src/Comparison between Alzheimer's and Parkinson's Disease.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "from matplotlib_venn import venn2\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "\n",
    "os.chdir('data')\n",
    "sns.set_style('whitegrid')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Load the RNA-seq differentially expressed genes data\n",
    "datPD = pd.read_table('parkinsonDE.txt')\n",
    "\n",
    "# Slice the data by the adjusted p-value\n",
    "lowPVal = datPD[datPD['padj'] < 0.05]\n",
    "\n",
    "# Load the MS3 Proteomics data\n",
    "protDatPD = pd.read_table('protPDE.csv')\n",
    "\n",
    "# Slice the data by the FDR q-value\n",
    "lowQVal = protDatPD[protDatPD['qvalue'] < 0.05]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Read the up regulated genes in the Alzheimer's disease\n",
    "alzUpGenes = []\n",
    "with open('alzUpGenes.txt', 'r') as file:\n",
    "    for gene in file:\n",
    "        gene = gene.strip().upper()\n",
    "        alzUpGenes.append(gene)\n",
    "\n",
    "intersectAlzRNASeq = list(set(lowPVal['symbol']).intersection(alzUpGenes))\n",
    "intersectTab = lowPVal[lowPVal['symbol'].isin(intersectAlzRNASeq)]\n",
    "downRegGenes = intersectTab[intersectTab['log2FoldChange'] < 0].sort_values(by='log2FoldChange', ascending=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Read the down regulated genes in the Alzheimer's disease\n",
    "alzDnGenes = []\n",
    "with open('alzDnGenes.txt', 'r') as file:\n",
    "    for gene in file:\n",
    "        gene = gene.strip().upper()\n",
    "        alzDnGenes.append(gene)\n",
    "alzDnGenes = alzDnGenes[2:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Symbol</th>\n",
       "      <th>log2FoldChange</th>\n",
       "      <th>foldChange</th>\n",
       "      <th>pvalue</th>\n",
       "      <th>padj</th>\n",
       "      <th>qvalue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>AQP1</td>\n",
       "      <td>0.382980</td>\n",
       "      <td>1.304033</td>\n",
       "      <td>1.424316e-03</td>\n",
       "      <td>0.037185</td>\n",
       "      <td>0.023895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>CA1</td>\n",
       "      <td>0.308048</td>\n",
       "      <td>1.238031</td>\n",
       "      <td>2.296287e-03</td>\n",
       "      <td>0.049218</td>\n",
       "      <td>0.031627</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>DPYSL3</td>\n",
       "      <td>0.221558</td>\n",
       "      <td>1.165992</td>\n",
       "      <td>1.570000e-07</td>\n",
       "      <td>0.000187</td>\n",
       "      <td>0.000120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>NT5C</td>\n",
       "      <td>0.195499</td>\n",
       "      <td>1.145120</td>\n",
       "      <td>7.490000e-05</td>\n",
       "      <td>0.007015</td>\n",
       "      <td>0.004508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>MAPK1</td>\n",
       "      <td>0.185216</td>\n",
       "      <td>1.136987</td>\n",
       "      <td>6.180000e-07</td>\n",
       "      <td>0.000275</td>\n",
       "      <td>0.000177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>NEK7</td>\n",
       "      <td>0.132257</td>\n",
       "      <td>1.096007</td>\n",
       "      <td>3.560000e-06</td>\n",
       "      <td>0.001055</td>\n",
       "      <td>0.000678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>ARHGAP1</td>\n",
       "      <td>0.120384</td>\n",
       "      <td>1.087024</td>\n",
       "      <td>2.130634e-04</td>\n",
       "      <td>0.012857</td>\n",
       "      <td>0.008262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>GPC4</td>\n",
       "      <td>0.119807</td>\n",
       "      <td>1.086589</td>\n",
       "      <td>9.654721e-04</td>\n",
       "      <td>0.031480</td>\n",
       "      <td>0.020229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>266</th>\n",
       "      <td>GPM6B</td>\n",
       "      <td>0.117889</td>\n",
       "      <td>1.085146</td>\n",
       "      <td>5.437979e-03</td>\n",
       "      <td>0.072466</td>\n",
       "      <td>0.046566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>KPNB1</td>\n",
       "      <td>0.115725</td>\n",
       "      <td>1.083519</td>\n",
       "      <td>2.044361e-03</td>\n",
       "      <td>0.046037</td>\n",
       "      <td>0.029583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>PSMF1</td>\n",
       "      <td>0.105289</td>\n",
       "      <td>1.075710</td>\n",
       "      <td>8.848292e-04</td>\n",
       "      <td>0.030565</td>\n",
       "      <td>0.019641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208</th>\n",
       "      <td>CARM1</td>\n",
       "      <td>0.100302</td>\n",
       "      <td>1.071998</td>\n",
       "      <td>3.648562e-03</td>\n",
       "      <td>0.061869</td>\n",
       "      <td>0.039757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>G6PD</td>\n",
       "      <td>0.097997</td>\n",
       "      <td>1.070287</td>\n",
       "      <td>9.980000e-05</td>\n",
       "      <td>0.008358</td>\n",
       "      <td>0.005371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>VAT1</td>\n",
       "      <td>0.091203</td>\n",
       "      <td>1.065258</td>\n",
       "      <td>3.372708e-03</td>\n",
       "      <td>0.059966</td>\n",
       "      <td>0.038534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>SGTA</td>\n",
       "      <td>0.090186</td>\n",
       "      <td>1.064507</td>\n",
       "      <td>1.947368e-03</td>\n",
       "      <td>0.044992</td>\n",
       "      <td>0.028911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>231</th>\n",
       "      <td>KPNA6</td>\n",
       "      <td>0.089482</td>\n",
       "      <td>1.063988</td>\n",
       "      <td>4.375878e-03</td>\n",
       "      <td>0.067109</td>\n",
       "      <td>0.043124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>EEF1A1</td>\n",
       "      <td>0.067864</td>\n",
       "      <td>1.048164</td>\n",
       "      <td>1.283989e-03</td>\n",
       "      <td>0.036199</td>\n",
       "      <td>0.023261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>263</th>\n",
       "      <td>PEBP1</td>\n",
       "      <td>0.054957</td>\n",
       "      <td>1.038828</td>\n",
       "      <td>5.265602e-03</td>\n",
       "      <td>0.070966</td>\n",
       "      <td>0.045602</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Symbol  log2FoldChange  foldChange        pvalue      padj    qvalue\n",
       "135     AQP1        0.382980    1.304033  1.424316e-03  0.037185  0.023895\n",
       "165      CA1        0.308048    1.238031  2.296287e-03  0.049218  0.031627\n",
       "2     DPYSL3        0.221558    1.165992  1.570000e-07  0.000187  0.000120\n",
       "37      NT5C        0.195499    1.145120  7.490000e-05  0.007015  0.004508\n",
       "7      MAPK1        0.185216    1.136987  6.180000e-07  0.000275  0.000177\n",
       "11      NEK7        0.132257    1.096007  3.560000e-06  0.001055  0.000678\n",
       "57   ARHGAP1        0.120384    1.087024  2.130634e-04  0.012857  0.008262\n",
       "107     GPC4        0.119807    1.086589  9.654721e-04  0.031480  0.020229\n",
       "266    GPM6B        0.117889    1.085146  5.437979e-03  0.072466  0.046566\n",
       "157    KPNB1        0.115725    1.083519  2.044361e-03  0.046037  0.029583\n",
       "102    PSMF1        0.105289    1.075710  8.848292e-04  0.030565  0.019641\n",
       "208    CARM1        0.100302    1.071998  3.648562e-03  0.061869  0.039757\n",
       "41      G6PD        0.097997    1.070287  9.980000e-05  0.008358  0.005371\n",
       "198     VAT1        0.091203    1.065258  3.372708e-03  0.059966  0.038534\n",
       "153     SGTA        0.090186    1.064507  1.947368e-03  0.044992  0.028911\n",
       "231    KPNA6        0.089482    1.063988  4.375878e-03  0.067109  0.043124\n",
       "124   EEF1A1        0.067864    1.048164  1.283989e-03  0.036199  0.023261\n",
       "263    PEBP1        0.054957    1.038828  5.265602e-03  0.070966  0.045602"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find the intersection between the Proteomics proteins and the upregulated genes in the Alzheimer's disease\n",
    "intersectAlzUpProt = list(set(lowQVal['Symbol']).intersection(alzUpGenes))\n",
    "intersectTabUpProt = lowQVal[lowQVal['Symbol'].isin(intersectAlzUpProt)]\n",
    "\n",
    "intersectTabUpProt[intersectTabUpProt['log2FoldChange'] > 0].sort_values(by='log2FoldChange', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Symbol</th>\n",
       "      <th>log2FoldChange</th>\n",
       "      <th>foldChange</th>\n",
       "      <th>pvalue</th>\n",
       "      <th>padj</th>\n",
       "      <th>qvalue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>ERP44</td>\n",
       "      <td>-0.065121</td>\n",
       "      <td>0.955865</td>\n",
       "      <td>1.898488e-03</td>\n",
       "      <td>0.044149</td>\n",
       "      <td>0.028370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>PURA</td>\n",
       "      <td>-0.070011</td>\n",
       "      <td>0.952630</td>\n",
       "      <td>1.878987e-03</td>\n",
