HER2_ensemble_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "############################################################################\n",
    "# HER2 Overexpression,This is the analysis of the results of ensemble clustering       \n",
    "############################################################################\n",
    "%matplotlib inline \n",
    "import numpy as np \n",
    "import pandas as pd \n",
    "import matplotlib.pyplot as plt\n",
    "#from cooccurrence import coMat\n",
    "import openensembles as oe\n",
    "import finishing as finish\n",
    "\n",
    "import pickle\n",
    "pd.set_option(\"display.max_rows\",101)\n",
    "\n",
    "[dataObj_P, dataObj_24H, c_P, c_24H, c_link_P, c_link_24H, c_g_P, c_g_24H] = pickle.load( open( \"P_24H_ensembleClusterworkspace.p\", \"rb\" ))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "coMat_P = c_P.co_occurrence_matrix('parent')\n",
    "coMat_24H = c_24H.co_occurrence_matrix('parent')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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iX2hgM62f5OPaqj7X5yI0mzkmkGtbEWy3LBe/WRX5uZIX6eitIa25mMeQATrsknsWmwlV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lje8usZKuf8c5J3VtUdk1zW3Sd390u6+9wMQ22+O6vKY6+qsPP8JJclOTxDlZ0LuvtjSd6+0OXq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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1055186d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f_P = coMat_P.plot(distance_threshold=0.45)\n",
    "f_P.set_size_inches(8.5, 8.5, forward=True)\n",
    "f_P.savefig('P_coOccMatrix.svg', format='svg', bbox_inches='tight', dpi=1200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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d/sVI3RkFbAG8TIoIv5w0nOc9wFuAo7q/HZA0RNI5LEzdmQRsD4wA7gFuBE4n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\nN16vvLjxxvm+c8k6czLPbUXqzgjK3xCqvqYf3kRc1uvzy2tPTc60ezr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1jqRc1LaZmZmZ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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x105518630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f_24H = coMat_24H.plot(distance_threshold=0.45)\n",
    "f_24H.set_size_inches(8.5, 8.5, forward=True)\n",
    "f_24H.savefig('24H_coOccMatrix.svg', format='svg', bbox_inches='tight', dpi=1200)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compare top and bottom quartiles "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "coMat_pair_P = coMat_P.pairwise_list()\n",
    "coMat_pair_24H = coMat_24H.pairwise_list()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x12fa0c9e8>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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/XlN2tZv5eaNcKE52dpXCHcQ+E1ZUntfsCKnDh48ahdZdd91DajD2wIF7EtmD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\ngZiZWSFOIGZmVogTiJmZFeIEYmZmhfwPigRsKlrjkDwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12f930fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# What is the similarity between the two\n",
    "plt.scatter(coMat_pair_P['pairwise'], coMat_pair_24H['pairwise'])\n",
    "plt.xlabel('Parental Co-Occurrence')\n",
    "plt.ylabel('24H Co-Occurrence')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#compare the differences in clustering to that of the direct correlation\n",
    "#Calculate correlation of peptides between the datasets\n",
    "df1 = dataObj_P.df\n",
    "df2 = dataObj_24H.df\n",
    "df1.columns = [0, 5, 10, 30]\n",
    "df2.columns = df1.columns\n",
    "df_corr = df1.corrwith(df2, axis=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "gene_site\n",
       "ALB_Y164         -0.749120\n",
       "BCAR3_Y266        0.461549\n",
       "YES1_Y426        -0.479415\n",
       "SGK223_Y413      -0.243006\n",
       "ARHGAP35_Y1105    0.471324\n",
       "PRPF4B_Y849      -0.829022\n",
       "PTPN11_Y62        0.326561\n",
       "PTK2_Y576         0.319880\n",
       "dtype: float64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#List the correlations that are less than 0.5\n",
    "df_corr[df_corr<0.5]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>site_1</th>\n",
       "      <th>site_2</th>\n",
       "      <th>pairwise_P</th>\n",
       "      <th>pairwise_24H</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; SLC38A2_Y20</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>SLC38A2_Y20</td>\n",
       "      <td>0.190909</td>\n",
       "      <td>0.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; PTPRA_Y798</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>PTPRA_Y798</td>\n",
       "      <td>0.190909</td>\n",
       "      <td>0.190909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; LDLR_Y845</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>LDLR_Y845</td>\n",
       "      <td>0.450000</td>\n",
       "      <td>0.109091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; BCAR3_Y266</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>BCAR3_Y266</td>\n",
       "      <td>0.513636</td>\n",
       "      <td>0.409091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; AFAP1L2_Y413</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>AFAP1L2_Y413</td>\n",
       "      <td>0.190909</td>\n",
       "      <td>0.340909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; YES1_Y426</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>YES1_Y426</td>\n",
       "      <td>0.554545</td>\n",
       "      <td>0.672727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; EFNB2_Y304</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>EFNB2_Y304</td>\n",
       "      <td>0.304545</td>\n",
       "      <td>0.163636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; ANXA2_Y30</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>ANXA2_Y30</td>\n",
       "      <td>0.668182</td>\n",
       "      <td>0.136364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; ANXA2_Y238</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>ANXA2_Y238</td>\n",
       "      <td>0.190909</td>\n",
       "      <td>0.054545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; ANXA2_Y24</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>ANXA2_Y24</td>\n",
       "      <td>0.354545</td>\n",
       "      <td>0.254545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; KIAA1217_Y393</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>KIAA1217_Y393</td>\n",
       "      <td>0.554545</td>\n",
       "      <td>0.136364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; TNK2_Y859</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>TNK2_Y859</td>\n",
       "      <td>0.163636</td>\n",
       "      <td>0.190909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; EPHA2_Y588</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>EPHA2_Y588</td>\n",
       "      <td>0.354545</td>\n",
       "      <td>0.109091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; EPHA2_Y588_Y594</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>EPHA2_Y588_Y594</td>\n",
       "      <td>0.527273</td>\n",
       "      <td>0.054545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; EPHA2_Y575</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>EPHA2_Y575</td>\n",
       "      <td>0.395455</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; EPHA2_Y772</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>EPHA2_Y772</td>\n",
       "      <td>0.763636</td>\n",
       "      <td>0.163636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; EGFR_Y1092</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>EGFR_Y1092</td>\n",
       "      <td>0.136364</td>\n",
       "      <td>0.136364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; EGFR_Y1172</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>EGFR_Y1172</td>\n",
       "      <td>0.136364</td>\n",
       "      <td>0.163636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; EGFR_Y1197</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>EGFR_Y1197</td>\n",
       "      <td>0.163636</td>\n",
       "      <td>0.109091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; BCAR1_Y249</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>BCAR1_Y249</td>\n",
