsLIzS0lIqKytdwTkjI4OtW7fSsWNHioqK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\nZejQob94//p1uXeb8PBwwsPD1ds6na7BWunWLj4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TlJaWUl1dTWRkJOHh4ertqKgowsPD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ltvMXDgQHx8fOzr+fn5kZmZycKFC+3PtZw+ABAfH09aWhr+/v44Ozu3O2McEhLC3r172bZt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TCQBgtTb83Dh+/Dj8/f0xatQoJCYmNvvafn5+OHnyJAYOHNjsfm+m0+kAACaTCbNmzYJK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\n",
       "text": [
        "<matplotlib.figure.Figure at 0xb3d1e90>"
       ]
      }
     ],
     "prompt_number": 62
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "os.chdir(\"/nas3/khutt/KK_RNAseq/MN_data/gene_lists/up50\")\n",
      "bg = pd.read_table('all_bg', names=['bg'])\n",
      "from glob import glob as glob\n",
      "gene_lists = glob(\"*.txt\")\n",
      "lists = {}\n",
      "for l in gene_lists:\n",
      "    x = pd.read_table(l, names=['geneId', 'null'])\n",
      "    lists[os.path.basename(l).replace('.txt', '')] = x['geneId']\n",
      "\n",
      "e = pd.ExcelWriter(\"GOresults.xls\")\n",
      "\n",
      "ontologyObjects = [(cat, go.enrichment(list(lists[cat]), \n",
      "                   background=list(bg['bg']))) for cat in lists.keys()]\n",
      "\n",
      "ontologyObjects.append((\"Summary\", None))\n",
      "\n",
      "TOC = np.array([(\"sheet\"+ str(i+1), j[0]) for i, j in enumerate(ontologyObjects)])\n",
      "\n",
      "indexSheet = pd.DataFrame(TOC[:,1], index = TOC[:,0] )\n",
      "\n",
      "indexSheet.to_excel(e, sheet_name=\"Table of Contents\")\n",
      "\n",
      "\n",
      "index = set()\n",
      "[index.update(j.index) for i, j in ontologyObjects[:-1]]\n",
      "summaryCols = [i for i, j in ontologyObjects[:-1]]\n",
      "\n",
      "summarySheet = pd.DataFrame(columns=summaryCols, index=index)\n",
      "\n",
      "\n",
      "for i, (sheetName, sheet) in enumerate(ontologyObjects):\n",
      "    if sheet is None:\n",
      "        summarySheet.to_excel(e, sheet_name= \"sheet\" + str(i+1), na_rep='notest')\n",
      "        break\n",
      "    sheet.to_excel(e, sheet_name = \"sheet\" + str(i+1), na_rep='na')\n",
      "    summarySheet[sheetName] = sheet.get(\"Bonferroni-corrected Hypergeometric p-Value\")\n",
      "\n",
      "e.save()\n",
      "\n",
      "thisDf = summarySheet\n",
      "\n",
      "names = lists.keys()\n",
      "\n",
      "thisDfmod = thisDf.fillna(np.mean(np.array(thisDf.get(names).dropna())))\n",
      "thisDfmodR = thisDf.fillna(1)\n",
      "anySig = thisDfmod[np.any(np.array(thisDfmod) <= 0.00001, axis=1)]\n",
      "anySigR = thisDfmodR[np.any(np.array(thisDfmodR) <= 0.00001, axis=1)]\n",
      "clusterMe = -np.log10(np.array(anySig) + 0.000001) \n",
      "clusterMeR = -np.log10(np.array(anySigR) + 0.000001) \n",
      "\n",
      "rowNames = [\"|\".join(go.GO[i]['name']) for i in anySig.index]\n",
      "a = clusterGram(clusterMe, anySig.columns, rowNames, realdata = clusterMeR)\n",
      "pylab.savefig(\"kasey_ontology.pdf\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "getting row distance matrix\n",
        "calculating linkages\n",
        "getting column distance matrix\n",
        "calculating linkages\n",
        "nRow: 2"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "(2, 5)\n",
        "(2, 5)\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "/nas3/yeolab/Software/Python-2.7.5/lib/python2.7/site-packages/scipy/spatial/distance.py:1176: DeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n",
        "  dm = np.zeros((m * (m - 1) / 2,), dtype=np.double)\n",
        "/nas3/yeolab/Software/Python-2.7.5/lib/python2.7/site-packages/scipy/spatial/distance.py:1176: DeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n",
        "  dm = np.zeros((m * (m - 1) / 2,), dtype=np.double)\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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xxx//f33tt6vzP/IA4Nfb4sWLs/XWW+cLX/hCJk2alMWLF2fnnXfOtGnTcuGFF2b8+PFZ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\nRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x11563550>"
       ]
      }
     ],
     "prompt_number": 63
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "os.chdir(\"/nas3/khutt/KK_RNAseq/MN_data/gene_lists/\")\n",
      "bg = pd.read_table('all_bg', names=['bg'])\n",
      "from glob import glob as glob\n",
      "gene_lists = glob(\"*.txt\")\n",
      "lists = {}\n",
      "for l in gene_lists:\n",
      "    x = pd.read_table(l, names=['geneId', 'null'])\n",
      "    lists[os.path.basename(l).replace('.txt', '')] = x['geneId']\n",
      "\n",
      "e = pd.ExcelWriter(\"GOresults.xls\")\n",
      "\n",
      "ontologyObjects = [(cat, go.enrichment(list(lists[cat]), \n",
      "                   background=list(bg['bg']))) for cat in lists.keys()]\n",
      "\n",
      "ontologyObjects.append((\"Summary\", None))\n",
      "\n",
      "TOC = np.array([(\"sheet\"+ str(i+1), j[0]) for i, j in enumerate(ontologyObjects)])\n",
      "\n",
      "indexSheet = pd.DataFrame(TOC[:,1], index = TOC[:,0] )\n",
      "indexSheet.to_excel(e, sheet_name=\"Table of Contents\")\n",
      "\n",
      "\n",
      "index = set()\n",
      "[index.update(j.index) for i, j in ontologyObjects[:-1]]\n",
      "summaryCols = [i for i, j in ontologyObjects[:-1]]\n",