       "      <td>0.044149</td>\n",
       "      <td>0.028370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>GMPS</td>\n",
       "      <td>-0.079542</td>\n",
       "      <td>0.946358</td>\n",
       "      <td>2.718705e-04</td>\n",
       "      <td>0.014882</td>\n",
       "      <td>0.009563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>LONP1</td>\n",
       "      <td>-0.083056</td>\n",
       "      <td>0.944056</td>\n",
       "      <td>2.068578e-03</td>\n",
       "      <td>0.046289</td>\n",
       "      <td>0.029745</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>RPLP2</td>\n",
       "      <td>-0.138222</td>\n",
       "      <td>0.908638</td>\n",
       "      <td>2.533740e-03</td>\n",
       "      <td>0.051860</td>\n",
       "      <td>0.033325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>GAB2</td>\n",
       "      <td>-0.140629</td>\n",
       "      <td>0.907124</td>\n",
       "      <td>1.233482e-03</td>\n",
       "      <td>0.035690</td>\n",
       "      <td>0.022934</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>252</th>\n",
       "      <td>EML2</td>\n",
       "      <td>-0.151655</td>\n",
       "      <td>0.900217</td>\n",
       "      <td>5.034572e-03</td>\n",
       "      <td>0.070252</td>\n",
       "      <td>0.045144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>DAZAP1</td>\n",
       "      <td>-0.161622</td>\n",
       "      <td>0.894019</td>\n",
       "      <td>5.170000e-07</td>\n",
       "      <td>0.000263</td>\n",
       "      <td>0.000169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>CAST</td>\n",
       "      <td>-0.173852</td>\n",
       "      <td>0.886473</td>\n",
       "      <td>3.368597e-04</td>\n",
       "      <td>0.016881</td>\n",
       "      <td>0.010848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>GJB1</td>\n",
       "      <td>-0.179560</td>\n",
       "      <td>0.882972</td>\n",
       "      <td>1.841259e-03</td>\n",
       "      <td>0.043968</td>\n",
       "      <td>0.028253</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Symbol  log2FoldChange  foldChange        pvalue      padj    qvalue\n",
       "152   ERP44       -0.065121    0.955865  1.898488e-03  0.044149  0.028370\n",
       "150    PURA       -0.070011    0.952630  1.878987e-03  0.044149  0.028370\n",
       "64     GMPS       -0.079542    0.946358  2.718705e-04  0.014882  0.009563\n",
       "158   LONP1       -0.083056    0.944056  2.068578e-03  0.046289  0.029745\n",
       "172   RPLP2       -0.138222    0.908638  2.533740e-03  0.051860  0.033325\n",
       "121    GAB2       -0.140629    0.907124  1.233482e-03  0.035690  0.022934\n",
       "252    EML2       -0.151655    0.900217  5.034572e-03  0.070252  0.045144\n",
       "6    DAZAP1       -0.161622    0.894019  5.170000e-07  0.000263  0.000169\n",
       "70     CAST       -0.173852    0.886473  3.368597e-04  0.016881  0.010848\n",
       "148    GJB1       -0.179560    0.882972  1.841259e-03  0.043968  0.028253"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# List the proteins that are downregulated instead of upregulated like they are in Alzheimer's Disease\n",
    "intersectTabUpProt[intersectTabUpProt['log2FoldChange'] < 0].sort_values(by='log2FoldChange', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>symbol</th>\n",
       "      <th>baseMean</th>\n",
       "      <th>log2FoldChange</th>\n",
       "      <th>lfcSE</th>\n",
       "      <th>stat</th>\n",
       "      <th>pvalue</th>\n",
       "      <th>padj</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>S100A12</td>\n",
       "      <td>18.352878</td>\n",
       "      <td>1.095097</td>\n",
       "      <td>0.235501</td>\n",
       "      <td>4.650076</td>\n",
       "      <td>3.318127e-06</td>\n",
       "      <td>0.001242</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>SLC1A7</td>\n",
       "      <td>138.256682</td>\n",
       "      <td>0.976435</td>\n",
       "      <td>0.234148</td>\n",
       "      <td>4.170166</td>\n",
       "      <td>3.043779e-05</td>\n",
       "      <td>0.004164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>MAFF</td>\n",
       "      <td>498.794465</td>\n",
       "      <td>0.957856</td>\n",
       "      <td>0.194620</td>\n",
       "      <td>4.921670</td>\n",
       "      <td>8.580863e-07</td>\n",
       "      <td>0.000471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>GPR4</td>\n",
       "      <td>286.632707</td>\n",
       "      <td>0.935271</td>\n",
       "      <td>0.207966</td>\n",
       "      <td>4.497225</td>\n",
       "      <td>6.884627e-06</td>\n",
       "      <td>0.001834</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>ITGA10</td>\n",
       "      <td>334.582400</td>\n",
       "      <td>0.773580</td>\n",
       "      <td>0.172182</td>\n",
       "      <td>4.492805</td>\n",
       "      <td>7.029114e-06</td>\n",
       "      <td>0.001844</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      symbol    baseMean  log2FoldChange     lfcSE      stat        pvalue  \\\n",
       "45   S100A12   18.352878        1.095097  0.235501  4.650076  3.318127e-06   \n",
       "127   SLC1A7  138.256682        0.976435  0.234148  4.170166  3.043779e-05   \n",
       "31      MAFF  498.794465        0.957856  0.194620  4.921670  8.580863e-07   \n",
       "65      GPR4  286.632707        0.935271  0.207966  4.497225  6.884627e-06   \n",
       "66    ITGA10  334.582400        0.773580  0.172182  4.492805  7.029114e-06   \n",
       "\n",
       "         padj  \n",
       "45   0.001242  \n",
       "127  0.004164  \n",
       "31   0.000471  \n",
       "65   0.001834  \n",
       "66   0.001844  "
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find the intersection between the Proteomics proteins and the upregulated genes in the Alzheimer's disease\n",
    "intersectAlzUpRNA = list(set(lowPVal['symbol']).intersection(alzUpGenes))\n",
    "intersectTabUpRNA = lowPVal[lowPVal['symbol'].isin(intersectAlzUpRNA)]\n",
    "\n",
    "intersectTabUpRNA[intersectTabUpRNA['log2FoldChange'] > 0].ix[:, 1:].sort_values(by='log2FoldChange',\n",
    "                                                                                 ascending=False).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>symbol</th>\n",
       "      <th>baseMean</th>\n",
       "      <th>log2FoldChange</th>\n",
       "      <th>lfcSE</th>\n",
       "      <th>stat</th>\n",
       "      <th>pvalue</th>\n",
       "      <th>padj</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>DAO</td>\n",
       "      <td>38.020726</td>\n",
       "      <td>-1.049665</td>\n",
       "      <td>0.238808</td>\n",
       "      <td>-4.395434</td>\n",
       "      <td>0.000011</td>\n",
       "      <td>0.002492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>548</th>\n",
       "      <td>SPAG6</td>\n",
       "      <td>97.753997</td>\n",
       "      <td>-0.731278</td>\n",
       "      <td>0.216813</td>\n",
       "      <td>-3.372848</td>\n",
       "      <td>0.000744</td>\n",
       "      <td>0.023749</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>277</th>\n",
       "      <td>ANGPTL2</td>\n",
       "      <td>390.863474</td>\n",
       "      <td>-0.706149</td>\n",
       "      <td>0.189659</td>\n",
       "      <td>-3.723258</td>\n",
       "      <td>0.000197</td>\n",
       "      <td>0.012437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>325</th>\n",
       "      <td>ENOSF1</td>\n",
       "      <td>725.096904</td>\n",
       "      <td>-0.693534</td>\n",
       "      <td>0.189811</td>\n",
       "      <td>-3.653802</td>\n",
       "      <td>0.000258</td>\n",
       "      <td>0.013939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1016</th>\n",
       "      <td>PZP</td>\n",
       "      <td>25.175855</td>\n",
       "      <td>-0.648868</td>\n",
       "      <td>0.217105</td>\n",
       "      <td>-2.988727</td>\n",
       "      <td>0.002801</td>\n",
       "      <td>0.048426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>PLAG1</td>\n",
       "      <td>136.268581</td>\n",
       "      <td>-0.528449</td>\n",
       "      <td>0.131566</td>\n",
       "      <td>-4.016619</td>\n",
       "      <td>0.000059</td>\n",
       "      <td>0.006139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>611</th>\n",
       "      <td>RBM3</td>\n",
       "      <td>1564.087820</td>\n",
       "      <td>-0.497115</td>\n",
       "      <td>0.149865</td>\n",
       "      <td>-3.317088</td>\n",
       "      <td>0.000910</td>\n",
       "      <td>0.026129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>ZNF136</td>\n",
       "      <td>213.475884</td>\n",
       "      <td>-0.483048</td>\n",
       "      <td>0.113624</td>\n",
       "      <td>-4.251268</td>\n",
       "      <td>0.000021</td>\n",
       "      <td>0.003416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>353</th>\n",
       "      <td>ALMS1</td>\n",
       "      <td>372.994365</td>\n",
       "      <td>-0.468491</td>\n",
       "      <td>0.129729</td>\n",
       "      <td>-3.611315</td>\n",