       "      <td>0.722727</td>\n",
       "      <td>0.163636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; BCAR1_Y234</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>BCAR1_Y234</td>\n",
       "      <td>0.536364</td>\n",
       "      <td>0.163636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; BCAR1_Y327</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>BCAR1_Y327</td>\n",
       "      <td>0.081818</td>\n",
       "      <td>0.327273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; BCAR1_Y387</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>BCAR1_Y387</td>\n",
       "      <td>0.163636</td>\n",
       "      <td>0.163636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; SHC1_Y427</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>SHC1_Y427</td>\n",
       "      <td>0.136364</td>\n",
       "      <td>0.254545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; SHC1_Y349</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>SHC1_Y349</td>\n",
       "      <td>0.136364</td>\n",
       "      <td>0.190909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; SHC1_Y349_Y350</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>SHC1_Y349_Y350</td>\n",
       "      <td>0.150000</td>\n",
       "      <td>0.254545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; CAV1_Y14</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>CAV1_Y14</td>\n",
       "      <td>0.190909</td>\n",
       "      <td>0.136364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; DYRK1A_Y321</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>DYRK1A_Y321</td>\n",
       "      <td>0.300000</td>\n",
       "      <td>0.654545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; PTRF_Y308</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>PTRF_Y308</td>\n",
       "      <td>0.345455</td>\n",
       "      <td>0.354545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; STAT3_Y704</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>STAT3_Y704</td>\n",
       "      <td>0.136364</td>\n",
       "      <td>0.136364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; STAT3_Y705</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>STAT3_Y705</td>\n",
       "      <td>0.218182</td>\n",
       "      <td>0.136364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; SGK223_Y413</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>SGK223_Y413</td>\n",
       "      <td>0.163636</td>\n",
       "      <td>0.359091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; INSR_Y1185</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>INSR_Y1185</td>\n",
       "      <td>0.218182</td>\n",
       "      <td>0.240909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; INSR_Y1189</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>INSR_Y1189</td>\n",
       "      <td>0.190909</td>\n",
       "      <td>0.240909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; CRKL_Y132</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>CRKL_Y132</td>\n",
       "      <td>0.209091</td>\n",
       "      <td>0.627273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; FAM59A_Y453</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>FAM59A_Y453</td>\n",
       "      <td>0.136364</td>\n",
       "      <td>0.281818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; INPPL1_Y986</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>INPPL1_Y986</td>\n",
       "      <td>0.136364</td>\n",
       "      <td>0.136364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; MAPK3_Y204</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>MAPK3_Y204</td>\n",
       "      <td>0.136364</td>\n",
       "      <td>0.190909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; MAPK1_Y187</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>MAPK1_Y187</td>\n",
       "      <td>0.136364</td>\n",
       "      <td>0.190909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; MAPK1_T185_Y187</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>MAPK1_T185_Y187</td>\n",
       "      <td>0.163636</td>\n",
       "      <td>0.281818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; CDK1_Y15</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>CDK1_Y15</td>\n",
       "      <td>0.345455</td>\n",
       "      <td>0.613636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; GIT1_Y545</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>GIT1_Y545</td>\n",
       "      <td>0.163636</td>\n",
       "      <td>0.645455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; TFRC_Y20</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>TFRC_Y20</td>\n",
       "      <td>0.445455</td>\n",
       "      <td>0.081818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; ITGB4_Y1207</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>ITGB4_Y1207</td>\n",
       "      <td>0.218182</td>\n",
       "      <td>0.654545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; ERBB2IP_Y1104</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>ERBB2IP_Y1104</td>\n",
       "      <td>0.540909</td>\n",
       "      <td>0.081818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; SH2D3A_S218_Y231</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>SH2D3A_S218_Y231</td>\n",
       "      <td>0.190909</td>\n",
       "      <td>0.254545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; ARHGAP35_Y1105</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>ARHGAP35_Y1105</td>\n",
       "      <td>0.218182</td>\n",
       "      <td>0.204545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; RIN1_Y36</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>RIN1_Y36</td>\n",
       "      <td>0.163636</td>\n",
       "      <td>0.136364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; PKP3_Y176</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>PKP3_Y176</td>\n",
       "      <td>0.218182</td>\n",
       "      <td>0.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; CTNND1_Y228</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>CTNND1_Y228</td>\n",
       "      <td>0.190909</td>\n",
       "      <td>0.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MAPK14_Y182; PTK2_Y576</th>\n",
       "      <td>MAPK14_Y182</td>\n",
       "      <td>PTK2_Y576</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.809091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MAPK14_Y182; GSK3A_Y279</th>\n",
       "      <td>MAPK14_Y182</td>\n",
       "      <td>GSK3A_Y279</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.168182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MAPK14_Y182; MPZL1_Y263</th>\n",
       "      <td>MAPK14_Y182</td>\n",
       "      <td>MPZL1_Y263</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.181818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MAPK14_Y182; ERBB2_Y1248</th>\n",
       "      <td>MAPK14_Y182</td>\n",
       "      <td>ERBB2_Y1248</td>\n",
       "      <td>0.213636</td>\n",
       "      <td>0.195455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MAPK14_Y182; EPHB2_Y602</th>\n",
       "      <td>MAPK14_Y182</td>\n",
       "      <td>EPHB2_Y602</td>\n",
       "      <td>0.081818</td>\n",
       "      <td>0.090909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PXN_Y118; PXN_S84_Y88</th>\n",
       "      <td>PXN_Y118</td>\n",
       "      <td>PXN_S84_Y88</td>\n",
       "      <td>0.163636</td>\n",
       "      <td>0.659091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PXN_Y118; PTPN11_Y62</th>\n",
       "      <td>PXN_Y118</td>\n",
       "      <td>PTPN11_Y62</td>\n",
       "      <td>0.277273</td>\n",
       "      <td>0.081818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PXN_Y118; ACP1_Y132</th>\n",
       "      <td>PXN_Y118</td>\n",
       "      <td>ACP1_Y132</td>\n",
       "      <td>0.245455</td>\n",
       "      <td>0.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PXN_Y118; PTK2_Y397</th>\n",
       "      <td>PXN_Y118</td>\n",
       "      <td>PTK2_Y397</td>\n",
       "      <td>0.472727</td>\n",
       "      <td>0.163636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PXN_Y118; PTK2_Y576</th>\n",