      "\n",
      "summarySheet = pd.DataFrame(columns=summaryCols, index=index)\n",
      "\n",
      "\n",
      "for i, (sheetName, sheet) in enumerate(ontologyObjects):\n",
      "    if sheet is None:\n",
      "        summarySheet.to_excel(e, sheet_name= \"sheet\" + str(i+1), na_rep='notest')\n",
      "        break\n",
      "    sheet.to_excel(e, sheet_name = \"sheet\" + str(i+1), na_rep='na')\n",
      "    summarySheet[sheetName] = sheet.get(\"Bonferroni-corrected Hypergeometric p-Value\")\n",
      "\n",
      "e.save()\n",
      "\n",
      "thisDf = summarySheet\n",
      "\n",
      "names = lists.keys()\n",
      "\n",
      "thisDfmod = thisDf.fillna(np.mean(np.array(thisDf.get(names).dropna())))\n",
      "thisDfmodR = thisDf.fillna(1)\n",
      "anySig = thisDfmod[np.any(np.array(thisDfmod) <= 0.00001, axis=1)]\n",
      "anySigR = thisDfmodR[np.any(np.array(thisDfmodR) <= 0.00001, axis=1)]\n",
      "clusterMe = -np.log10(np.array(anySig) + 0.000001) \n",
      "clusterMeR = -np.log10(np.array(anySigR) + 0.000001) \n",
      "\n",
      "rowNames = [\"|\".join(go.GO[i]['name']) for i in anySig.index]\n",
      "a = clusterGram(clusterMe, anySig.columns, rowNames, realdata = clusterMeR)\n",
      "pylab.savefig(\"kasey_ontology.pdf\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "IOError",
       "evalue": "[Errno 13] Permission denied: 'GOresults.xls'",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mIOError\u001b[0m                                   Traceback (most recent call last)",
        "\u001b[1;32m<ipython-input-65-3339301e8d2c>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m     36\u001b[0m     \u001b[0msummarySheet\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0msheetName\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msheet\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Bonferroni-corrected Hypergeometric p-Value\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     37\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 38\u001b[1;33m \u001b[0me\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msave\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     39\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     40\u001b[0m \u001b[0mthisDf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msummarySheet\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32m/home/obot/packages/pandas/pandas/io/excel.pyc\u001b[0m in \u001b[0;36msave\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    593\u001b[0m         \u001b[0mSave\u001b[0m \u001b[0mworkbook\u001b[0m \u001b[0mto\u001b[0m \u001b[0mdisk\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    594\u001b[0m         \"\"\"\n\u001b[1;32m--> 595\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbook\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msave\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    596\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    597\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mwrite_cells\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcells\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msheet_name\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstartrow\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstartcol\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32m/nas3/yeolab/Software/Python-2.7.5/lib/python2.7/site-packages/xlwt-0.7.5-py2.7.egg/xlwt/Workbook.pyc\u001b[0m in \u001b[0;36msave\u001b[1;34m(self, filename)\u001b[0m\n\u001b[0;32m    660\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    661\u001b[0m         \u001b[0mdoc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mCompoundDoc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mXlsDoc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 662\u001b[1;33m         \u001b[0mdoc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msave\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_biff_data\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    663\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    664\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32m/nas3/yeolab/Software/Python-2.7.5/lib/python2.7/site-packages/xlwt-0.7.5-py2.7.egg/xlwt/CompoundDoc.pyc\u001b[0m in \u001b[0;36msave\u001b[1;34m(self, file_name_or_filelike_obj, stream)\u001b[0m\n\u001b[0;32m    259\u001b[0m         \u001b[0mwe_own_it\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mhasattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'write'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    260\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mwe_own_it\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 261\u001b[1;33m             \u001b[0mf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfile_name_or_filelike_obj\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'w+b'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    262\u001b[0m         \u001b[0mf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mheader\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    263\u001b[0m         \u001b[0mf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpacked_MSAT_1st\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;31mIOError\u001b[0m: [Errno 13] Permission denied: 'GOresults.xls'"
       ]
      }
     ],
     "prompt_number": 65
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}