       "      <td>0.000305</td>\n",
       "      <td>0.015129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>939</th>\n",
       "      <td>TUBA1A</td>\n",
       "      <td>20528.239091</td>\n",
       "      <td>-0.412856</td>\n",
       "      <td>0.136051</td>\n",
       "      <td>-3.034566</td>\n",
       "      <td>0.002409</td>\n",
       "      <td>0.045084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>435</th>\n",
       "      <td>BMP2K</td>\n",
       "      <td>185.775374</td>\n",
       "      <td>-0.399534</td>\n",
       "      <td>0.114162</td>\n",
       "      <td>-3.499700</td>\n",
       "      <td>0.000466</td>\n",
       "      <td>0.018776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>885</th>\n",
       "      <td>C5</td>\n",
       "      <td>202.246870</td>\n",
       "      <td>-0.365983</td>\n",
       "      <td>0.119090</td>\n",
       "      <td>-3.073165</td>\n",
       "      <td>0.002118</td>\n",
       "      <td>0.042026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>872</th>\n",
       "      <td>FBN1</td>\n",
       "      <td>727.047432</td>\n",
       "      <td>-0.347542</td>\n",
       "      <td>0.112755</td>\n",
       "      <td>-3.082264</td>\n",
       "      <td>0.002054</td>\n",
       "      <td>0.041380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>298</th>\n",
       "      <td>USP13</td>\n",
       "      <td>470.155898</td>\n",
       "      <td>-0.328363</td>\n",
       "      <td>0.089193</td>\n",
       "      <td>-3.681479</td>\n",
       "      <td>0.000232</td>\n",
       "      <td>0.013527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>ZNF236</td>\n",
       "      <td>599.540153</td>\n",
       "      <td>-0.311597</td>\n",
       "      <td>0.070808</td>\n",
       "      <td>-4.400570</td>\n",
       "      <td>0.000011</td>\n",
       "      <td>0.002492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>576</th>\n",
       "      <td>IPP</td>\n",
       "      <td>233.042954</td>\n",
       "      <td>-0.309777</td>\n",
       "      <td>0.092575</td>\n",
       "      <td>-3.346217</td>\n",
       "      <td>0.000819</td>\n",
       "      <td>0.024960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>739</th>\n",
       "      <td>HLCS</td>\n",
       "      <td>450.458525</td>\n",
       "      <td>-0.303498</td>\n",
       "      <td>0.095181</td>\n",
       "      <td>-3.188644</td>\n",
       "      <td>0.001429</td>\n",
       "      <td>0.034004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>612</th>\n",
       "      <td>KHDRBS1</td>\n",
       "      <td>2641.550382</td>\n",
       "      <td>-0.293317</td>\n",
       "      <td>0.088443</td>\n",
       "      <td>-3.316461</td>\n",
       "      <td>0.000912</td>\n",
       "      <td>0.026145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>736</th>\n",
       "      <td>ZNF268</td>\n",
       "      <td>276.447954</td>\n",
       "      <td>-0.262532</td>\n",
       "      <td>0.082321</td>\n",
       "      <td>-3.189111</td>\n",
       "      <td>0.001427</td>\n",
       "      <td>0.033995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>579</th>\n",
       "      <td>KLHL20</td>\n",
       "      <td>386.257394</td>\n",
       "      <td>-0.258724</td>\n",
       "      <td>0.077479</td>\n",
       "      <td>-3.339260</td>\n",
       "      <td>0.000840</td>\n",
       "      <td>0.024965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>731</th>\n",
       "      <td>ZNF43</td>\n",
       "      <td>315.552492</td>\n",
       "      <td>-0.257856</td>\n",
       "      <td>0.080528</td>\n",
       "      <td>-3.202065</td>\n",
       "      <td>0.001364</td>\n",
       "      <td>0.032773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>727</th>\n",
       "      <td>NUCKS1</td>\n",
       "      <td>6246.522803</td>\n",
       "      <td>-0.246799</td>\n",
       "      <td>0.076980</td>\n",
       "      <td>-3.206023</td>\n",
       "      <td>0.001346</td>\n",
       "      <td>0.032500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>717</th>\n",
       "      <td>ULK2</td>\n",
       "      <td>2281.708924</td>\n",
       "      <td>-0.237120</td>\n",
       "      <td>0.073807</td>\n",
       "      <td>-3.212727</td>\n",
       "      <td>0.001315</td>\n",
       "      <td>0.032014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>919</th>\n",
       "      <td>GTF2H3</td>\n",
       "      <td>718.719726</td>\n",
       "      <td>-0.233693</td>\n",
       "      <td>0.076713</td>\n",
       "      <td>-3.046314</td>\n",
       "      <td>0.002317</td>\n",
       "      <td>0.044268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1008</th>\n",
       "      <td>AIMP2</td>\n",
       "      <td>214.802404</td>\n",
       "      <td>-0.212647</td>\n",
       "      <td>0.071048</td>\n",
       "      <td>-2.993008</td>\n",
       "      <td>0.002762</td>\n",
       "      <td>0.047988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>770</th>\n",
       "      <td>PIK3C3</td>\n",
       "      <td>1578.240921</td>\n",
       "      <td>-0.212177</td>\n",
       "      <td>0.067239</td>\n",
       "      <td>-3.155547</td>\n",
       "      <td>0.001602</td>\n",
       "      <td>0.036422</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       symbol      baseMean  log2FoldChange     lfcSE      stat    pvalue  \\\n",
       "74        DAO     38.020726       -1.049665  0.238808 -4.395434  0.000011   \n",
       "548     SPAG6     97.753997       -0.731278  0.216813 -3.372848  0.000744   \n",
       "277   ANGPTL2    390.863474       -0.706149  0.189659 -3.723258  0.000197   \n",
       "325    ENOSF1    725.096904       -0.693534  0.189811 -3.653802  0.000258   \n",
       "1016      PZP     25.175855       -0.648868  0.217105 -2.988727  0.002801   \n",
       "169     PLAG1    136.268581       -0.528449  0.131566 -4.016619  0.000059   \n",
       "611      RBM3   1564.087820       -0.497115  0.149865 -3.317088  0.000910   \n",
       "108    ZNF136    213.475884       -0.483048  0.113624 -4.251268  0.000021   \n",
       "353     ALMS1    372.994365       -0.468491  0.129729 -3.611315  0.000305   \n",
       "939    TUBA1A  20528.239091       -0.412856  0.136051 -3.034566  0.002409   \n",
       "435     BMP2K    185.775374       -0.399534  0.114162 -3.499700  0.000466   \n",
       "885        C5    202.246870       -0.365983  0.119090 -3.073165  0.002118   \n",
       "872      FBN1    727.047432       -0.347542  0.112755 -3.082264  0.002054   \n",
       "298     USP13    470.155898       -0.328363  0.089193 -3.681479  0.000232   \n",
       "76     ZNF236    599.540153       -0.311597  0.070808 -4.400570  0.000011   \n",
       "576       IPP    233.042954       -0.309777  0.092575 -3.346217  0.000819   \n",
       "739      HLCS    450.458525       -0.303498  0.095181 -3.188644  0.001429   \n",
       "612   KHDRBS1   2641.550382       -0.293317  0.088443 -3.316461  0.000912   \n",
       "736    ZNF268    276.447954       -0.262532  0.082321 -3.189111  0.001427   \n",
       "579    KLHL20    386.257394       -0.258724  0.077479 -3.339260  0.000840   \n",
       "731     ZNF43    315.552492       -0.257856  0.080528 -3.202065  0.001364   \n",
       "727    NUCKS1   6246.522803       -0.246799  0.076980 -3.206023  0.001346   \n",
       "717      ULK2   2281.708924       -0.237120  0.073807 -3.212727  0.001315   \n",
       "919    GTF2H3    718.719726       -0.233693  0.076713 -3.046314  0.002317   \n",
       "1008    AIMP2    214.802404       -0.212647  0.071048 -2.993008  0.002762   \n",
       "770    PIK3C3   1578.240921       -0.212177  0.067239 -3.155547  0.001602   \n",
       "\n",
       "          padj  \n",
       "74    0.002492  \n",
       "548   0.023749  \n",
       "277   0.012437  \n",
       "325   0.013939  \n",
       "1016  0.048426  \n",
       "169   0.006139  \n",
       "611   0.026129  \n",
       "108   0.003416  \n",
       "353   0.015129  \n",
       "939   0.045084  \n",
       "435   0.018776  \n",
       "885   0.042026  \n",
       "872   0.041380  \n",
       "298   0.013527  \n",
       "76    0.002492  \n",
       "576   0.024960  \n",
       "739   0.034004  \n",
       "612   0.026145  \n",
       "736   0.033995  \n",
       "579   0.024965  \n",
       "731   0.032773  \n",
       "727   0.032500  \n",
       "717   0.032014  \n",
       "919   0.044268  \n",
       "1008  0.047988  \n",
       "770   0.036422  "
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "intersectTabUpRNA[intersectTabUpRNA['log2FoldChange'] < 0].ix[:, 1:].sort_values(by='log2FoldChange',\n",