       "      <td>PXN_Y118</td>\n",
       "      <td>PTK2_Y576</td>\n",
       "      <td>0.281818</td>\n",
       "      <td>0.372727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PXN_Y118; GSK3A_Y279</th>\n",
       "      <td>PXN_Y118</td>\n",
       "      <td>GSK3A_Y279</td>\n",
       "      <td>0.318182</td>\n",
       "      <td>0.654545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PXN_Y118; MPZL1_Y263</th>\n",
       "      <td>PXN_Y118</td>\n",
       "      <td>MPZL1_Y263</td>\n",
       "      <td>0.277273</td>\n",
       "      <td>0.309091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PXN_Y118; ERBB2_Y1248</th>\n",
       "      <td>PXN_Y118</td>\n",
       "      <td>ERBB2_Y1248</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>0.136364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PXN_Y118; EPHB2_Y602</th>\n",
       "      <td>PXN_Y118</td>\n",
       "      <td>EPHB2_Y602</td>\n",
       "      <td>0.163636</td>\n",
       "      <td>0.136364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PXN_S84_Y88; PTPN11_Y62</th>\n",
       "      <td>PXN_S84_Y88</td>\n",
       "      <td>PTPN11_Y62</td>\n",
       "      <td>0.163636</td>\n",
       "      <td>0.359091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PXN_S84_Y88; ACP1_Y132</th>\n",
       "      <td>PXN_S84_Y88</td>\n",
       "      <td>ACP1_Y132</td>\n",
       "      <td>0.886364</td>\n",
       "      <td>0.604545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PXN_S84_Y88; PTK2_Y397</th>\n",
       "      <td>PXN_S84_Y88</td>\n",
       "      <td>PTK2_Y397</td>\n",
       "      <td>0.168182</td>\n",
       "      <td>0.440909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PXN_S84_Y88; PTK2_Y576</th>\n",
       "      <td>PXN_S84_Y88</td>\n",
       "      <td>PTK2_Y576</td>\n",
       "      <td>0.245455</td>\n",
       "      <td>0.359091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PXN_S84_Y88; GSK3A_Y279</th>\n",
       "      <td>PXN_S84_Y88</td>\n",
       "      <td>GSK3A_Y279</td>\n",
       "      <td>0.109091</td>\n",
       "      <td>0.595455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PXN_S84_Y88; MPZL1_Y263</th>\n",
       "      <td>PXN_S84_Y88</td>\n",
       "      <td>MPZL1_Y263</td>\n",
       "      <td>0.254545</td>\n",
       "      <td>0.281818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PXN_S84_Y88; ERBB2_Y1248</th>\n",
       "      <td>PXN_S84_Y88</td>\n",
       "      <td>ERBB2_Y1248</td>\n",
       "      <td>0.168182</td>\n",
       "      <td>0.109091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PXN_S84_Y88; EPHB2_Y602</th>\n",
       "      <td>PXN_S84_Y88</td>\n",
       "      <td>EPHB2_Y602</td>\n",
       "      <td>0.854545</td>\n",
       "      <td>0.422727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTPN11_Y62; ACP1_Y132</th>\n",
       "      <td>PTPN11_Y62</td>\n",
       "      <td>ACP1_Y132</td>\n",
       "      <td>0.245455</td>\n",
       "      <td>0.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTPN11_Y62; PTK2_Y397</th>\n",
       "      <td>PTPN11_Y62</td>\n",
       "      <td>PTK2_Y397</td>\n",
       "      <td>0.272727</td>\n",
       "      <td>0.490909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTPN11_Y62; PTK2_Y576</th>\n",
       "      <td>PTPN11_Y62</td>\n",
       "      <td>PTK2_Y576</td>\n",
       "      <td>0.272727</td>\n",
       "      <td>0.109091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTPN11_Y62; GSK3A_Y279</th>\n",
       "      <td>PTPN11_Y62</td>\n",
       "      <td>GSK3A_Y279</td>\n",
       "      <td>0.663636</td>\n",
       "      <td>0.081818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTPN11_Y62; MPZL1_Y263</th>\n",
       "      <td>PTPN11_Y62</td>\n",
       "      <td>MPZL1_Y263</td>\n",
       "      <td>0.277273</td>\n",
       "      <td>0.109091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTPN11_Y62; ERBB2_Y1248</th>\n",
       "      <td>PTPN11_Y62</td>\n",
       "      <td>ERBB2_Y1248</td>\n",
       "      <td>0.281818</td>\n",
       "      <td>0.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTPN11_Y62; EPHB2_Y602</th>\n",
       "      <td>PTPN11_Y62</td>\n",
       "      <td>EPHB2_Y602</td>\n",
       "      <td>0.163636</td>\n",
       "      <td>0.563636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ACP1_Y132; PTK2_Y397</th>\n",
       "      <td>ACP1_Y132</td>\n",
       "      <td>PTK2_Y397</td>\n",
       "      <td>0.272727</td>\n",
       "      <td>0.513636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ACP1_Y132; PTK2_Y576</th>\n",
       "      <td>ACP1_Y132</td>\n",
       "      <td>PTK2_Y576</td>\n",
       "      <td>0.350000</td>\n",
       "      <td>0.190909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ACP1_Y132; GSK3A_Y279</th>\n",
       "      <td>ACP1_Y132</td>\n",
       "      <td>GSK3A_Y279</td>\n",
       "      <td>0.190909</td>\n",
       "      <td>0.263636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ACP1_Y132; MPZL1_Y263</th>\n",
       "      <td>ACP1_Y132</td>\n",
       "      <td>MPZL1_Y263</td>\n",
       "      <td>0.354545</td>\n",
       "      <td>0.572727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ACP1_Y132; ERBB2_Y1248</th>\n",
       "      <td>ACP1_Y132</td>\n",
       "      <td>ERBB2_Y1248</td>\n",
       "      <td>0.254545</td>\n",
       "      <td>0.109091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ACP1_Y132; EPHB2_Y602</th>\n",
       "      <td>ACP1_Y132</td>\n",
       "      <td>EPHB2_Y602</td>\n",
       "      <td>0.740909</td>\n",
       "      <td>0.490909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTK2_Y397; PTK2_Y576</th>\n",
       "      <td>PTK2_Y397</td>\n",
       "      <td>PTK2_Y576</td>\n",
       "      <td>0.790909</td>\n",
       "      <td>0.163636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTK2_Y397; GSK3A_Y279</th>\n",
       "      <td>PTK2_Y397</td>\n",
       "      <td>GSK3A_Y279</td>\n",
       "      <td>0.218182</td>\n",
       "      <td>0.163636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTK2_Y397; MPZL1_Y263</th>\n",
       "      <td>PTK2_Y397</td>\n",
       "      <td>MPZL1_Y263</td>\n",
       "      <td>0.745455</td>\n",
       "      <td>0.163636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTK2_Y397; ERBB2_Y1248</th>\n",
       "      <td>PTK2_Y397</td>\n",
       "      <td>ERBB2_Y1248</td>\n",
       "      <td>0.459091</td>\n",
       "      <td>0.109091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTK2_Y397; EPHB2_Y602</th>\n",
       "      <td>PTK2_Y397</td>\n",
       "      <td>EPHB2_Y602</td>\n",
       "      <td>0.163636</td>\n",
       "      <td>0.895455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTK2_Y576; GSK3A_Y279</th>\n",
       "      <td>PTK2_Y576</td>\n",
       "      <td>GSK3A_Y279</td>\n",
       "      <td>0.218182</td>\n",
       "      <td>0.318182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTK2_Y576; MPZL1_Y263</th>\n",
       "      <td>PTK2_Y576</td>\n",
       "      <td>MPZL1_Y263</td>\n",
       "      <td>0.918182</td>\n",
       "      <td>0.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTK2_Y576; ERBB2_Y1248</th>\n",
       "      <td>PTK2_Y576</td>\n",
       "      <td>ERBB2_Y1248</td>\n",
       "      <td>0.281818</td>\n",
       "      <td>0.136364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTK2_Y576; EPHB2_Y602</th>\n",
       "      <td>PTK2_Y576</td>\n",
       "      <td>EPHB2_Y602</td>\n",
       "      <td>0.172727</td>\n",
       "      <td>0.163636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GSK3A_Y279; MPZL1_Y263</th>\n",
       "      <td>GSK3A_Y279</td>\n",
       "      <td>MPZL1_Y263</td>\n",
       "      <td>0.218182</td>\n",
       "      <td>0.368182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GSK3A_Y279; ERBB2_Y1248</th>\n",
       "      <td>GSK3A_Y279</td>\n",
       "      <td>ERBB2_Y1248</td>\n",
       "      <td>0.309091</td>\n",
       "      <td>0.304545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GSK3A_Y279; EPHB2_Y602</th>\n",
       "      <td>GSK3A_Y279</td>\n",
       "      <td>EPHB2_Y602</td>\n",
       "      <td>0.109091</td>\n",
       "      <td>0.136364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MPZL1_Y263; ERBB2_Y1248</th>\n",
       "      <td>MPZL1_Y263</td>\n",
       "      <td>ERBB2_Y1248</td>\n",
       "      <td>0.286364</td>\n",
       "      <td>0.413636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MPZL1_Y263; EPHB2_Y602</th>\n",
       "      <td>MPZL1_Y263</td>\n",
       "      <td>EPHB2_Y602</td>\n",
       "      <td>0.168182</td>\n",
       "      <td>0.163636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ERBB2_Y1248; EPHB2_Y602</th>\n",
       "      <td>ERBB2_Y1248</td>\n",
       "      <td>EPHB2_Y602</td>\n",
       "      <td>0.163636</td>\n",
       "      <td>0.127273</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2278 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 site_1            site_2  pairwise_P  \\\n",
       "ALB_Y164; SLC38A2_Y20          ALB_Y164       SLC38A2_Y20    0.190909   \n",
       "ALB_Y164; PTPRA_Y798           ALB_Y164        PTPRA_Y798    0.190909   \n",
       "ALB_Y164; LDLR_Y845            ALB_Y164         LDLR_Y845    0.450000   \n",
       "ALB_Y164; BCAR3_Y266           ALB_Y164        BCAR3_Y266    0.513636   \n",
       "ALB_Y164; AFAP1L2_Y413         ALB_Y164      AFAP1L2_Y413    0.190909   \n",
       "ALB_Y164; YES1_Y426            ALB_Y164         YES1_Y426    0.554545   \n",
       "ALB_Y164; EFNB2_Y304           ALB_Y164        EFNB2_Y304    0.304545   \n",
       "ALB_Y164; ANXA2_Y30            ALB_Y164         ANXA2_Y30    0.668182   \n",
       "ALB_Y164; ANXA2_Y238           ALB_Y164        ANXA2_Y238    0.190909   \n",
       "ALB_Y164; ANXA2_Y24            ALB_Y164         ANXA2_Y24    0.354545   \n",
       "ALB_Y164; KIAA1217_Y393        ALB_Y164     KIAA1217_Y393    0.554545   \n",
       "ALB_Y164; TNK2_Y859            ALB_Y164         TNK2_Y859    0.163636   \n",
       "ALB_Y164; EPHA2_Y588           ALB_Y164        EPHA2_Y588    0.354545   \n",
       "ALB_Y164; EPHA2_Y588_Y594      ALB_Y164   EPHA2_Y588_Y594    0.527273   \n",
       "ALB_Y164; EPHA2_Y575           ALB_Y164        EPHA2_Y575    0.395455   \n",
       "ALB_Y164; EPHA2_Y772           ALB_Y164        EPHA2_Y772    0.763636   \n",
       "ALB_Y164; EGFR_Y1092           ALB_Y164        EGFR_Y1092    0.136364   \n",
       "ALB_Y164; EGFR_Y1172           ALB_Y164        EGFR_Y1172    0.136364   \n",
       "ALB_Y164; EGFR_Y1197           ALB_Y164        EGFR_Y1197    0.163636   \n",
       "ALB_Y164; BCAR1_Y249           ALB_Y164        BCAR1_Y249    0.722727   \n",
       "ALB_Y164; BCAR1_Y234           ALB_Y164        BCAR1_Y234    0.536364   \n",
       "ALB_Y164; BCAR1_Y327           ALB_Y164        BCAR1_Y327    0.081818   \n",
       "ALB_Y164; BCAR1_Y387           ALB_Y164        BCAR1_Y387    0.163636   \n",
       "ALB_Y164; SHC1_Y427            ALB_Y164         SHC1_Y427    0.136364   \n",
       "ALB_Y164; SHC1_Y349            ALB_Y164         SHC1_Y349    0.136364   \n",
       "ALB_Y164; SHC1_Y349_Y350       ALB_Y164    SHC1_Y349_Y350    0.150000   \n",
       "ALB_Y164; CAV1_Y14             ALB_Y164          CAV1_Y14    0.190909   \n",
       "ALB_Y164; DYRK1A_Y321          ALB_Y164       DYRK1A_Y321    0.300000   \n",
       "ALB_Y164; PTRF_Y308            ALB_Y164         PTRF_Y308    0.345455   \n",
       "ALB_Y164; STAT3_Y704           ALB_Y164        STAT3_Y704    0.136364   \n",
       "ALB_Y164; STAT3_Y705           ALB_Y164        STAT3_Y705    0.218182   \n",
       "ALB_Y164; SGK223_Y413          ALB_Y164       SGK223_Y413    0.163636   \n",
       "ALB_Y164; INSR_Y1185           ALB_Y164        INSR_Y1185    0.218182   \n",
       "ALB_Y164; INSR_Y1189           ALB_Y164        INSR_Y1189    0.190909   \n",
       "ALB_Y164; CRKL_Y132            ALB_Y164         CRKL_Y132    0.209091   \n",
       "ALB_Y164; FAM59A_Y453          ALB_Y164       FAM59A_Y453    0.136364   \n",
       "ALB_Y164; INPPL1_Y986          ALB_Y164       INPPL1_Y986    0.136364   \n",
       "ALB_Y164; MAPK3_Y204           ALB_Y164        MAPK3_Y204    0.136364   \n",
       "ALB_Y164; MAPK1_Y187           ALB_Y164        MAPK1_Y187    0.136364   \n",
       "ALB_Y164; MAPK1_T185_Y187      ALB_Y164   MAPK1_T185_Y187    0.163636   \n",
       "ALB_Y164; CDK1_Y15             ALB_Y164          CDK1_Y15    0.345455   \n",
       "ALB_Y164; GIT1_Y545            ALB_Y164         GIT1_Y545    0.163636   \n",
       "ALB_Y164; TFRC_Y20             ALB_Y164          TFRC_Y20    0.445455   \n",
       "ALB_Y164; ITGB4_Y1207          ALB_Y164       ITGB4_Y1207    0.218182   \n",
       "ALB_Y164; ERBB2IP_Y1104        ALB_Y164     ERBB2IP_Y1104    0.540909   \n",
       "ALB_Y164; SH2D3A_S218_Y231     ALB_Y164  SH2D3A_S218_Y231    0.190909   \n",
       "ALB_Y164; ARHGAP35_Y1105       ALB_Y164    ARHGAP35_Y1105    0.218182   \n",
       "ALB_Y164; RIN1_Y36             ALB_Y164          RIN1_Y36    0.163636   \n",
       "ALB_Y164; PKP3_Y176            ALB_Y164         PKP3_Y176    0.218182   \n",
       "ALB_Y164; CTNND1_Y228          ALB_Y164       CTNND1_Y228    0.190909   \n",
       "...                                 ...               ...         ...   \n",
       "MAPK14_Y182; PTK2_Y576      MAPK14_Y182         PTK2_Y576    0.200000   \n",
       "MAPK14_Y182; GSK3A_Y279     MAPK14_Y182        GSK3A_Y279    0.200000   \n",
       "MAPK14_Y182; MPZL1_Y263     MAPK14_Y182        MPZL1_Y263    0.200000   \n",
       "MAPK14_Y182; ERBB2_Y1248    MAPK14_Y182       ERBB2_Y1248    0.213636   \n",
       "MAPK14_Y182; EPHB2_Y602     MAPK14_Y182        EPHB2_Y602    0.081818   \n",
       "PXN_Y118; PXN_S84_Y88          PXN_Y118       PXN_S84_Y88    0.163636   \n",
       "PXN_Y118; PTPN11_Y62           PXN_Y118        PTPN11_Y62    0.277273   \n",
       "PXN_Y118; ACP1_Y132            PXN_Y118         ACP1_Y132    0.245455   \n",
       "PXN_Y118; PTK2_Y397            PXN_Y118         PTK2_Y397    0.472727   \n",
       "PXN_Y118; PTK2_Y576            PXN_Y118         PTK2_Y576    0.281818   \n",
       "PXN_Y118; GSK3A_Y279           PXN_Y118        GSK3A_Y279    0.318182   \n",
       "PXN_Y118; MPZL1_Y263           PXN_Y118        MPZL1_Y263    0.277273   \n",
       "PXN_Y118; ERBB2_Y1248          PXN_Y118       ERBB2_Y1248    0.750000   \n",
       "PXN_Y118; EPHB2_Y602           PXN_Y118        EPHB2_Y602    0.163636   \n",
       "PXN_S84_Y88; PTPN11_Y62     PXN_S84_Y88        PTPN11_Y62    0.163636   \n",
       "PXN_S84_Y88; ACP1_Y132      PXN_S84_Y88         ACP1_Y132    0.886364   \n",
       "PXN_S84_Y88; PTK2_Y397      PXN_S84_Y88         PTK2_Y397    0.168182   \n",
       "PXN_S84_Y88; PTK2_Y576      PXN_S84_Y88         PTK2_Y576    0.245455   \n",
       "PXN_S84_Y88; GSK3A_Y279     PXN_S84_Y88        GSK3A_Y279    0.109091   \n",
       "PXN_S84_Y88; MPZL1_Y263     PXN_S84_Y88        MPZL1_Y263    0.254545   \n",
       "PXN_S84_Y88; ERBB2_Y1248    PXN_S84_Y88       ERBB2_Y1248    0.168182   \n",
       "PXN_S84_Y88; EPHB2_Y602     PXN_S84_Y88        EPHB2_Y602    0.854545   \n",
       "PTPN11_Y62; ACP1_Y132        PTPN11_Y62         ACP1_Y132    0.245455   \n",
       "PTPN11_Y62; PTK2_Y397        PTPN11_Y62         PTK2_Y397    0.272727   \n",
       "PTPN11_Y62; PTK2_Y576        PTPN11_Y62         PTK2_Y576    0.272727   \n",
       "PTPN11_Y62; GSK3A_Y279       PTPN11_Y62        GSK3A_Y279    0.663636   \n",
       "PTPN11_Y62; MPZL1_Y263       PTPN11_Y62        MPZL1_Y263    0.277273   \n",
       "PTPN11_Y62; ERBB2_Y1248      PTPN11_Y62       ERBB2_Y1248    0.281818   \n",
       "PTPN11_Y62; EPHB2_Y602       PTPN11_Y62        EPHB2_Y602    0.163636   \n",
       "ACP1_Y132; PTK2_Y397          ACP1_Y132         PTK2_Y397    0.272727   \n",
       "ACP1_Y132; PTK2_Y576          ACP1_Y132         PTK2_Y576    0.350000   \n",
       "ACP1_Y132; GSK3A_Y279         ACP1_Y132        GSK3A_Y279    0.190909   \n",
       "ACP1_Y132; MPZL1_Y263         ACP1_Y132        MPZL1_Y263    0.354545   \n",
       "ACP1_Y132; ERBB2_Y1248        ACP1_Y132       ERBB2_Y1248    0.254545   \n",
       "ACP1_Y132; EPHB2_Y602         ACP1_Y132        EPHB2_Y602    0.740909   \n",