    "                                                                                 ascending=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "intAlzUpRNAFalse = sum(intersectTabUpRNA['log2FoldChange'] < 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Wx6t1+aDuKnd7NH/pRhUUlWrC8N6mZK7K5/Np2WvL1KZbG/UY0UOFZ6tv0hsV\nE6Uel/XQ+o/W66O/fKSJ90+UK8al/87/r9xlbg27YVi1xzvt1vl1hfBm8/ksMuv6yy+l3bvNToEm\nNnXePK3/rihVvNusuLLm2auv1sTu3fXK2rX6dPduncjPV4zTqcFt2+rnI0cqo8pq3x6vV6+sWaP5\n336rU0VF6pCcrJ9ddpmu6VH9su3Nx4/rrnfe0cs33qixXapv+YDIVNAqVjkJxU3+dYtLyvTX+V9q\nzdZ9KiwuU6c2qfrepBEa0e/c8/LDFVv0wYqvdTTrjBwOu7q2T9NdE4drSK9OTZ7X43BoaeK5JQPy\nTuXpbw/8TTbZap3/dNktl2nE5BEqyivSin+t0L5N++Quc6t159Yad884texQfbX+FnEtNLkny4PA\nfNYpTsuXS7t2mZ0CQIQpbh6trJRSs2OEPI/TpaUJ5UE7fpfmXXRl5yuDdnzAX9aZOMQcJwAmcJaw\n8KI/PEE+o5kc0/TztoDaWKeNMMcJgAmcpR5ef/zgsde8Ci6QkqMpTggN1ilOVS4jB4CmYvP65PAF\ntxSEA0+Qf5sw4oRQYZ3iFBtrdgIAESrKyxVdF+MO8qgcI04IFRQnALiImFLrvFSaxR3E3hTrjFW0\nkwVpERqs82pAcQJgkph8t9kRQp47iBfwtEtqF7RjA/VFcQKAi3Dll8luY57ThZQHcYn1DskdgnZs\noL4oTgBwETZJMR4uULmQ8iCdqrPb7Gqf3D44BwcawDrFKSaGtZwAmCa6hCUJLqRc3qAct3VCa0U5\nKK0IHdZpIjabUZ4AwARxZ8rMjhDSgvWv0zG5Y5CODDSMdYqTxOk6AKZxlrgV6+XNW13KbMEZcerY\njOKE0EJxAgA/JRRwuq4uxUE4VZcam6qk6KSAHxdoDGsVp7g4sxMAiGCx2cVy2FgM83w+m01FCvye\nfv1a9Qv4MYHGslZxYsQJgIlsPim+lInK53M7XfIpsMsRJEQlqEtKl4AeEwgEihMA1EPCaRbDPF+Z\nM/BrXPVr1U92m7V+RSEyWOtZSXECYDJXYZnivUwbqKrEHti5XzHOGGW0yAjoMYFAsVZxYo4TgBCQ\nnOWWLcib2lpJcYAHnHq37C2nnblkCE3WKk6MOAEIAa7CMsW7eT2qUBTA7Vacdqf6pPUJ2PGAQLNW\ncYqPNzsBAEiSmp0oZQ7OdwoDuIbTwNYDFe2MDtjxgECz1k99dLSUkGB2CgCQo9SjpGIWxJSkfAVm\nwnzzmOZlFeY8AAAgAElEQVTq37p/QI4FBIu1ipMkpaSYnQAAJElJJ4oVpchensBnt6s4AGs42WTT\n6I6jGcVDyLPeMzQ11ewEACBJsnl9Sj3pky2Cf9mXOwMzibtXy15qndA6IMcCgsl6P+2MOAEIIVGF\n5WpeELlzckodjb+krllMMw1vNzwAaYDgs15xYsQJQIhJPFkcsRsAFzgbtyyD3WbX2E5j5bAHfhFN\nIBisV5ySk6UADQ0DQKCkHiuPyH3sch2NW4pgVIdRahnfMkBpgOCzXnGy2aTmzc1OAQDVOMo8apnl\nkN2CL6uNkaPyBn/u4DaDWSEclmPNn3BO1wEIQdF5pWpxJipiVhX3OhwqaOBSBBktMjQ4fXCAEwHB\nR3ECgACKPV2i1NzImO9U7HI16PM6JnfU6A6jA5wGaBrWLE5cWQcghMWfKlZKYfhvyVLgrP+vkLT4\nNF3Z+cqIGZVD+LFmcWLECUCISzxZrObFcca8zDCVV88L4dLi0zSx60Q28IWlWbM4RUWx9QqAkJd0\nvEgtcmPCdoHM0zb/5zd1Temq67tfrxhnZJzGRPiybu1PTZUKCsxOAQAXFH+qWM6yaJ1q4ZYnAFuT\nhAqf3a5cX5l0kQE1m2wa1GYQE8ERNqz7NojTdQAsIjq3VK2P2+RSwyZTh6ISV5R8FylNTrtT4y4Z\nR2lCWLFucWKCOAALcRa71fqQR3He8Jg0Xui68K+POFecru9+vbqkdGmiREDTsO6pupasNAvAWuxu\nr1oeKFZBWqzOJJXJ67PuqbvTdawYbpNNPVr00KVtL1W0M3L38EP4sm5xSkw0tl/JzTU7CQDUS0JW\nsWLznDrdJkZF9hKz4zRIpq3miuEpsSka3WG0WiW0MiER0DSsW5wkqV07ihMAS3KUuNXygFtFLWJ1\npplbbl/Dty5pamUul4qqbLXisrs0OH2w+qb1ZX0mhD3rF6dt28xOAQANFpddrNgcmwrTYpWbUC53\nA7cwaUr5US5J5bLJpkuaX6IR7UYoPire7FhAk7B2cUpPl+x2yes1OwkANJjN51NCZrHis2wqbBmr\nvES3yhuxeW6w5brsymiRof6t+is5JtnsOECTsvl8vtpn+FnFhx9Kx4+bnQIAAsZns6moZawK4r0q\ndZQqVF6mnTaXEkqiFHvF9YqKTzI7DmAKa484ScbpOooTgDBi8/kUn1WkeEmeKIeKUqJUGO9Tqa1U\nauIS5ZBTsW6X4vJ9ijlTKltKkkRpQgSzfnFq315at87sFAAQFI4yjxJPFitRkjvWpaJmLpXF+FTq\nCM6EcpvNpihvlGJLHYrNdSuqoEyqOu+qXbuAf03ASqxfnFJTpdhYqbjY7CQAEFTO4nIlFZ8rS55o\np0oTXSqLsaksyie3zSOP3PLKv3mfLptLTo9DLrddrjLJVeyWq8gtu7u07k+iOCHCWb84ScYP8p49\nZqcAgCblKHUrrtStuPNu9zns8jht8rrs8jnssnl9snklm9dr/OnxyubxyeYrl+ozCd3plFq3DuS3\nAFgOxQkAwozN45XTI6k0wCuTt2kjORyBPSZgMdbdq66qdu0kFl0DgODiNB0QJsUpNtaY6wQACB6K\nExAmxUniBxoAgik5WWre3OwUgOnCpzi1b292AgAIX127mp0ACAnhU5xatZKiosxOAQDhqVs3sxMA\nISF8ipPdLnXoYHYKAAg/aWlSEquFA1I4FSeJoWQACAZGm4BK4VWc2reXYmLMTgEA4cNul7p0MTsF\nEDLCqzjZbIw6AUAgtWvHG1KgivAqThLFCQACiddUoJrwK05pacZ6IwCAxnG5pE6dzE4RMEePHlVG\nRoYeffRRs6PAwsJjr7rzdesmbdhgdgoACEk+n0/L9u7Vf3bs0DcnT+p0cbFsktISEjQwPV139e+v\nAenpRmlyhs+viRYtWugvf/mL2rZtG9DjTp06VevXr69xe3R0tNq0aaOxY8fqvvvuU/MqC4jOnj1b\nL730Uo3HN2/eXD179tT48eN13XXXKTo62q8MjzzyiBYuXFjrfbGxserYsaOuvvpq3XvvvdWOefTo\nUY0fP16S9Mc//lHXXXfdBY+/c+fOWu93u90aM2aMsrOzNWXKFD3xxBN+5T5fVlaWXnvtNa1evVpZ\nWVnKy8tTbGysOnXqpPHjx2vatGmKjY1t0LEDJXx+Iqrq1k3auFHy+cxOAgAhJbekRA988IFWHz6s\nvq1b63sDBqhNYqLyy8q0PTNTn+zerQ927NDPR47U/ZMmmR03oGJiYjRhwoSgHf/pp59WUpVlG3Jy\ncrRu3Tq9/vrrWrx4sebNm6cWLVpU+5x77rlHgwYNkiSVlJTo+PHjWrFihX7961/r1Vdf1Ysvvqie\nPXv6neEXv/iFOlUZJfT5fMrKytKSJUv04osvatmyZfrXv/6lqFrWPXzuuec0ZswYJSQk1Hps2wX2\nhP3888+VnZ2tli1b6sMPP9SMGTMUU8+5cQcOHNBdd92l4uJi3Xzzzerbt6+io6OVmZmpJUuW6M9/\n/rMWL16sd955p9b8TSU8i1NiorGL9/HjZicBgJDh9fn08w8+0JrDh/XY2LGa9t0v7Kp+OmKEfjh/\nvmZ99ZW67typ8Wxn5RebzaaxY8cq9bx9U6dMmaK+ffvq97//vV599VX9+te/rnZ/v379apS5+++/\nX19++aUefPBB3XvvvZo/f77S09P9yjF8+HD169evxu1Tp07Vo48+qgULFujf//637rrrrmr3Dxs2\nTOvWrdOsWbP0+OOP13ps3wUGI959910lJibqF7/4hR599FF98sknuvnmm/3KXGHWrFk6c+aM/vrX\nv2rMmDHV7rv33nv10EMP6eOPP9bChQt1++231+vYgRR+c5wqZGSYnQAAQsrSvXu15vBh3dCrV62l\nSZJaJSbqheuu0xPTpqlv37417v/000911113aeDAgerfv7+uvfZavfzyyyorK6t8jM/nU0ZGhn74\nwx8qMzNTDz74oEaMGKG+fftq8uTJWrVqVY3jbt++XT/5yU80fPhw9enTR2PHjtXMmTOVmZlZ7XEF\nBQWaM2eOrr32Wg0aNEhDhgzRzTffrNdff/2Cv9il2uc4zZgxQxkZGcrMzNTf//53TZgwQX379tXl\nl1+uP//5z/J6vRc8pj9uueUWSar1dF5dxowZoyeffFJnzpzRrFmzGp1BUmXZqC3HsGHDdMMNN+jt\nt9/W9u3b63XcI0eOaNWqVbrqqqs0ceJExcXFad68efXOt3v3btntdl1++eW13j9jxgy9/PLLGjt2\nbLXbDx8+rF/96lcaNWqU+vTpo1GjRumhhx7S/v37axxj1apVuu2229S/f38NHz5cDz74oDIzM3X9\n9dfXKGt1Cd/idMklXEILAFX857tfiN+vozRV6N6ihabcd59atWpV7fZ//OMfeuCBB+RyufTYY49p\n5syZ6tmzp2bPnq0f//jHlY+rOKVTXFys6dOnKzU1VTNmzNC9996rvXv36ic/+YmysrIqH79x40bd\ncccd2rt3r+6//34988wzuuaaa/TBBx/o9ttvV3Z2duVjf/7zn+ull17S8OHD9cQTT+ixxx5Tenq6\nnnvuOT333HP1/jepyDp79mx9/vnnuvfee/Xoo48qPj5er776qv75z3/W+5jnqzit5Ha76/V5N954\no9LT07V48WKVlpY2OofL5ZIk2e21/+qfMWOG4uLi9NRTT120hFb13nvvSZJuuukmxcbG6uqrr9bm\nzZu1b9++euVLS0uT1+vVBx98UOf9Y8eOVcuWLStvO3jwoG699VatXbtWd999t5599lndcccdWrVq\nlW6//Xbt3bu38rHffPON/ud//kcnTpzQAw88oBkzZigxMVHTp09XUVGRHA6HXznD81SdJDkcxlyn\nrVvNTgIAIeHbzEzFulzqfV4hqqFZM6nKLyfJmLQ7a9YsjR07Vq+88krl7bfccotatmyp1157TUuX\nLq2caCxJmzZt0mOPPaZp06ZV3lZQUKC5c+dq5cqVlSMxTz75pFq2bKl58+Yp+burom+44QYNGzZM\n999/f+UprrNnz2rVqlUaM2aMfvOb31Qec/LkyXr66aeVn5/f4H+bnTt3at68eZWlol+/frr11lu1\ndOlSff/732/wcSVVjrDVNoJ3McOGDdPChQu1Y8cODRgwoFE5PvvsM0mq9VSeJKWmpuqBBx7Q7373\nO82bN0933HHHRY/pdrv1/vvvq127dho2bJgk4zmxYMECzZs3r15XME6bNk3r1q3TjBkz9Mknn2ji\nxIkaMmSI2l3gdPFzzz0nr9eruXPnqn379pW3X3XVVbrlllv0wgsv6OWXX5Ykvfrqq3K73XrxxRc1\nePBgSdLNN9+sl156SbNnz/b7ooHwHXGSOF0HAFXkFBWpRXx8rfcVlJUpr6TE+GjbVnl5ecrLy6u8\nf9myZSovL9c111xTeV/Fx1VXXSVJWrt2bbVjOp1OTZkypdptvXv3lqTKUaR9+/Zpz549uvzyy2Wz\n2aodd9CgQUpOTta6deskSQ6HQ3a7Xfv27dPp06erHffxxx/XM8880+B/mylTplQbienVq5dsNlu1\nkbEL8fl8ys/Pr5b/0KFDmj9/vmbOnKm4uDj96Ec/qneuitGV87/fuhQWFlbLkJubq127dunFF1/U\n3//+d7Vv3/6C84Puuusu9erVSy+88IJfX3PZsmXKzs7WTTfdVHnbkCFD1L59ey1cuLDaKdyLufLK\nKzV79my1b99eX375pR555BGNHz9eo0eP1owZM7R8+fIa3+vKlSs1ePBgNWvWrNr3nZ6erq5du1Y+\ndyRpzZo1SktLqyxNFe68806/M0rhPOIkSc2bS61bSydPmp0EAExnt9nkqWPOzq1vvaWDZ84Yf6ly\n9VTF5ecV80UefvjhWj/fZrPp5Hmvta1bt648PVSh4lL48vJyScaVVJL0zjvv6J133rlg/sTERE2b\nNk2vv/66xo8fr7Fjx2rEiBEaPXp0jdOK9dWxY8dqf7fb7XI6nfU6vTZx4sRab+/bt69mzpypzp07\n1ztXxdf39zTSD37wg1pvdzqduuKKK/S73/3ugpfz22w2Pfnkk7rzzjv1hz/8Qc8+++wFv17FKN35\nE8Fvvvlm/eUvf9GSJUsqlzjw+Xw6U/Ec+47L5VJiYmLl38ePH68rr7xSmzZt0tq1a7Vx40Z9/fXX\nWrRokRYtWqShQ4dq9uzZatasmQ4fPiyPx6Ply5dr6NChdX4/BQUFKi8vV2FhYa1XKKamplaOdPoj\nvIuTZIw6UZwAQGkJCcosKJDb65XzvHkuv580SaVut9S5s3y9eumZZ57Rrl27Ku8vKiqSJD322GN1\nXh5f9VJ8SX5dMl5YWCjJ+EU7efLkWh9T9TL4Rx55RAMGDNC//vUvLV68WB999JFsNptGjRqlp556\nyu+rz84XiMvb58yZU+0XcFRUlNLT06vNyamvY8eOSZLfxfCJJ55Q1yqrve/Zs0e//e1vNX78eL8n\nmVecpnzvvfd0yy23aMiQIbU+rmJSeLNmzfT+++9Xu69ipG7evHmVxenYsWPVTuVKxqnIN998s9pt\nNptNgwcPrhwZcrvdWrVqlebMmaP169fr+eef17PPPlv53Bk9erTuu+++Or+fqKioytO4dS2RUJ+l\nE8K/OHXuLK1ZI5WUmJ0EAEw1KD1di7Zv1/qjRzWiQ4dq9/Vr3drY0Pe226T4+GqjAJIU/90pvrS0\ntDrf3TdExXFjY2P9Pu7EiRM1ceJEFRQUaM2aNVq4cKGWLl2qe++9Vx999JHfozOBZLPZNHDgwBrL\nETRGaWmp1q5dq+TkZPXo0cOvz+ndu3e1OUxDhw7VmjVr9Omnn9aYg3YhDz30kD777DM99dRTdS6s\nWXHlXG5ubo3FPCusW7dOhw4dUseOHZWWllZjsv35z7PaVIyWDR48WKNHj9bKlSslqXK9KbvdftHn\nTsVIZ12T7AsKCtSsWbOLZpHCfY6TZKx624AJeQAQbm797rXw1fPmIlXq2lWqMgeq6pVV3bp1k2Rc\nAXe+srIyFRQUNCjThY4rXXhuT0JCgsaPH685c+boqquu0sGDB6tdRWV1c+fOVW5uriZPnnzBxScv\n5vHHH1dCQoKefPLJavPWLiQ5OVm/+tWvtGfPHr3++us17i8vL9f777+v5ORkbdmyRTt37qzx8fzz\nz0s6d9VdVFSUhg4dWu0j47u5yNu3b9fTTz+txYsX15kpISFBycnJKvluIKRTp05yOp3aunVrradU\nqz53mjdvrtjY2MoRvKqOHj1aOXrlj/AvTpLUu7dk4iqjABAKhrZrp2szMrTm8GE9/fnncled72Sz\nSf37y+v16q233tLmzZurnb648sorFRUVpf/85z81yszrr7+uyy67TBsasNVVx44d1bNnT+3atUur\nV6+udt/XX3+tkSNH6m9/+5sk6csvv9S4ceMqRxyqqhi5MnNF6UD65JNP9MILL6ht27a6//77G3Ws\ntLQ0Pfjgg8rOzr7onKWqJk+erEGDBmnOnDk15q8tW7ZMOTk5uv766+v8N584caKSkpK0YMGCi84V\ns9vtmjt3rp5//vkaa3dVWLx4sU6ePKnLLrtMknF6bezYsTp9+rQWLFhQ7bFHjhzRuHHj9NRTT0ky\nRgSHDh2q48eP6+uvv6722IvNrTtf+J+qk4zS1KePtGmT2UkAwFTPXn21JOmtzZu18uBBXZeRoQ7N\nmqksOVmH/vEPLVmyRIcPH1a3bt30+9//vvLzUlJS9Mtf/lLPPPOM7rzzTk2dOlUJCQlat25d5aTd\nQRdZH6ouTzzxhO655x799Kc/1Q9+8AO1b99e+/fv19y5c9WyZUvdcMMNkqRBgwbJ4/Ho5z//ue68\n8051795dPp9Pmzdv1qJFizRy5Ehdcskljf9HaoD6rHtU1ZYtWyqv5vN6vcrMzNQXX3yhdevWqVOn\nTnrllVfqNXG5LnfddZcWLVqkBQsWaNKkSRo9erRfn/fEE0/olltu0Zo1a6rdXnGa7rbbbqvzc6Oj\no3XDDTforbfe0ueff37B7W4yMjL00EMP6U9/+pOuv/56XXfdderdu7eio6N1+vRprV27Vl9++aXa\ntWtXbYmDhx9+WBs2bNBTTz2l/fv3q2fPnjp27Jjmzp0rh8NRbUmF6dOn66uvvtJPf/pTTZ8+XUlJ\nSdqwYYO2bt1ar3lokVGcJON03dat0ndXcgBAJIpyOvWna6/VrX366N/ffqsF27Ypp6hIjqgotUxL\n08CBAzVjxgxdeeWVNT532rRpSk9P1xtvvKFZs2aptLRU7dq10/3336/77ruvzoUVq7LZbDVOOw0Y\nMEDvvvuuXnrpJc2dO1f5+flKSUnRhAkT9NOf/rRyYnRSUpLmzZunV155RYsXL9bcuXMlSR06dNDP\nfvYzTZ8+vd7/HrXlqXpffY5T368rSW+88YbeeOONytuSkpLUvXt3/eY3v9Ftt93m9wjahb6Pivt/\n+9vf6tZbb9UTTzyhDz/8UHFxcRc9bo8ePXT33Xfr9ddfrzz+kSNHtHr1avXr1++ic69uu+02vfXW\nW5o3b95F9wmcPn26hgwZorffflurVq3S/Pnz5Xa7lZCQoK5du+oXv/iFpkyZUi13+/bt9d577+ml\nl17Shx9+qH/+859KSkrSsGHD9P/+3/9T9+7dKx87bNiwys2VX3jhBcXExGjEiBH6xz/+Ua8lCWy+\nhtZkK1qzRvrmG7NTAEBoadVKuvFGs1MAphk3bpxsNpuWLVt20cdGxhynCv37G5PFAQDn9O9vdgLA\nMiKrOMXGSn5e0gkAEaFZM6lTJ7NTAJYRWcVJkgYMMNYqAQAw2gTUU2TNcaqwYoX03TYCABCx4uOl\nKVN4MwnUQ2T+tDDqBADGMi28FgL1Epk/MUlJUpcuZqcAAPNERUm9epmdArCcyCxOkjRwYLUdwAEg\novTtK7lcZqcALCdyi1OzZpJJK8wCgKkSEpgUDjRQ5BYnyRh1AoBIc+mlrGkHNFBkF6fUVGM3cACI\nFK1bM8cTaITILk6SNHy4MUkSAMKdzSZ9t7M8gIahOMXFSYMHm50CAIKvRw+pRQuzUwCWRnGSjLVM\nUlLMTgEAwRMVJQ0danYKwPIoTpIxfD1ypNkpACB4Bg409usE0CgUpwpt2kjdupmdAgACLznZWLcJ\nQKNRnKpiojiAcDR8OFurAAHCT1JVsbFMFAcQXtq3lzp2NDsFEDYoTufr08dY3wkArM5ul0aMMDsF\nEFYoTudjojiAcNGrl7G9FICAoTjVpnVrqXt3s1MAQMPFxEhDhpidAgg7FKe6XHopE8UBWBevYUBQ\nUJzqEhvLuzUA1tShg7FKOICAozhdSO/ebE8AwFpiYqTLLzc7BRC2KE4XYrNJV1whORxmJwEA/4wc\naezBCSAoKE4Xk5pqLB4HAKGuSxfjA0DQUJz80bu31KmT2SkAoG5xcdKoUWanAMIexclfV1whJSSY\nnQIAanf55VJ0tNkpgLBHcfJXdLQ0diz7PQEIPb16GVfSAQg6WkB9tGkjDRxodgoAOCclhW1VgCZE\ncaqvQYOMAgUAZnM6pSuv5MpfoAlRnOrLZpPGjTPWSgEAMw0fLjVvbnYKIKJQnBoiPt6YLA4AZrnk\nEmNuE4AmRXFqqI4dpT59zE4BIBIlJLA6OGASilNjXHqpsUAmADQVu924wpelBwBTUJwaw+EwJma6\nXGYnARApRo7kAhXARBSnxmrWTLrsMrNTAIgEfftKPXuanQKIaBSnQOjRgxczAMHVsSP7ZgIhgOIU\nKKNGSW3bmp0CQDhq0cKYFmCzmZ0EiHgUp0Cx2aSrrmJNFQCBFR8vXX21sdglANNRnAIpKkqaOFGK\njTU7CYBw4HIZpSk+3uwkAL5DcQq0xETeHQJovIpdClq0MDsJgCooTsGQliaNGcN8BAANd+mlxoRw\nACGF4hQsnTtLw4aZnQKAFfXsKfXrZ3YKALWgOAVT//7GuisA4K+2bY2rdAGEJIpTsI0YIXXtanYK\nAFbQvLlxdS6n+YGQRXFqCmPGSO3amZ0CQCiLjTWuyo2KMjsJgAugODUFu914F9mypdlJAISi6Gij\nNCUmmp0EwEVQnJqKyyVdc42xtx0AVIiJka67jjdWgEVQnJpSTIxRnnhXCUA6V5pSU81OAsBPNp/P\n5zM7RMQpLJQ++kg6e9bsJADMEhtrlCa2aQIsheJkluJi6eOPpZwcs5MAaGpxcUZp4tQ9YDkUJzOV\nlkqffCJlZZmdBEBTiY83SlNystlJADQAxcls5eXS4sXS8eNmJwEQbAkJRmlKSjI7CYAGojiFAo9H\n+uwz6fBhs5MACJbERKM0cXEIYGkUp1Dh9Uqffy7t3292EgCBlpRklKaEBLOTAGgkilMo8fmkFSuk\nXbvMTgIgUJKTjdIUH292EgABQHEKRf/9r/Ttt2anANBYzZoZpSkuzuwkAAKE4hSqNmyQNm0yOwWA\nhkpNlSZNMtZrAhA2KE6hbMsWae1as1MAqK9LLpHGjpWcTrOTAAgwilOo277dOHXn9ZqdBMDF2GzS\noEHS4MFmJwEQJBQnKzh+XFq2zFhtHEBocrmkMWOM0SYAYYviZBWFhcZaT6wyDoSexETp6qullBSz\nkwAIMoqTlXg80qpV0s6dZicBUCE9XRo/XoqJMTsJgCZAcbKiHTuMeU8ej9lJgMjWq5d02WWS3W52\nEgBNhOJkVVlZxqm7wkKzkwCRx26XRo6UevY0OwmAJkZxsrLiYmPSOBsEA00nJka66iqpTRuzkwAw\nAcXJ6nw+Y62nb74xOwkQ/lJTpQkT2KgXiGAUp3Cxb5+0fLnkdpudBAhPnTsbyw2wqCUQ0ShO4eT0\naWnJEikvz+wkQPhwOqXhw42J4AAiHsUp3JSVSV98IR06ZHYSwPrS0oytU5KTzU4CIERQnMLV7t3S\n6tVSaanZSQDrsdulAQOMrVNsNrPTAAghFKdwVlwsffWVdOCA2UkA60hKMkaZWrUyOwmAEERxigQH\nDhgrjhcVmZ0ECG09exrzmVwus5MACFEUp0hRWmqcutu92+wkQOhJTJQuv1xq29bsJABCHMUp0hw5\nIq1cKRUUmJ0EMJ/NJvXuLQ0bxjIDAPxCcYpE5eXGopk7dhgLaAKRqFkzY5SpdWuzkwCwEIpTJDtx\nwlg0k3WfEEnsdqlvX2nIEMnhMDsNAIuhOEU6j0dav17aupXRJ4S/du2kSy81tk4BgAagOMFw6pS0\nYoWUk2N2EiDwUlKMwtS+vdlJAFgcxQnn+HzSnj3GCFRhodlpgMaLjzdOyXXvzkKWAAKC4oSaPB7p\nm2+kLVuMLVwAq3G5pP79pX79uFoOQEBRnFC3khJp0yZp+3bJ6zU7DXBxdrvUo4cxyhQba3YaAGGI\n4oSLy801Tt8dOMAEcoSuDh2MeUzNm5udBEAYozjBfzk50saN0sGDZicBzmnRwtgmJT3d7CQAIgDF\nCfV36pS0YYOxCjlgloQEaehQqVs3s5MAiCAUJzRcZqZRoI4dMzsJIkmLFsYCll26GHOaAKAJUZzQ\neCdOGAtoHj7MJHIEh80mdexoFKY2bcxOAyCCUZwQOAUFxv53O3dKxcVmp0E4cLmMq+T69JGSksxO\nAwAUJwSBxyPt3y9t2yZlZZmdBlaUmGiUpR49pKgos9MAQCWKE4Lr1CmjQO3fL7ndZqdBqGvd2jgd\n16kTK30DCEkUJzSN0lLjFN727VJ+vtlpEErsdqlzZ6MwtWxpdhoAuCCKE5qWz2dMIt+2zbgaj6df\n5EpKMq6M69XL2FMOACyA4gTz5OYaI1D797OpcKRITDRGlzp3ZnQJgCVRnBAasrKMFckPHDAKFcJH\nQsK5spSWZnYaAGgUihNCz5kzRoE6eFDKzjY7DRoiPv5cWWrVyuw0ABAwFCeEtvx8o0AdPCidPMmc\nqFAWF3euLLVubXYaAAgKihOso7hYOnTIKFHHjhnrRcFciYlShw7nyhJLCAAIcxQnWFN5uXF13pEj\nxls1pbUAABLJSURBVJ55zItqGvHxUnr6uY/ERLMTAUCTojghPJSUGBPMMzONP0+dksrKzE5lffHx\nxkhSRVFKTjY7EQCYiuKE8OTzGZPMK4pUxagUT/e6ORxSaqoxmbvig/WVAKAaihMiR2mpUaIqitSp\nU8ZtkSg21hg9SkqSUlKMktSihVGeAAB1ojghsuXlGSNR5/+Zny95vWana5zoaKMcVRSkiv9OTmbj\nXABoIIoTUBufzyhP+flSQYHxUVhofFT8t9lzqJxOowDFxVUvRRUf0dHm5gOAMERxAhqqrEwqKpLc\nbuPD4zn33+f//UL/7XBILpdRgurzJ5f+A0CTozgBAAD4yW52AAAAAKugOAEAAPiJ4gQAAOAnihMA\nAICfKE4AAAB+ojgBAAD4ieIEAADgJ4oTAACAnyhOAAAAfqI4AQAA+IniFAQZGRmaOnWq2TFqOHXq\nVNCyTZ06VRkZGQE/LgAAoSSgxWn27NnKyMjQxx9/fMHHZWRk6Jprrgnklw45tkZswLpo0SKtW7cu\ngGmqq0+2M2fOqG/fvsrIyNDf//73gB3XX263WwsWLNB9992nUaNGqU+fPhowYIAmTZqkmTNnau/e\nvQH/mgAA1MW0Eadg/JINF7NmzQpqcaqPhQsXqry8XC1bttR7773XpF/7xIkTuu222/Too4+qvLxc\n06dP1/PPP69f/vKX6tWrlxYtWqTJkydrwYIFTZoLABC5nGYHCISysjJFRUWZHSMgcnJydOLECbNj\nVHr33XfVuXNn3XTTTXrhhRe0bt06DRs2LOhft7i4WD/60Y906NAhzZo1SxMnTqx2/9133609e/bo\nhz/8oR5//HF1795dvXv3DnouAEBkC4k5TmvWrFFGRoZee+01LV26VJMnT9aAAQN06aWX6uGHH1ZO\nTk7lY48ePaqMjAw9/vjjWrhwoUaNGqU77rij8v7CwkL98Y9/1IQJE9SnTx8NGzZMP/jBD7Ry5coa\nX/fQoUP68Y9/rMGDB2vIkCH6yU9+oqNHj+qhhx5SRkaGjh07Jklau3atMjIyNGfOnBrHmDlzpjIy\nMi46QrR//3498sgjlaebRo8erR/96EfasmVL5WNmz56tkSNHSpLmzJmjjIwMLVy4sPL+7du36yc/\n+YmGDx+uPn36aOzYsZo5c6YyMzNrfL3//Oc/uu6669S3b19dfvnleu6551RaWnrBjOdbt26dDh48\nqGuvvVbXXnutbDab5s2b59fnVsx5qutj/fr1F/z8d955R3v37tX06dNrlKYK3bp105/+9Cc9/fTT\nSk9Pr/UYFc+lgQMHavLkyXrrrbfk8/kqH3PkyBFlZGRo5syZ2rdvn+677z4NGzZM/fv31913361t\n27bVOO7q1at17733aujQoerXr58mTJig3//+98rLy6v2uOzsbD377LO6+uqrK5/Pd955Z7X/pwAA\nawmJEaeK03Zr167Vm2++qSlTpqhNmzZas2aN5s+fr927d+v999+X3X6u5+Xk5GjOnDn63//9X6Wl\npUmSSktLNW3aNO3du1e33367+vXrp5ycHM2fP1/33XefnnvuOd14442SpPz8fE2dOlU5OTmaOnWq\n+vTpo/Xr12vatGm65JJLquWqz/dQm8zMTN11111yu92aPn26OnTooJMnT+rNN9/U9773Pb399tvq\n27evJk2aJJvNpjlz5uiaa67RNddcoz59+kiSNm7cqHvuuUfp6em6//77lZKSop07d+rtt9/W8uXL\nNX/+fLVo0UKStGTJEj388MPq2LGjHnzwQcXHx2v58v+/vXsPqqra4wD+PQLy0gENQ1SIINy8HFBg\nhoeYoEH4IjCgGnk4pWYCajkjZGYiE0MOoRZDwQQcCRUUSE8IggNkNmAyg5LCcQA1HloRD3kdQWDd\nP7j7yOYc4Nhlijv9PjPMyNprr732Y2b/WOu3lz/go48+eoa7MjraJBKJ4Ovri8WLF8PJyQnFxcV4\n9OgR9PT0Jt03MjISnZ2dgjKZTIaYmBiIRCIYGxtPuv+FCxegpqY2ZSK7k5MTnJycFMpjYmJw6tQp\neHl5ITg4GIODgygtLUVsbCykUiliY2MBPL1vbW1t2LZtGzZu3Ij169ejpqYGp06dwo4dO1BaWiof\n0bx48SI++OADWFlZYc+ePdDV1UV1dTVOnjyJq1ev4uzZs9DU1MTw8DDCwsLQ1NSEsLAwWFhYoL+/\nH99//z2ioqLQ3d2NkJCQSc+NEELIDMSm0YkTJxjHcaygoGDSehzHMR8fH/nvlZWVjOM4ZmNjw+7d\nuyeou2/fPsZxHLt8+TJjjLHm5mbGcRyztrZmVVVVgrppaWmM4zhWVFQkKO/r62Oenp7M2dmZDQ0N\nCeoeP35cUDc5OZlxHMcsLS1Za2uroH9ffPGFwrkcPHiQcRzHfv75Z8H5BQcHy3//6aef2DvvvMO+\n++47wb5XrlxhHMexDz/8UOFajD/Whg0bmIeHB+vq6hKUl5WVMY7jWGxsrLzM19eX2djYsJaWFkHd\nnTt3KvRtIh0dHczW1pZt2bJFXpafn884jmNisVih/pYtW5ilpeWkbUZFRTGO41hhYeGk9QYGBpiV\nlZXgGXkWv/zyC+M4jsXExChsi4iIYBzHsdraWsbY0+dp7DPG27FjB+M4jlVUVDDGGJPJZMzFxYX5\n+/uzgYEBQd1vv/2WcRzH0tPTGWOM3b59m3Ecx44cOaLQh71797KjR4/+pXMjhBDyz5oRU3U8Z2dn\nmJqaCsrWrVsHALhx44ag3MDAAA4ODoKywsJCzJ07F66uruju7pb/DA0N4eWXX0ZnZyfq6+sBjE4P\nAsCmTZsEbYSEhEx7vpSrqytSU1Plo119fX3o7u6GkZERAEyZ09TY2Ij6+nqsWrUKIpFIcG4rVqyA\nnp6efKqwq6sLUqkUdnZ2WLx4saCdgIAAlfucn5+PJ0+eYPPmzfIyb29v6Ojo/KUk8XPnziE/Px8h\nISETTr3xHj16hJGREflI4ng9PT2Ca9Dd3Y3e3l759qKiIgCAj4+PQj1vb28Ao6ObYxkZGWHNmjWC\nMj5n6s8//wQwOnXZ0dEBLy8vPH78WNCuh4cHRCKR/D6oqakBAG7dugWZTCZo9/PPP8e+ffsmvQaE\nEEJmphkxVcezsLBQKONfnvzLizc+KABG84h6e3uVTt0Ao9MyDx48gKWlJR48eACRSAQTExNBHR0d\nHVhYWKC2tvavnoZSEokEGRkZaGxsxOPHjwXbhoaGJt333r17AEZzds6cOTNp3ZaWFgBQOhVmZmam\ncn9zcnKgo6MjDzQAQFtbGz4+PsjNzUV1dTWWL1+uUltSqRQxMTGwt7fH/v37p6zPT8kODw8r3e7q\n6oonT54IyhYtWoTS0lIAo88BMJpAroxIJMJvv/0mKBv/HACApqYmgKf3h283MTERiYmJStvm2+U4\nDl5eXiguLsbq1auxdu1auLi4wM3NDfPmzVO6LyGEkJlvWgMnVXKC2H8Tc8fmK/F0dHQUyubMmQMA\nCom3urq6CnX7+/thYGAw4UsNAMzNzQGM5ttoaGgo7cfcuXMFCcT/q7Nnz+LgwYNYtGgRdu/eDXNz\nc2hra6OrqwsRERFT7t/X1wcA8PPzg7+/v9I6/LXngzJlo2ZaWloq9ffatWu4f/8+TExMFNZu4kd2\ncnJyVAqcenp6EBkZiTlz5uD48ePykZjJ6OvrQ0NDY8KRuPT0dPn9YYzh/fffFzx7/f39AEZHdhYs\nWKC0jfHlqowy8u1u374d7u7uSuvwwRZ//Pz8fJw7dw55eXnIzc2Furo6vL298fHHH0+ZJ0YIIWTm\nmdbAiQ9y+Be9MnzCsL6+vsK28VMawOiLF4BKLxldXV309fVNOOI01uzZsycc6ent7VU5MVyVL9XS\n0tKgrq6O9PR0vPDCC/JyfgRjKnyQqK2tPeW58S/uwcFBhW2T3ZexsrOzAYx+cZaUlKS0TlFREQ4c\nOCC/5xOJjo5Ga2srUlNTYWhoqNLx1dTUYGdnh6qqKjQ1NSmMBjk6Ogp+Hx/08NfL2NgYy5YtU+mY\nquDb1dPTU+kZU1dXR0BAAAICAtDZ2SlPHi8oKEB7ezsyMjKmrW+EEEL+HtOa4zT2C7CJVFRUAADs\n7OwUtjU2NiqUNTU1AVAcIVDmpZdegkwmQ11dncK2rq4uwSiSoaEhRkZG5EsO8GQymTwPiqeuPhpf\n8iMOY92/f3/KfrW0tGDhwoWCoAkAqqqqptwXAJYuXQpg4uva0dEh/zc/hdnc3KxQb/x5TdRWSUkJ\nzMzMUFdXB6lUqvATGRkJmUwGiUQyaVtpaWm4fPkydu3aBVdX1ymPPdbrr78OAPjqq6+eaT/g6ZSv\nsuvV39//zMsy8J7lPow3b948bNy4EWKxGNbW1qisrBTkZRFCCPn/MK2Bk4ODAywtLVFQUIDq6mqF\n7W1tbUhMTISmpibeeusthe2VlZXyHB0en+iryl/4fCJ5WlqaoHxgYABhYWGCRPAVK1YAGE0oHysz\nM1PhxcrnWUmlUkF5TU0NampqphydMjAwQHt7uyC36eHDh8jMzAQgHB3ip7LGlpmYmMDKygp37tyR\nB568GzduwM3NDampqQCA+fPnw9zcHDdv3lSY6lJlDSY+KXyyRPLNmzdDTU1t0iTxqqoqJCQkwN3d\nHe+9996Uxx1v06ZNcHR0RF5envzcxhscHMSxY8fw8OFDwTQkn3x++vRphXsZHx8PFxcXpYHlVBwd\nHfHcc8/hypUrCqOFFy9exMqVK1FQUABg9FqvWrVK4b+EEYlE0NXVhbq6ukrTloQQQmaWac9xOnbs\nGEJCQhAaGgpfX19YWVlBQ0MDDQ0NOH/+PGQyGT777DOlyd3Lly9HSEgIAgMD5es4FRcXw97eHitX\nrpzy+G+88QYkEgkkEgkGBgbg6emJ3t5e5Obm4s6dOzhy5Ii8bmBgIMRiMU6cOIGuri6YmZnh5s2b\nuH79OpycnAQLNBobG2Pp0qWoqKjA4cOHYWdnh+bmZuTk5GDDhg1TjrysW7cO33zzDSIiIrB+/Xr8\n8ccfyMzMRHR0NOLi4lBbW4vs7GysWbMGS5YsgUgkwoULF6Cvrw+O4+Dm5oZDhw4hLCwM4eHh2Lp1\nK4yNjXH37l1kZWVhwYIFgqBw+/bt2L9/P95++20EBgZCS0sL5eXlKr2oc3JyMHv2bLz22msT1jE0\nNIS7uzvKy8tx+/Zt+ddn/IheX18f9u7dC5FIhLVr18qD37GWLFkiH6FUZtasWUhKSkJkZCQSEhJQ\nWFiIV199FQsXLoRMJkNDQwOKiorQ1tYGBwcHxMfHy/e1tLREaGgoxGIx3nzzTQQFBUFNTQ0//PAD\nSkpK4OvrO+U6UspoaGjgk08+wZ49exASEoKwsDAYGBjg1q1byMnJgbm5OVavXg1g9AvRo0ePIjQ0\nFEFBQTA1NcXg4CCuXr2K69evIzAwENra2s/cB0IIIf+saf+qztTUFBKJBGlpaSgrK4NEIsHw8DCM\njIzg5eWFrVu3yheYHM/R0RHBwcFITk5GQ0MDtLS04Ofnh6ioKJWOraGhgYyMDKSkpKCwsBBlZWXQ\n0NCAra0tvvzyS8Hn5oaGhkhLS0N8fDwyMzOhq6sLNzc3iMVi+fHGBhrJycn49NNPcenSJZw/fx62\ntrZISkpCRUUFRCLRpMnkERERGBgYQElJCaqqqsBxHGJiYuDh4QGZTIb4+HgkJibCzs4OlpaWePfd\nd5GZmYmkpCRERETAzc0N9vb2yM7ORlJSErKystDT04P58+fDy8sL4eHhgvwhX19fDAwMID09HQkJ\nCdDT04OPjw92794NJyenCftaWVmJX3/9FT4+PlN++RUYGIjy8nLk5OTg8OHDAJ4mqHd2dqKtrQ0i\nkQiHDh1Sur+fnx/i4uImPYaenh7EYjEuXboEiUSCrKwsdHR0QEtLC88//zw8PT3h4+MDZ2dnhX2j\no6NhYWGB7OxsxMXFYWRkBC+++CKioqKeaeHJ8aOJr7zyCsRiMb7++mukpKSgv78fhoaGCAoKwq5d\nu+R5UCYmJjhz5gxSUlKQl5eH9vZ2qKurw9zcHAcOHJjwiz9CCCEzm4hN5+djf9G1a9cQGhqK8PBw\nhIeH/9Pdgb+/P6RSKaqrqwVfSRFCCCHk321GLYD5d5JKpdi5cydOnjwpKK+vr0ddXR2sra0paCKE\nEEKIwIxaAPPvZGpqirt37+LHH39Ea2srbGxs8Pvvv0MsFmPWrFkqra9ECCGEkH+Xf23gpKWlhays\nLCQnJ6O0tBSnT5+GpqYmli1bhm3btsHFxeWf7iIhhBBCZpgZkeNECCGEEPL/4F+b40QIIYQQ8qwo\ncCKEEEIIUREFToQQQgghKqLAiRBCCCFERRQ4EUIIIYSoiAInQgghhBAVUeBECCGEEKIiCpwIIYQQ\nQlREgRMhhBBCiIoocCKEEEIIUREFToQQQgghKvoPpbwv8FxH1kUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7feba94c0240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Generate the venn diagram for the upregulated genes in Alz's disease and genes in PD RNA-Seq\n",