       "PTK2_Y397; PTK2_Y576          PTK2_Y397         PTK2_Y576    0.790909   \n",
       "PTK2_Y397; GSK3A_Y279         PTK2_Y397        GSK3A_Y279    0.218182   \n",
       "PTK2_Y397; MPZL1_Y263         PTK2_Y397        MPZL1_Y263    0.745455   \n",
       "PTK2_Y397; ERBB2_Y1248        PTK2_Y397       ERBB2_Y1248    0.459091   \n",
       "PTK2_Y397; EPHB2_Y602         PTK2_Y397        EPHB2_Y602    0.163636   \n",
       "PTK2_Y576; GSK3A_Y279         PTK2_Y576        GSK3A_Y279    0.218182   \n",
       "PTK2_Y576; MPZL1_Y263         PTK2_Y576        MPZL1_Y263    0.918182   \n",
       "PTK2_Y576; ERBB2_Y1248        PTK2_Y576       ERBB2_Y1248    0.281818   \n",
       "PTK2_Y576; EPHB2_Y602         PTK2_Y576        EPHB2_Y602    0.172727   \n",
       "GSK3A_Y279; MPZL1_Y263       GSK3A_Y279        MPZL1_Y263    0.218182   \n",
       "GSK3A_Y279; ERBB2_Y1248      GSK3A_Y279       ERBB2_Y1248    0.309091   \n",
       "GSK3A_Y279; EPHB2_Y602       GSK3A_Y279        EPHB2_Y602    0.109091   \n",
       "MPZL1_Y263; ERBB2_Y1248      MPZL1_Y263       ERBB2_Y1248    0.286364   \n",
       "MPZL1_Y263; EPHB2_Y602       MPZL1_Y263        EPHB2_Y602    0.168182   \n",
       "ERBB2_Y1248; EPHB2_Y602     ERBB2_Y1248        EPHB2_Y602    0.163636   \n",
       "\n",
       "                            pairwise_24H  \n",
       "ALB_Y164; SLC38A2_Y20           0.200000  \n",
       "ALB_Y164; PTPRA_Y798            0.190909  \n",
       "ALB_Y164; LDLR_Y845             0.109091  \n",
       "ALB_Y164; BCAR3_Y266            0.409091  \n",
       "ALB_Y164; AFAP1L2_Y413          0.340909  \n",
       "ALB_Y164; YES1_Y426             0.672727  \n",
       "ALB_Y164; EFNB2_Y304            0.163636  \n",
       "ALB_Y164; ANXA2_Y30             0.136364  \n",
       "ALB_Y164; ANXA2_Y238            0.054545  \n",
       "ALB_Y164; ANXA2_Y24             0.254545  \n",
       "ALB_Y164; KIAA1217_Y393         0.136364  \n",
       "ALB_Y164; TNK2_Y859             0.190909  \n",
       "ALB_Y164; EPHA2_Y588            0.109091  \n",
       "ALB_Y164; EPHA2_Y588_Y594       0.054545  \n",
       "ALB_Y164; EPHA2_Y575            0.100000  \n",
       "ALB_Y164; EPHA2_Y772            0.163636  \n",
       "ALB_Y164; EGFR_Y1092            0.136364  \n",
       "ALB_Y164; EGFR_Y1172            0.163636  \n",
       "ALB_Y164; EGFR_Y1197            0.109091  \n",
       "ALB_Y164; BCAR1_Y249            0.163636  \n",
       "ALB_Y164; BCAR1_Y234            0.163636  \n",
       "ALB_Y164; BCAR1_Y327            0.327273  \n",
       "ALB_Y164; BCAR1_Y387            0.163636  \n",
       "ALB_Y164; SHC1_Y427             0.254545  \n",
       "ALB_Y164; SHC1_Y349             0.190909  \n",
       "ALB_Y164; SHC1_Y349_Y350        0.254545  \n",
       "ALB_Y164; CAV1_Y14              0.136364  \n",
       "ALB_Y164; DYRK1A_Y321           0.654545  \n",
       "ALB_Y164; PTRF_Y308             0.354545  \n",
       "ALB_Y164; STAT3_Y704            0.136364  \n",
       "ALB_Y164; STAT3_Y705            0.136364  \n",
       "ALB_Y164; SGK223_Y413           0.359091  \n",
       "ALB_Y164; INSR_Y1185            0.240909  \n",
       "ALB_Y164; INSR_Y1189            0.240909  \n",
       "ALB_Y164; CRKL_Y132             0.627273  \n",
       "ALB_Y164; FAM59A_Y453           0.281818  \n",
       "ALB_Y164; INPPL1_Y986           0.136364  \n",
       "ALB_Y164; MAPK3_Y204            0.190909  \n",
       "ALB_Y164; MAPK1_Y187            0.190909  \n",
       "ALB_Y164; MAPK1_T185_Y187       0.281818  \n",
       "ALB_Y164; CDK1_Y15              0.613636  \n",
       "ALB_Y164; GIT1_Y545             0.645455  \n",
       "ALB_Y164; TFRC_Y20              0.081818  \n",
       "ALB_Y164; ITGB4_Y1207           0.654545  \n",
       "ALB_Y164; ERBB2IP_Y1104         0.081818  \n",
       "ALB_Y164; SH2D3A_S218_Y231      0.254545  \n",
       "ALB_Y164; ARHGAP35_Y1105        0.204545  \n",
       "ALB_Y164; RIN1_Y36              0.136364  \n",
       "ALB_Y164; PKP3_Y176             0.200000  \n",
       "ALB_Y164; CTNND1_Y228           0.200000  \n",
       "...                                  ...  \n",
       "MAPK14_Y182; PTK2_Y576          0.809091  \n",
       "MAPK14_Y182; GSK3A_Y279         0.168182  \n",
       "MAPK14_Y182; MPZL1_Y263         0.181818  \n",
       "MAPK14_Y182; ERBB2_Y1248        0.195455  \n",
       "MAPK14_Y182; EPHB2_Y602         0.090909  \n",
       "PXN_Y118; PXN_S84_Y88           0.659091  \n",
       "PXN_Y118; PTPN11_Y62            0.081818  \n",
       "PXN_Y118; ACP1_Y132             0.300000  \n",
       "PXN_Y118; PTK2_Y397             0.163636  \n",
       "PXN_Y118; PTK2_Y576             0.372727  \n",
       "PXN_Y118; GSK3A_Y279            0.654545  \n",
       "PXN_Y118; MPZL1_Y263            0.309091  \n",
       "PXN_Y118; ERBB2_Y1248           0.136364  \n",
       "PXN_Y118; EPHB2_Y602            0.136364  \n",
       "PXN_S84_Y88; PTPN11_Y62         0.359091  \n",
       "PXN_S84_Y88; ACP1_Y132          0.604545  \n",
       "PXN_S84_Y88; PTK2_Y397          0.440909  \n",
       "PXN_S84_Y88; PTK2_Y576          0.359091  \n",
       "PXN_S84_Y88; GSK3A_Y279         0.595455  \n",
       "PXN_S84_Y88; MPZL1_Y263         0.281818  \n",
       "PXN_S84_Y88; ERBB2_Y1248        0.109091  \n",
       "PXN_S84_Y88; EPHB2_Y602         0.422727  \n",
       "PTPN11_Y62; ACP1_Y132           0.400000  \n",
       "PTPN11_Y62; PTK2_Y397           0.490909  \n",
       "PTPN11_Y62; PTK2_Y576           0.109091  \n",
       "PTPN11_Y62; GSK3A_Y279          0.081818  \n",
       "PTPN11_Y62; MPZL1_Y263          0.109091  \n",
       "PTPN11_Y62; ERBB2_Y1248         0.200000  \n",
       "PTPN11_Y62; EPHB2_Y602          0.563636  \n",
       "ACP1_Y132; PTK2_Y397            0.513636  \n",
       "ACP1_Y132; PTK2_Y576            0.190909  \n",
       "ACP1_Y132; GSK3A_Y279           0.263636  \n",
       "ACP1_Y132; MPZL1_Y263           0.572727  \n",
       "ACP1_Y132; ERBB2_Y1248          0.109091  \n",
       "ACP1_Y132; EPHB2_Y602           0.490909  \n",
       "PTK2_Y397; PTK2_Y576            0.163636  \n",
       "PTK2_Y397; GSK3A_Y279           0.163636  \n",
       "PTK2_Y397; MPZL1_Y263           0.163636  \n",
       "PTK2_Y397; ERBB2_Y1248          0.109091  \n",
       "PTK2_Y397; EPHB2_Y602           0.895455  \n",
       "PTK2_Y576; GSK3A_Y279           0.318182  \n",
       "PTK2_Y576; MPZL1_Y263           0.250000  \n",
       "PTK2_Y576; ERBB2_Y1248          0.136364  \n",
       "PTK2_Y576; EPHB2_Y602           0.163636  \n",
       "GSK3A_Y279; MPZL1_Y263          0.368182  \n",
       "GSK3A_Y279; ERBB2_Y1248         0.304545  \n",
       "GSK3A_Y279; EPHB2_Y602          0.136364  \n",
       "MPZL1_Y263; ERBB2_Y1248         0.413636  \n",
       "MPZL1_Y263; EPHB2_Y602          0.163636  \n",
       "ERBB2_Y1248; EPHB2_Y602         0.127273  \n",
       "\n",
       "[2278 rows x 4 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Merge the coMatrixes of parental and 24H into a single coMat_pairings\n",
    "df_temp = coMat_pair_24H['pairwise']\n",
    "df_temp.columns = ['pairwise_24H']\n",
    "coMat_pairings = pd.concat([coMat_pair_P, df_temp], axis=1, join='inner')\n",
    "coMat_pairings.columns = ['site_1', 'site_2', 'pairwise_P', 'pairwise_24H']\n",
    "coMat_pairings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Return the top in the Parental that are bottom in 24H\n",
    "threshold = 0.75\n",
    "df_topP_bott24H = coMat_pairings[(coMat_pairings.pairwise_P >= threshold) & (coMat_pairings.pairwise_24H <= (1-threshold))]\n",
    "df_top24H_bottP = coMat_pairings[(coMat_pairings.pairwise_24H >= threshold) & (coMat_pairings.pairwise_P <= (1-threshold))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false,
    "scrolled": 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>site_1</th>\n",
       "      <th>site_2</th>\n",
       "      <th>pairwise_P</th>\n",
       "      <th>pairwise_24H</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>PIK3R2_Y464; DSC3_Y818</th>\n",
       "      <td>PIK3R2_Y464</td>\n",
       "      <td>DSC3_Y818</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.218182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YES1_Y426; EPHB2_Y602</th>\n",