    "intAlzUpRNA = [len(alzUpGenes)-len(intersectAlzUpRNA), intAlzUpRNAFalse, len(intersectAlzUpRNA)-intAlzUpRNAFalse]\n",
    "intAlzUpRNAPDVenn = venn2(intAlzUpRNA, ['Upregulated Alz Genes',\n",
    "                                          'Genes in PD RNA-Seq'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "intAlzUpProtFalse = sum(intersectTabUpProt['foldChange'] < 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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PD3VVTWaXQhS1GKQOsWP9XtgcXNIjough2yTs21YDVVHNLoUoKjFIHdBS347e7j6zyyAi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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7febbf74a898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Generate the venn diagram for the upregulated genes in Alz's disease and proteins in PD MS3P\n",
    "intAlzUpProt = [len(alzUpGenes)-len(intersectAlzUpProt), intAlzUpProtFalse, len(intersectAlzUpProt)-intAlzUpProtFalse]\n",
    "intAlzUpProtPDVenn = venn2(intAlzUpProt, ['Upregulated Alz Genes',\n",
    "                                          'Proteins in PD MS3P'])\n",
    "intAlzUpProtPDVenn.get_patch_by_id('10').set_color('#613F75')\n",
    "intAlzUpProtPDVenn.get_patch_by_id('01').set_color('#7D82B8')\n",
    "intAlzUpProtPDVenn.get_patch_by_id('11').set_color('#E5C3D1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Symbol</th>\n",
       "      <th>log2FoldChange</th>\n",
       "      <th>foldChange</th>\n",
       "      <th>pvalue</th>\n",
       "      <th>padj</th>\n",
       "      <th>qvalue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>225</th>\n",
       "      <td>DLD</td>\n",
       "      <td>-0.063471</td>\n",
       "      <td>0.956959</td>\n",
       "      <td>4.106793e-03</td>\n",
       "      <td>0.064655</td>\n",
       "      <td>0.041547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>257</th>\n",
       "      <td>OPA1</td>\n",
       "      <td>-0.068977</td>\n",
       "      <td>0.953314</td>\n",
       "      <td>5.109362e-03</td>\n",
       "      <td>0.070252</td>\n",
       "      <td>0.045144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>216</th>\n",
       "      <td>CS</td>\n",
       "      <td>-0.075342</td>\n",
       "      <td>0.949117</td>\n",
       "      <td>3.803462e-03</td>\n",
       "      <td>0.062363</td>\n",
       "      <td>0.040074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>VDAC1</td>\n",
       "      <td>-0.078594</td>\n",
       "      <td>0.946980</td>\n",
       "      <td>1.701323e-04</td>\n",
       "      <td>0.011006</td>\n",
       "      <td>0.007072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>269</th>\n",
       "      <td>MICU1</td>\n",
       "      <td>-0.079595</td>\n",
       "      <td>0.946323</td>\n",
       "      <td>5.594906e-03</td>\n",
       "      <td>0.073728</td>\n",
       "      <td>0.047377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>NNT</td>\n",
       "      <td>-0.082885</td>\n",
       "      <td>0.944167</td>\n",
       "      <td>2.412585e-03</td>\n",
       "      <td>0.049941</td>\n",
       "      <td>0.032092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>NDUFB11</td>\n",
       "      <td>-0.083626</td>\n",
       "      <td>0.943683</td>\n",
       "      <td>4.040400e-03</td>\n",
       "      <td>0.063892</td>\n",
       "      <td>0.041057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>CNTNAP2</td>\n",
       "      <td>-0.085431</td>\n",
       "      <td>0.942503</td>\n",
       "      <td>2.169302e-04</td>\n",
       "      <td>0.012864</td>\n",
       "      <td>0.008266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>NDUFV2</td>\n",
       "      <td>-0.086275</td>\n",
       "      <td>0.941951</td>\n",
       "      <td>2.907925e-03</td>\n",
       "      <td>0.054914</td>\n",
       "      <td>0.035288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>COX7A2L</td>\n",
       "      <td>-0.086373</td>\n",
       "      <td>0.941888</td>\n",
       "      <td>2.328876e-03</td>\n",
       "      <td>0.049495</td>\n",
       "      <td>0.031805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>DLAT</td>\n",
       "      <td>-0.089265</td>\n",
       "      <td>0.940002</td>\n",
       "      <td>1.556205e-04</td>\n",
       "      <td>0.011006</td>\n",
       "      <td>0.007072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>PDHX</td>\n",
       "      <td>-0.089637</td>\n",
       "      <td>0.939759</td>\n",
       "      <td>9.415332e-04</td>\n",
       "      <td>0.031480</td>\n",
       "      <td>0.020229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>STXBP5L</td>\n",
       "      <td>-0.089774</td>\n",
       "      <td>0.939670</td>\n",
       "      <td>5.127288e-04</td>\n",
       "      <td>0.023534</td>\n",
       "      <td>0.015123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260</th>\n",
       "      <td>SUMO2</td>\n",
       "      <td>-0.092139</td>\n",
       "      <td>0.938131</td>\n",
       "      <td>5.237995e-03</td>\n",
       "      <td>0.070966</td>\n",
       "      <td>0.045602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>RGS7</td>\n",
       "      <td>-0.094444</td>\n",
       "      <td>0.936633</td>\n",
       "      <td>1.101768e-03</td>\n",
       "      <td>0.033505</td>\n",
       "      <td>0.021530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>ADAM23</td>\n",
       "      <td>-0.096330</td>\n",
       "      <td>0.935409</td>\n",
       "      <td>3.763254e-03</td>\n",
       "      <td>0.062363</td>\n",
       "      <td>0.040074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>AUH</td>\n",
       "      <td>-0.099059</td>\n",
       "      <td>0.933642</td>\n",
       "      <td>1.341490e-03</td>\n",
       "      <td>0.036199</td>\n",
       "      <td>0.023261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>COX4I1</td>\n",
       "      <td>-0.101120</td>\n",
       "      <td>0.932309</td>\n",
       "      <td>1.331807e-03</td>\n",
       "      <td>0.036199</td>\n",
       "      <td>0.023261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>NDUFS4</td>\n",
       "      <td>-0.103041</td>\n",
       "      <td>0.931068</td>\n",
       "      <td>9.659021e-04</td>\n",
       "      <td>0.031480</td>\n",
       "      <td>0.020229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>CYCS</td>\n",
       "      <td>-0.103156</td>\n",
       "      <td>0.930994</td>\n",
       "      <td>1.006196e-03</td>\n",
       "      <td>0.032253</td>\n",
       "      <td>0.020725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230</th>\n",
       "      <td>NRN1</td>\n",
       "      <td>-0.105549</td>\n",
       "      <td>0.929451</td>\n",
       "      <td>4.371254e-03</td>\n",
       "      <td>0.067109</td>\n",
       "      <td>0.043124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>UQCRC1</td>\n",
       "      <td>-0.105601</td>\n",
       "      <td>0.929417</td>\n",
       "      <td>2.038169e-03</td>\n",
       "      <td>0.046037</td>\n",
       "      <td>0.029583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>COX6C</td>\n",
       "      <td>-0.108584</td>\n",
       "      <td>0.927498</td>\n",
       "      <td>4.751065e-03</td>\n",
       "      <td>0.069525</td>\n",
       "      <td>0.044677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>ACOT13</td>\n",
       "      <td>-0.110542</td>\n",
       "      <td>0.926240</td>\n",
       "      <td>8.460000e-05</td>\n",
       "      <td>0.007718</td>\n",
       "      <td>0.004959</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236</th>\n",
       "      <td>UQCRC2</td>\n",
       "      <td>-0.111935</td>\n",
       "      <td>0.925346</td>\n",
       "      <td>4.686810e-03</td>\n",
       "      <td>0.069525</td>\n",
       "      <td>0.044677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>ATP5H</td>\n",
       "      <td>-0.112765</td>\n",
       "      <td>0.924814</td>\n",
       "      <td>3.951941e-03</td>\n",
       "      <td>0.063130</td>\n",
       "      <td>0.040567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>PLCB1</td>\n",
       "      <td>-0.114471</td>\n",
       "      <td>0.923721</td>\n",
       "      <td>2.119770e-04</td>\n",
       "      <td>0.012857</td>\n",
       "      <td>0.008262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>255</th>\n",
       "      <td>HNRNPC</td>\n",
       "      <td>-0.114789</td>\n",
       "      <td>0.923517</td>\n",
       "      <td>5.082905e-03</td>\n",
       "      <td>0.070252</td>\n",
       "      <td>0.045144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>NDUFA4</td>\n",
       "      <td>-0.119132</td>\n",
       "      <td>0.920742</td>\n",
       "      <td>2.353584e-04</td>\n",
       "      <td>0.013639</td>\n",
       "      <td>0.008765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>267</th>\n",
       "      <td>ATP1A2</td>\n",
       "      <td>-0.123689</td>\n",
       "      <td>0.917837</td>\n",
       "      <td>5.465083e-03</td>\n",
       "      <td>0.072555</td>\n",
       "      <td>0.046624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>NDUFB5</td>\n",
       "      <td>-0.126062</td>\n",
       "      <td>0.916329</td>\n",
       "      <td>8.015950e-04</td>\n",
       "      <td>0.029709</td>\n",
       "      <td>0.019091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>ISCU</td>\n",
       "      <td>-0.126723</td>\n",
       "      <td>0.915910</td>\n",
       "      <td>3.670000e-05</td>\n",
       "      <td>0.005180</td>\n",
       "      <td>0.003329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>MPP1</td>\n",
       "      <td>-0.127312</td>\n",
       "      <td>0.915536</td>\n",
       "      <td>2.423970e-04</td>\n",
       "      <td>0.013639</td>\n",
       "      <td>0.008765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>NDUFB3</td>\n",
       "      <td>-0.128332</td>\n",
       "      <td>0.914888</td>\n",
       "      <td>1.300194e-03</td>\n",
       "      <td>0.036199</td>\n",
       "      <td>0.023261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>SUCLA2</td>\n",
       "      <td>-0.136572</td>\n",
       "      <td>0.909678</td>\n",
       "      <td>6.084452e-04</td>\n",
       "      <td>0.025244</td>\n",
       "      <td>0.016222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>NDUFA8</td>\n",
       "      <td>-0.137068</td>\n",
       "      <td>0.909366</td>\n",
       "      <td>5.680000e-06</td>\n",
       "      <td>0.001263</td>\n",
       "      <td>0.000812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>PSPC1</td>\n",
       "      <td>-0.142115</td>\n",
       "      <td>0.906189</td>\n",
       "      <td>3.055999e-04</td>\n",
       "      <td>0.015990</td>\n",
       "      <td>0.010275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>OLFM1</td>\n",
       "      <td>-0.142890</td>\n",
       "      <td>0.905703</td>\n",
       "      <td>3.735119e-04</td>\n",
       "      <td>0.018458</td>\n",
       "      <td>0.011861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>NDUFA7</td>\n",
       "      <td>-0.143381</td>\n",
       "      <td>0.905395</td>\n",
       "      <td>4.392824e-04</td>\n",
       "      <td>0.021121</td>\n",
       "      <td>0.013572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>ATP2B2</td>\n",
       "      <td>-0.143609</td>\n",
       "      <td>0.905252</td>\n",
       "      <td>3.790000e-05</td>\n",
       "      <td>0.005180</td>\n",
       "      <td>0.003329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>NDUFB1</td>\n",
       "      <td>-0.144582</td>\n",
       "      <td>0.904641</td>\n",
       "      <td>1.403385e-03</td>\n",
       "      <td>0.036987</td>\n",
       "      <td>0.023768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>PEX19</td>\n",
       "      <td>-0.151263</td>\n",
       "      <td>0.900462</td>\n",
       "      <td>8.124779e-04</td>\n",
       "      <td>0.029802</td>\n",
       "      <td>0.019151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>SLC25A5</td>\n",
       "      <td>-0.163352</td>\n",
       "      <td>0.892948</td>\n",
       "      <td>1.120000e-06</td>\n",
       "      <td>0.000444</td>\n",
       "      <td>0.000285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>NDUFC2</td>\n",
       "      <td>-0.170667</td>\n",
       "      <td>0.888432</td>\n",
       "      <td>2.580000e-05</td>\n",
       "      <td>0.003989</td>\n",
       "      <td>0.002563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>GAD1</td>\n",
       "      <td>-0.179035</td>\n",
       "      <td>0.883294</td>\n",
       "      <td>2.440000e-05</td>\n",
       "      <td>0.003943</td>\n",
       "      <td>0.002534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215</th>\n",
       "      <td>SCN1A</td>\n",
       "      <td>-0.205877</td>\n",
       "      <td>0.867011</td>\n",
       "      <td>3.796930e-03</td>\n",
       "      <td>0.062363</td>\n",
       "      <td>0.040074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>VAMP1</td>\n",
       "      <td>-0.228358</td>\n",
       "      <td>0.853606</td>\n",
       "      <td>1.100294e-03</td>\n",
       "      <td>0.033505</td>\n",
       "      <td>0.021530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>NDUFAB1</td>\n",
       "      <td>-0.262984</td>\n",
       "      <td>0.833362</td>\n",
       "      <td>1.985181e-03</td>\n",
       "      <td>0.045570</td>\n",
       "      <td>0.029283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>SYT1</td>\n",
       "      <td>-0.324413</td>\n",
       "      <td>0.798623</td>\n",
       "      <td>2.690000e-07</td>\n",
       "      <td>0.000203</td>\n",
       "      <td>0.000131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>ATPIF1</td>\n",
       "      <td>-0.391989</td>\n",
       "      <td>0.762078</td>\n",
       "      <td>1.193190e-03</td>\n",
       "      <td>0.035086</td>\n",
       "      <td>0.022546</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Symbol  log2FoldChange  foldChange        pvalue      padj    qvalue\n",
       "225      DLD       -0.063471    0.956959  4.106793e-03  0.064655  0.041547\n",
       "257     OPA1       -0.068977    0.953314  5.109362e-03  0.070252  0.045144\n",
       "216       CS       -0.075342    0.949117  3.803462e-03  0.062363  0.040074\n",
       "54     VDAC1       -0.078594    0.946980  1.701323e-04  0.011006  0.007072\n",
       "269    MICU1       -0.079595    0.946323  5.594906e-03  0.073728  0.047377\n",
       "169      NNT       -0.082885    0.944167  2.412585e-03  0.049941  0.032092\n",
       "224  NDUFB11       -0.083626    0.943683  4.040400e-03  0.063892  0.041057\n",
       "59   CNTNAP2       -0.085431    0.942503  2.169302e-04  0.012864  0.008266\n",
       "186   NDUFV2       -0.086275    0.941951  2.907925e-03  0.054914  0.035288\n",
       "166  COX7A2L       -0.086373    0.941888  2.328876e-03  0.049495  0.031805\n",
       "48      DLAT       -0.089265    0.940002  1.556205e-04  0.011006  0.007072\n",
       "104     PDHX       -0.089637    0.939759  9.415332e-04  0.031480  0.020229\n",
       "76   STXBP5L       -0.089774    0.939670  5.127288e-04  0.023534  0.015123\n",
       "260    SUMO2       -0.092139    0.938131  5.237995e-03  0.070966  0.045602\n",
       "116     RGS7       -0.094444    0.936633  1.101768e-03  0.033505  0.021530\n",
       "213   ADAM23       -0.096330    0.935409  3.763254e-03  0.062363  0.040074\n",
       "130      AUH       -0.099059    0.933642  1.341490e-03  0.036199  0.023261\n",
       "128   COX4I1       -0.101120    0.932309  1.331807e-03  0.036199  0.023261\n",
       "108   NDUFS4       -0.103041    0.931068  9.659021e-04  0.031480  0.020229\n",
       "110     CYCS       -0.103156    0.930994  1.006196e-03  0.032253  0.020725\n",
       "230     NRN1       -0.105549    0.929451  4.371254e-03  0.067109  0.043124\n",
       "156   UQCRC1       -0.105601    0.929417  2.038169e-03  0.046037  0.029583\n",
       "241    COX6C       -0.108584    0.927498  4.751065e-03  0.069525  0.044677\n",
       "38    ACOT13       -0.110542    0.926240  8.460000e-05  0.007718  0.004959\n",
       "236   UQCRC2       -0.111935    0.925346  4.686810e-03  0.069525  0.044677\n",
       "221    ATP5H       -0.112765    0.924814  3.951941e-03  0.063130  0.040567\n",
       "56     PLCB1       -0.114471    0.923721  2.119770e-04  0.012857  0.008262\n",
       "255   HNRNPC       -0.114789    0.923517  5.082905e-03  0.070252  0.045144\n",
       "60    NDUFA4       -0.119132    0.920742  2.353584e-04  0.013639  0.008765\n",
       "267   ATP1A2       -0.123689    0.917837  5.465083e-03  0.072555  0.046624\n",
       "95    NDUFB5       -0.126062    0.916329  8.015950e-04  0.029709  0.019091\n",
       "23      ISCU       -0.126723    0.915910  3.670000e-05  0.005180  0.003329\n",
       "61      MPP1       -0.127312    0.915536  2.423970e-04  0.013639  0.008765\n",
       "126   NDUFB3       -0.128332    0.914888  1.300194e-03  0.036199  0.023261\n",
       "84    SUCLA2       -0.136572    0.909678  6.084452e-04  0.025244  0.016222\n",
       "15    NDUFA8       -0.137068    0.909366  5.680000e-06  0.001263  0.000812\n",
       "67     PSPC1       -0.142115    0.906189  3.055999e-04  0.015990  0.010275\n",
       "71     OLFM1       -0.142890    0.905703  3.735119e-04  0.018458  0.011861\n",
       "73    NDUFA7       -0.143381    0.905395  4.392824e-04  0.021121  0.013572\n",