       "      <td>YES1_Y426</td>\n",
       "      <td>EPHB2_Y602</td>\n",
       "      <td>0.995455</td>\n",
       "      <td>0.227273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YES1_Y426; KIAA1217_Y393</th>\n",
       "      <td>YES1_Y426</td>\n",
       "      <td>KIAA1217_Y393</td>\n",
       "      <td>0.995455</td>\n",
       "      <td>0.236364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CDK1_Y15; PTPN11_Y62</th>\n",
       "      <td>CDK1_Y15</td>\n",
       "      <td>PTPN11_Y62</td>\n",
       "      <td>0.990909</td>\n",
       "      <td>0.172727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AFAP1L2_Y413; PIK3R2_Y464</th>\n",
       "      <td>AFAP1L2_Y413</td>\n",
       "      <td>PIK3R2_Y464</td>\n",
       "      <td>0.990909</td>\n",
       "      <td>0.222727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INSR_Y1189; PTK2_Y576</th>\n",
       "      <td>INSR_Y1189</td>\n",
       "      <td>PTK2_Y576</td>\n",
       "      <td>0.977273</td>\n",
       "      <td>0.172727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ANXA2_Y238; ENO1_Y44</th>\n",
       "      <td>ANXA2_Y238</td>\n",
       "      <td>ENO1_Y44</td>\n",
       "      <td>0.977273</td>\n",
       "      <td>0.081818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KIAA1217_Y393; ERBB2IP_Y1104</th>\n",
       "      <td>KIAA1217_Y393</td>\n",
       "      <td>ERBB2IP_Y1104</td>\n",
       "      <td>0.977273</td>\n",
       "      <td>0.136364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ERBB2IP_Y1104; EPHB2_Y602</th>\n",
       "      <td>ERBB2IP_Y1104</td>\n",
       "      <td>EPHB2_Y602</td>\n",
       "      <td>0.977273</td>\n",
       "      <td>0.218182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YES1_Y426; ERBB2IP_Y1104</th>\n",
       "      <td>YES1_Y426</td>\n",
       "      <td>ERBB2IP_Y1104</td>\n",
       "      <td>0.972727</td>\n",
       "      <td>0.190909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SLC38A2_Y20; PTK2_Y576</th>\n",
       "      <td>SLC38A2_Y20</td>\n",
       "      <td>PTK2_Y576</td>\n",
       "      <td>0.954545</td>\n",
       "      <td>0.190909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DYRK1A_Y321; SHB_Y268</th>\n",
       "      <td>DYRK1A_Y321</td>\n",
       "      <td>SHB_Y268</td>\n",
       "      <td>0.950000</td>\n",
       "      <td>0.195455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BCAR1_Y234; ERBB2IP_Y1104</th>\n",
       "      <td>BCAR1_Y234</td>\n",
       "      <td>ERBB2IP_Y1104</td>\n",
       "      <td>0.950000</td>\n",
       "      <td>0.118182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EGFR_Y1197; SHC1_Y427</th>\n",
       "      <td>EGFR_Y1197</td>\n",
       "      <td>SHC1_Y427</td>\n",
       "      <td>0.950000</td>\n",
       "      <td>0.231818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ANXA2_Y238; PIK3R2_Y464</th>\n",
       "      <td>ANXA2_Y238</td>\n",
       "      <td>PIK3R2_Y464</td>\n",
       "      <td>0.945455</td>\n",
       "      <td>0.081818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ANXA2_Y238; DSC3_Y818</th>\n",
       "      <td>ANXA2_Y238</td>\n",
       "      <td>DSC3_Y818</td>\n",
       "      <td>0.945455</td>\n",
       "      <td>0.109091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AFAP1L2_Y413; ANXA2_Y238</th>\n",
       "      <td>AFAP1L2_Y413</td>\n",
       "      <td>ANXA2_Y238</td>\n",
       "      <td>0.945455</td>\n",
       "      <td>0.109091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PKP3_Y176; PTK2_Y397</th>\n",
       "      <td>PKP3_Y176</td>\n",
       "      <td>PTK2_Y397</td>\n",
       "      <td>0.931818</td>\n",
       "      <td>0.163636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BCAR3_Y266; ERBB2IP_Y1104</th>\n",
       "      <td>BCAR3_Y266</td>\n",
       "      <td>ERBB2IP_Y1104</td>\n",
       "      <td>0.927273</td>\n",
       "      <td>0.095455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INSR_Y1189; CTNND1_Y228</th>\n",
       "      <td>INSR_Y1189</td>\n",
       "      <td>CTNND1_Y228</td>\n",
       "      <td>0.918182</td>\n",
       "      <td>0.204545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTK2_Y576; MPZL1_Y263</th>\n",
       "      <td>PTK2_Y576</td>\n",
       "      <td>MPZL1_Y263</td>\n",
       "      <td>0.918182</td>\n",
       "      <td>0.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EPHA2_Y588; DYRK1A_Y321</th>\n",
       "      <td>EPHA2_Y588</td>\n",
       "      <td>DYRK1A_Y321</td>\n",
       "      <td>0.909091</td>\n",
       "      <td>0.163636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SLC38A2_Y20; CTNND1_Y228</th>\n",
       "      <td>SLC38A2_Y20</td>\n",
       "      <td>CTNND1_Y228</td>\n",
       "      <td>0.895455</td>\n",
       "      <td>0.231818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DSC3_Y818; PXN_Y118</th>\n",
       "      <td>DSC3_Y818</td>\n",
       "      <td>PXN_Y118</td>\n",
       "      <td>0.881818</td>\n",
       "      <td>0.190909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAV1_Y14; CRKL_Y132</th>\n",
       "      <td>CAV1_Y14</td>\n",
       "      <td>CRKL_Y132</td>\n",
       "      <td>0.877273</td>\n",
       "      <td>0.240909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAV1_Y14; GPRC5A_Y347</th>\n",
       "      <td>CAV1_Y14</td>\n",
       "      <td>GPRC5A_Y347</td>\n",
       "      <td>0.877273</td>\n",
       "      <td>0.190909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YES1_Y426; TFRC_Y20</th>\n",
       "      <td>YES1_Y426</td>\n",
       "      <td>TFRC_Y20</td>\n",
       "      <td>0.863636</td>\n",
       "      <td>0.245455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ANXA2_Y238; PXN_Y118</th>\n",
       "      <td>ANXA2_Y238</td>\n",
       "      <td>PXN_Y118</td>\n",
       "      <td>0.863636</td>\n",
       "      <td>0.081818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FAM59A_Y453; PTK2_Y576</th>\n",
       "      <td>FAM59A_Y453</td>\n",
       "      <td>PTK2_Y576</td>\n",
       "      <td>0.859091</td>\n",
       "      <td>0.218182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PIK3R2_Y464; ERBB2_Y1248</th>\n",
       "      <td>PIK3R2_Y464</td>\n",
       "      <td>ERBB2_Y1248</td>\n",
       "      <td>0.859091</td>\n",
       "      <td>0.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTPRA_Y798; ERBB2_Y1248</th>\n",
       "      <td>PTPRA_Y798</td>\n",
       "      <td>ERBB2_Y1248</td>\n",
       "      <td>0.840909</td>\n",
       "      <td>0.136364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ERBB2IP_Y1104; PXN_S84_Y88</th>\n",
       "      <td>ERBB2IP_Y1104</td>\n",
       "      <td>PXN_S84_Y88</td>\n",
       "      <td>0.831818</td>\n",
       "      <td>0.122727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ANXA2_Y238; ERBB2_Y1248</th>\n",
       "      <td>ANXA2_Y238</td>\n",
       "      <td>ERBB2_Y1248</td>\n",
       "      <td>0.804545</td>\n",
       "      <td>0.190909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INSR_Y1189; PTK2_Y397</th>\n",
       "      <td>INSR_Y1189</td>\n",
       "      <td>PTK2_Y397</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>0.163636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SLC38A2_Y20; PTK2_Y397</th>\n",
       "      <td>SLC38A2_Y20</td>\n",
       "      <td>PTK2_Y397</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>0.163636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EPHA2_Y588; INSR_Y1185</th>\n",
       "      <td>EPHA2_Y588</td>\n",
       "      <td>INSR_Y1185</td>\n",
       "      <td>0.795455</td>\n",
       "      <td>0.136364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTPRA_Y798; ENO1_Y44</th>\n",
       "      <td>PTPRA_Y798</td>\n",
       "      <td>ENO1_Y44</td>\n",
       "      <td>0.790909</td>\n",
       "      <td>0.190909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTK2_Y397; PTK2_Y576</th>\n",
       "      <td>PTK2_Y397</td>\n",
       "      <td>PTK2_Y576</td>\n",
       "      <td>0.790909</td>\n",
       "      <td>0.163636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MAPK1_T185_Y187; PTK2_Y576</th>\n",