       "25    ATP2B2       -0.143609    0.905252  3.790000e-05  0.005180  0.003329\n",
       "134   NDUFB1       -0.144582    0.904641  1.403385e-03  0.036987  0.023768\n",
       "96     PEX19       -0.151263    0.900462  8.124779e-04  0.029802  0.019151\n",
       "8    SLC25A5       -0.163352    0.892948  1.120000e-06  0.000444  0.000285\n",
       "22    NDUFC2       -0.170667    0.888432  2.580000e-05  0.003989  0.002563\n",
       "21      GAD1       -0.179035    0.883294  2.440000e-05  0.003943  0.002534\n",
       "215    SCN1A       -0.205877    0.867011  3.796930e-03  0.062363  0.040074\n",
       "115    VAMP1       -0.228358    0.853606  1.100294e-03  0.033505  0.021530\n",
       "154  NDUFAB1       -0.262984    0.833362  1.985181e-03  0.045570  0.029283\n",
       "3       SYT1       -0.324413    0.798623  2.690000e-07  0.000203  0.000131\n",
       "120   ATPIF1       -0.391989    0.762078  1.193190e-03  0.035086  0.022546"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find the intersection between the Proteomics proteins and the upregulated genes in the Alzheimer's disease\n",
    "intersectAlzDnProt = list(set(lowQVal['Symbol']).intersection(alzDnGenes))\n",
    "intersectTabDnProt = lowQVal[lowQVal['Symbol'].isin(intersectAlzDnProt)]\n",
    "intersectTabDnProt[intersectTabDnProt['log2FoldChange'] < 0].sort_values(by='log2FoldChange', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Symbol</th>\n",
       "      <th>log2FoldChange</th>\n",
       "      <th>foldChange</th>\n",
       "      <th>pvalue</th>\n",
       "      <th>padj</th>\n",
       "      <th>qvalue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>SCN3B</td>\n",
       "      <td>0.218901</td>\n",
       "      <td>1.163847</td>\n",
       "      <td>1.033580e-04</td>\n",
       "      <td>0.008358</td>\n",
       "      <td>0.005371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>MAPK1</td>\n",
       "      <td>0.185216</td>\n",
       "      <td>1.136987</td>\n",
       "      <td>6.180000e-07</td>\n",
       "      <td>0.000275</td>\n",
       "      <td>0.000177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>272</th>\n",
       "      <td>SYN1</td>\n",
       "      <td>0.149011</td>\n",
       "      <td>1.108809</td>\n",
       "      <td>5.729241e-03</td>\n",
       "      <td>0.074669</td>\n",
       "      <td>0.047982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>GRIA1</td>\n",
       "      <td>0.140143</td>\n",
       "      <td>1.102014</td>\n",
       "      <td>2.967760e-03</td>\n",
       "      <td>0.055060</td>\n",
       "      <td>0.035381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>KPNB1</td>\n",
       "      <td>0.115725</td>\n",
       "      <td>1.083519</td>\n",
       "      <td>2.044361e-03</td>\n",
       "      <td>0.046037</td>\n",
       "      <td>0.029583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>FHL1</td>\n",
       "      <td>0.112306</td>\n",
       "      <td>1.080955</td>\n",
       "      <td>4.825130e-03</td>\n",
       "      <td>0.069525</td>\n",
       "      <td>0.044677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>GLUD1</td>\n",
       "      <td>0.107536</td>\n",
       "      <td>1.077386</td>\n",
       "      <td>1.149074e-03</td>\n",
       "      <td>0.034070</td>\n",
       "      <td>0.021893</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>ACTR3</td>\n",
       "      <td>0.099772</td>\n",
       "      <td>1.071604</td>\n",
       "      <td>8.243150e-04</td>\n",
       "      <td>0.029928</td>\n",
       "      <td>0.019231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>YWHAZ</td>\n",
       "      <td>0.098871</td>\n",
       "      <td>1.070935</td>\n",
       "      <td>3.670000e-05</td>\n",
       "      <td>0.005180</td>\n",
       "      <td>0.003329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>ESD</td>\n",
       "      <td>0.093348</td>\n",
       "      <td>1.066843</td>\n",
       "      <td>4.570000e-05</td>\n",
       "      <td>0.005805</td>\n",
       "      <td>0.003730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>SNCA</td>\n",
       "      <td>0.090126</td>\n",
       "      <td>1.064463</td>\n",
       "      <td>4.846054e-03</td>\n",
       "      <td>0.069525</td>\n",
       "      <td>0.044677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>CUL2</td>\n",
       "      <td>0.088065</td>\n",
       "      <td>1.062944</td>\n",
       "      <td>2.943583e-04</td>\n",
       "      <td>0.015632</td>\n",
       "      <td>0.010045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>CNKSR2</td>\n",
       "      <td>0.087151</td>\n",
       "      <td>1.062271</td>\n",
       "      <td>2.414241e-03</td>\n",
       "      <td>0.049941</td>\n",
       "      <td>0.032092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>XPO7</td>\n",
       "      <td>0.080968</td>\n",
       "      <td>1.057728</td>\n",
       "      <td>2.959264e-03</td>\n",
       "      <td>0.055060</td>\n",
       "      <td>0.035381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>NPEPPS</td>\n",
       "      <td>0.073447</td>\n",
       "      <td>1.052228</td>\n",
       "      <td>3.121998e-03</td>\n",
       "      <td>0.057258</td>\n",
       "      <td>0.036794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>TUBB2A</td>\n",
       "      <td>0.071340</td>\n",
       "      <td>1.050692</td>\n",
       "      <td>7.896409e-04</td>\n",
       "      <td>0.029709</td>\n",
       "      <td>0.019091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>YWHAE</td>\n",
       "      <td>0.053855</td>\n",
       "      <td>1.038035</td>\n",
       "      <td>1.565269e-03</td>\n",
       "      <td>0.039780</td>\n",
       "      <td>0.025563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>238</th>\n",
       "      <td>VCP</td>\n",
       "      <td>0.045767</td>\n",
       "      <td>1.032232</td>\n",
       "      <td>4.698582e-03</td>\n",
       "      <td>0.069525</td>\n",
       "      <td>0.044677</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Symbol  log2FoldChange  foldChange        pvalue      padj    qvalue\n",
       "43    SCN3B        0.218901    1.163847  1.033580e-04  0.008358  0.005371\n",
       "7     MAPK1        0.185216    1.136987  6.180000e-07  0.000275  0.000177\n",
       "272    SYN1        0.149011    1.108809  5.729241e-03  0.074669  0.047982\n",
       "190   GRIA1        0.140143    1.102014  2.967760e-03  0.055060  0.035381\n",
       "157   KPNB1        0.115725    1.083519  2.044361e-03  0.046037  0.029583\n",
       "245    FHL1        0.112306    1.080955  4.825130e-03  0.069525  0.044677\n",
       "119   GLUD1        0.107536    1.077386  1.149074e-03  0.034070  0.021893\n",
       "97    ACTR3        0.099772    1.071604  8.243150e-04  0.029928  0.019231\n",
       "24    YWHAZ        0.098871    1.070935  3.670000e-05  0.005180  0.003329\n",
       "27      ESD        0.093348    1.066843  4.570000e-05  0.005805  0.003730\n",
       "247    SNCA        0.090126    1.064463  4.846054e-03  0.069525  0.044677\n",
       "66     CUL2        0.088065    1.062944  2.943583e-04  0.015632  0.010045\n",
       "171  CNKSR2        0.087151    1.062271  2.414241e-03  0.049941  0.032092\n",
       "189    XPO7        0.080968    1.057728  2.959264e-03  0.055060  0.035381\n",
       "193  NPEPPS        0.073447    1.052228  3.121998e-03  0.057258  0.036794\n",
       "93   TUBB2A        0.071340    1.050692  7.896409e-04  0.029709  0.019091\n",
       "139   YWHAE        0.053855    1.038035  1.565269e-03  0.039780  0.025563\n",
       "238     VCP        0.045767    1.032232  4.698582e-03  0.069525  0.044677"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# List the proteins that are upregulated instead of downregulated like they are in Alzheimer's Disease\n",
    "intersectTabDnProt[intersectTabDnProt['log2FoldChange'] > 0].sort_values(by='log2FoldChange', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "intAlzDnProtFalse = sum(intersectTabDnProt['log2FoldChange'] > 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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/j+S0DFxxwy1Iz8xGdn4Brr/tK1B8PlTt2Drs9n0+ZcTfY6JA4kgXMOyXmah0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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7feba95578d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Generate the venn diagram for the downregulated genes in Alz's disease and proteins in PD MS3P\n",
    "intAlzDnProt = [len(alzDnGenes)-len(intersectAlzDnProt), intAlzDnProtFalse,\n",
    "                len(intersectAlzDnProt)-intAlzDnProtFalse]\n",
    "intAlzDnProtPDVenn = venn2(intAlzDnProt, ['Down regulated Alz Genes',\n",
    "                                          'Proteins in PD MS3P'])\n",
    "\n",
    "intAlzDnProtPDVenn.get_patch_by_id('10').set_color('#2F4858')\n",
    "intAlzDnProtPDVenn.get_patch_by_id('01').set_color('#33658A')\n",
    "intAlzDnProtPDVenn.get_patch_by_id('11').set_color('#86BBD8')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.4.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}