       "      <td>MAPK1_T185_Y187</td>\n",
       "      <td>PTK2_Y576</td>\n",
       "      <td>0.786364</td>\n",
       "      <td>0.218182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EPHA2_Y588; GPRC5A_Y347</th>\n",
       "      <td>EPHA2_Y588</td>\n",
       "      <td>GPRC5A_Y347</td>\n",
       "      <td>0.786364</td>\n",
       "      <td>0.136364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BCAR1_Y234; PXN_S84_Y88</th>\n",
       "      <td>BCAR1_Y234</td>\n",
       "      <td>PXN_S84_Y88</td>\n",
       "      <td>0.786364</td>\n",
       "      <td>0.213636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BCAR3_Y266; TFRC_Y20</th>\n",
       "      <td>BCAR3_Y266</td>\n",
       "      <td>TFRC_Y20</td>\n",
       "      <td>0.786364</td>\n",
       "      <td>0.213636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INSR_Y1185; SHB_Y268</th>\n",
       "      <td>INSR_Y1185</td>\n",
       "      <td>SHB_Y268</td>\n",
       "      <td>0.781818</td>\n",
       "      <td>0.218182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BCAR3_Y266; PXN_S84_Y88</th>\n",
       "      <td>BCAR3_Y266</td>\n",
       "      <td>PXN_S84_Y88</td>\n",
       "      <td>0.781818</td>\n",
       "      <td>0.136364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EPHA2_Y588; CRKL_Y132</th>\n",
       "      <td>EPHA2_Y588</td>\n",
       "      <td>CRKL_Y132</td>\n",
       "      <td>0.777273</td>\n",
       "      <td>0.140909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTPRA_Y798; ANXA2_Y238</th>\n",
       "      <td>PTPRA_Y798</td>\n",
       "      <td>ANXA2_Y238</td>\n",
       "      <td>0.777273</td>\n",
       "      <td>0.204545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PKP3_Y176; PTK2_Y576</th>\n",
       "      <td>PKP3_Y176</td>\n",
       "      <td>PTK2_Y576</td>\n",
       "      <td>0.768182</td>\n",
       "      <td>0.190909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTPRA_Y798; DSC3_Y818</th>\n",
       "      <td>PTPRA_Y798</td>\n",
       "      <td>DSC3_Y818</td>\n",
       "      <td>0.768182</td>\n",
       "      <td>0.190909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SH2D3A_S218_Y231; PTK2_Y397</th>\n",
       "      <td>SH2D3A_S218_Y231</td>\n",
       "      <td>PTK2_Y397</td>\n",
       "      <td>0.763636</td>\n",
       "      <td>0.163636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB_Y164; EPHA2_Y772</th>\n",
       "      <td>ALB_Y164</td>\n",
       "      <td>EPHA2_Y772</td>\n",
       "      <td>0.763636</td>\n",
       "      <td>0.163636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EPHA2_Y772; ERBB2IP_Y1104</th>\n",
       "      <td>EPHA2_Y772</td>\n",
       "      <td>ERBB2IP_Y1104</td>\n",
       "      <td>0.754545</td>\n",
       "      <td>0.118182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PXN_Y118; ERBB2_Y1248</th>\n",
       "      <td>PXN_Y118</td>\n",
       "      <td>ERBB2_Y1248</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>0.136364</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        site_1         site_2  pairwise_P  \\\n",
       "PIK3R2_Y464; DSC3_Y818             PIK3R2_Y464      DSC3_Y818    1.000000   \n",
       "YES1_Y426; EPHB2_Y602                YES1_Y426     EPHB2_Y602    0.995455   \n",
       "YES1_Y426; KIAA1217_Y393             YES1_Y426  KIAA1217_Y393    0.995455   \n",
       "CDK1_Y15; PTPN11_Y62                  CDK1_Y15     PTPN11_Y62    0.990909   \n",
       "AFAP1L2_Y413; PIK3R2_Y464         AFAP1L2_Y413    PIK3R2_Y464    0.990909   \n",
       "INSR_Y1189; PTK2_Y576               INSR_Y1189      PTK2_Y576    0.977273   \n",
       "ANXA2_Y238; ENO1_Y44                ANXA2_Y238       ENO1_Y44    0.977273   \n",
       "KIAA1217_Y393; ERBB2IP_Y1104     KIAA1217_Y393  ERBB2IP_Y1104    0.977273   \n",
       "ERBB2IP_Y1104; EPHB2_Y602        ERBB2IP_Y1104     EPHB2_Y602    0.977273   \n",
       "YES1_Y426; ERBB2IP_Y1104             YES1_Y426  ERBB2IP_Y1104    0.972727   \n",
       "SLC38A2_Y20; PTK2_Y576             SLC38A2_Y20      PTK2_Y576    0.954545   \n",
       "DYRK1A_Y321; SHB_Y268              DYRK1A_Y321       SHB_Y268    0.950000   \n",
       "BCAR1_Y234; ERBB2IP_Y1104           BCAR1_Y234  ERBB2IP_Y1104    0.950000   \n",
       "EGFR_Y1197; SHC1_Y427               EGFR_Y1197      SHC1_Y427    0.950000   \n",
       "ANXA2_Y238; PIK3R2_Y464             ANXA2_Y238    PIK3R2_Y464    0.945455   \n",
       "ANXA2_Y238; DSC3_Y818               ANXA2_Y238      DSC3_Y818    0.945455   \n",
       "AFAP1L2_Y413; ANXA2_Y238          AFAP1L2_Y413     ANXA2_Y238    0.945455   \n",
       "PKP3_Y176; PTK2_Y397                 PKP3_Y176      PTK2_Y397    0.931818   \n",
       "BCAR3_Y266; ERBB2IP_Y1104           BCAR3_Y266  ERBB2IP_Y1104    0.927273   \n",
       "INSR_Y1189; CTNND1_Y228             INSR_Y1189    CTNND1_Y228    0.918182   \n",
       "PTK2_Y576; MPZL1_Y263                PTK2_Y576     MPZL1_Y263    0.918182   \n",
       "EPHA2_Y588; DYRK1A_Y321             EPHA2_Y588    DYRK1A_Y321    0.909091   \n",
       "SLC38A2_Y20; CTNND1_Y228           SLC38A2_Y20    CTNND1_Y228    0.895455   \n",
       "DSC3_Y818; PXN_Y118                  DSC3_Y818       PXN_Y118    0.881818   \n",
       "CAV1_Y14; CRKL_Y132                   CAV1_Y14      CRKL_Y132    0.877273   \n",
       "CAV1_Y14; GPRC5A_Y347                 CAV1_Y14    GPRC5A_Y347    0.877273   \n",
       "YES1_Y426; TFRC_Y20                  YES1_Y426       TFRC_Y20    0.863636   \n",
       "ANXA2_Y238; PXN_Y118                ANXA2_Y238       PXN_Y118    0.863636   \n",
       "FAM59A_Y453; PTK2_Y576             FAM59A_Y453      PTK2_Y576    0.859091   \n",
       "PIK3R2_Y464; ERBB2_Y1248           PIK3R2_Y464    ERBB2_Y1248    0.859091   \n",
       "PTPRA_Y798; ERBB2_Y1248             PTPRA_Y798    ERBB2_Y1248    0.840909   \n",
       "ERBB2IP_Y1104; PXN_S84_Y88       ERBB2IP_Y1104    PXN_S84_Y88    0.831818   \n",
       "ANXA2_Y238; ERBB2_Y1248             ANXA2_Y238    ERBB2_Y1248    0.804545   \n",
       "INSR_Y1189; PTK2_Y397               INSR_Y1189      PTK2_Y397    0.800000   \n",
       "SLC38A2_Y20; PTK2_Y397             SLC38A2_Y20      PTK2_Y397    0.800000   \n",
       "EPHA2_Y588; INSR_Y1185              EPHA2_Y588     INSR_Y1185    0.795455   \n",
       "PTPRA_Y798; ENO1_Y44                PTPRA_Y798       ENO1_Y44    0.790909   \n",
       "PTK2_Y397; PTK2_Y576                 PTK2_Y397      PTK2_Y576    0.790909   \n",
       "MAPK1_T185_Y187; PTK2_Y576     MAPK1_T185_Y187      PTK2_Y576    0.786364   \n",
       "EPHA2_Y588; GPRC5A_Y347             EPHA2_Y588    GPRC5A_Y347    0.786364   \n",
       "BCAR1_Y234; PXN_S84_Y88             BCAR1_Y234    PXN_S84_Y88    0.786364   \n",
       "BCAR3_Y266; TFRC_Y20                BCAR3_Y266       TFRC_Y20    0.786364   \n",
       "INSR_Y1185; SHB_Y268                INSR_Y1185       SHB_Y268    0.781818   \n",
       "BCAR3_Y266; PXN_S84_Y88             BCAR3_Y266    PXN_S84_Y88    0.781818   \n",
       "EPHA2_Y588; CRKL_Y132               EPHA2_Y588      CRKL_Y132    0.777273   \n",
       "PTPRA_Y798; ANXA2_Y238              PTPRA_Y798     ANXA2_Y238    0.777273   \n",
       "PKP3_Y176; PTK2_Y576                 PKP3_Y176      PTK2_Y576    0.768182   \n",
       "PTPRA_Y798; DSC3_Y818               PTPRA_Y798      DSC3_Y818    0.768182   \n",
       "SH2D3A_S218_Y231; PTK2_Y397   SH2D3A_S218_Y231      PTK2_Y397    0.763636   \n",
       "ALB_Y164; EPHA2_Y772                  ALB_Y164     EPHA2_Y772    0.763636   \n",
       "EPHA2_Y772; ERBB2IP_Y1104           EPHA2_Y772  ERBB2IP_Y1104    0.754545   \n",
       "PXN_Y118; ERBB2_Y1248                 PXN_Y118    ERBB2_Y1248    0.750000   \n",
       "\n",
       "                              pairwise_24H  \n",
       "PIK3R2_Y464; DSC3_Y818            0.218182  \n",
       "YES1_Y426; EPHB2_Y602             0.227273  \n",
       "YES1_Y426; KIAA1217_Y393          0.236364  \n",
       "CDK1_Y15; PTPN11_Y62              0.172727  \n",
       "AFAP1L2_Y413; PIK3R2_Y464         0.222727  \n",
       "INSR_Y1189; PTK2_Y576             0.172727  \n",
       "ANXA2_Y238; ENO1_Y44              0.081818  \n",
       "KIAA1217_Y393; ERBB2IP_Y1104      0.136364  \n",
       "ERBB2IP_Y1104; EPHB2_Y602         0.218182  \n",
       "YES1_Y426; ERBB2IP_Y1104          0.190909  \n",
       "SLC38A2_Y20; PTK2_Y576            0.190909  \n",
       "DYRK1A_Y321; SHB_Y268             0.195455  \n",
       "BCAR1_Y234; ERBB2IP_Y1104         0.118182  \n",
       "EGFR_Y1197; SHC1_Y427             0.231818  \n",
       "ANXA2_Y238; PIK3R2_Y464           0.081818  \n",
       "ANXA2_Y238; DSC3_Y818             0.109091  \n",
       "AFAP1L2_Y413; ANXA2_Y238          0.109091  \n",
       "PKP3_Y176; PTK2_Y397              0.163636  \n",
       "BCAR3_Y266; ERBB2IP_Y1104         0.095455  \n",
       "INSR_Y1189; CTNND1_Y228           0.204545  \n",
       "PTK2_Y576; MPZL1_Y263             0.250000  \n",
       "EPHA2_Y588; DYRK1A_Y321           0.163636  \n",
       "SLC38A2_Y20; CTNND1_Y228          0.231818  \n",
       "DSC3_Y818; PXN_Y118               0.190909  \n",
       "CAV1_Y14; CRKL_Y132               0.240909  \n",
       "CAV1_Y14; GPRC5A_Y347             0.190909  \n",
       "YES1_Y426; TFRC_Y20               0.245455  \n",
       "ANXA2_Y238; PXN_Y118              0.081818  \n",
       "FAM59A_Y453; PTK2_Y576            0.218182  \n",
       "PIK3R2_Y464; ERBB2_Y1248          0.200000  \n",
       "PTPRA_Y798; ERBB2_Y1248           0.136364  \n",
       "ERBB2IP_Y1104; PXN_S84_Y88        0.122727  \n",
       "ANXA2_Y238; ERBB2_Y1248           0.190909  \n",
       "INSR_Y1189; PTK2_Y397             0.163636  \n",
       "SLC38A2_Y20; PTK2_Y397            0.163636  \n",
       "EPHA2_Y588; INSR_Y1185            0.136364  \n",
       "PTPRA_Y798; ENO1_Y44              0.190909  \n",
       "PTK2_Y397; PTK2_Y576              0.163636  \n",
       "MAPK1_T185_Y187; PTK2_Y576        0.218182  \n",
       "EPHA2_Y588; GPRC5A_Y347           0.136364  \n",
       "BCAR1_Y234; PXN_S84_Y88           0.213636  \n",
       "BCAR3_Y266; TFRC_Y20              0.213636  \n",
       "INSR_Y1185; SHB_Y268              0.218182  \n",
       "BCAR3_Y266; PXN_S84_Y88           0.136364  \n",
       "EPHA2_Y588; CRKL_Y132             0.140909  \n",
       "PTPRA_Y798; ANXA2_Y238            0.204545  \n",
       "PKP3_Y176; PTK2_Y576              0.190909  \n",
       "PTPRA_Y798; DSC3_Y818             0.190909  \n",
       "SH2D3A_S218_Y231; PTK2_Y397       0.163636  \n",
       "ALB_Y164; EPHA2_Y772              0.163636  \n",
       "EPHA2_Y772; ERBB2IP_Y1104         0.118182  \n",
       "PXN_Y118; ERBB2_Y1248             0.136364  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_topP_bott24H.sort_values(by='pairwise_P', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/knaegle/anaconda/envs/py35/lib/python3.5/site-packages/ipykernel/__main__.py:1: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n",
      "  if __name__ == '__main__':\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>site_1</th>\n",
       "      <th>site_2</th>\n",
       "      <th>pairwise_P</th>\n",
       "      <th>pairwise_24H</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ITGB4_Y1207; PXN_Y118</th>\n",
       "      <td>ITGB4_Y1207</td>\n",
       "      <td>PXN_Y118</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KIAA1217_Y393; PTK2_Y397</th>\n",
       "      <td>KIAA1217_Y393</td>\n",
       "      <td>PTK2_Y397</td>\n",
       "      <td>0.163636</td>\n",
       "      <td>0.972727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SHC1_Y349; CTNND1_Y228</th>\n",
       "      <td>SHC1_Y349</td>\n",
       "      <td>CTNND1_Y228</td>\n",
       "      <td>0.218182</td>\n",
       "      <td>0.972727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MAPK3_Y204; CTNND1_Y228</th>\n",
       "      <td>MAPK3_Y204</td>\n",
       "      <td>CTNND1_Y228</td>\n",
       "      <td>0.236364</td>\n",
       "      <td>0.950000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CRKL_Y132; PRPF4B_Y849</th>\n",
       "      <td>CRKL_Y132</td>\n",
       "      <td>PRPF4B_Y849</td>\n",
       "      <td>0.177273</td>\n",
       "      <td>0.931818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ANXA2_Y238; TFRC_Y20</th>\n",
       "      <td>ANXA2_Y238</td>\n",
       "      <td>TFRC_Y20</td>\n",
       "      <td>0.163636</td>\n",
       "      <td>0.918182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MAPK1_Y187; CTNND1_Y228</th>\n",
       "      <td>MAPK1_Y187</td>\n",
       "      <td>CTNND1_Y228</td>\n",
       "      <td>0.227273</td>\n",
       "      <td>0.913636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTK2_Y397; EPHB2_Y602</th>\n",
       "      <td>PTK2_Y397</td>\n",
       "      <td>EPHB2_Y602</td>\n",
       "      <td>0.163636</td>\n",
       "      <td>0.895455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EFNB2_Y304; PTK2_Y397</th>\n",
       "      <td>EFNB2_Y304</td>\n",
       "      <td>PTK2_Y397</td>\n",
       "      <td>0.218182</td>\n",
       "      <td>0.881818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TNK2_Y859; CAV1_Y14</th>\n",
       "      <td>TNK2_Y859</td>\n",
       "      <td>CAV1_Y14</td>\n",
       "      <td>0.245455</td>\n",
       "      <td>0.881818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EPHA2_Y588_Y594; PTPN11_Y62</th>\n",
       "      <td>EPHA2_Y588_Y594</td>\n",
       "      <td>PTPN11_Y62</td>\n",
       "      <td>0.163636</td>\n",
       "      <td>0.872727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EFNB2_Y304; EPHA2_Y588</th>\n",
       "      <td>EFNB2_Y304</td>\n",
       "      <td>EPHA2_Y588</td>\n",
       "      <td>0.218182</td>\n",
       "      <td>0.859091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BCAR3_Y266; BCAR1_Y327</th>\n",
       "      <td>BCAR3_Y266</td>\n",
       "      <td>BCAR1_Y327</td>\n",
       "      <td>0.090909</td>\n",
       "      <td>0.859091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GIT1_Y545; PXN_S84_Y88</th>\n",
       "      <td>GIT1_Y545</td>\n",
       "      <td>PXN_S84_Y88</td>\n",
       "      <td>0.190909</td>\n",
       "      <td>0.831818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TFRC_Y20; PTPN11_Y62</th>\n",
       "      <td>TFRC_Y20</td>\n",
       "      <td>PTPN11_Y62</td>\n",
       "      <td>0.163636</td>\n",
       "      <td>0.813636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MAPK14_Y182; PTK2_Y576</th>\n",
       "      <td>MAPK14_Y182</td>\n",
       "      <td>PTK2_Y576</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.809091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EGFR_Y1092; CAV1_Y14</th>\n",
       "      <td>EGFR_Y1092</td>\n",
       "      <td>CAV1_Y14</td>\n",
       "      <td>0.227273</td>\n",
       "      <td>0.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MAPK1_T185_Y187; PIK3R2_Y464</th>\n",
       "      <td>MAPK1_T185_Y187</td>\n",
       "      <td>PIK3R2_Y464</td>\n",
       "      <td>0.204545</td>\n",
       "      <td>0.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAV1_Y14; INPPL1_Y986</th>\n",
       "      <td>CAV1_Y14</td>\n",
       "      <td>INPPL1_Y986</td>\n",
       "      <td>0.227273</td>\n",
       "      <td>0.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FAM59A_Y453; PIK3R2_Y464</th>\n",
       "      <td>FAM59A_Y453</td>\n",
       "      <td>PIK3R2_Y464</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.795455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SHC1_Y427; GPRC5A_Y347</th>\n",
       "      <td>SHC1_Y427</td>\n",
       "      <td>GPRC5A_Y347</td>\n",
       "      <td>0.236364</td>\n",
       "      <td>0.795455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ANXA2_Y238; EPHA2_Y588_Y594</th>\n",
       "      <td>ANXA2_Y238</td>\n",
       "      <td>EPHA2_Y588_Y594</td>\n",
       "      <td>0.163636</td>\n",
       "      <td>0.768182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PRPF4B_Y849; PXN_Y118</th>\n",
       "      <td>PRPF4B_Y849</td>\n",
       "      <td>PXN_Y118</td>\n",
       "      <td>0.168182</td>\n",
       "      <td>0.768182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SHC1_Y349_Y350; PIK3R2_Y464</th>\n",
       "      <td>SHC1_Y349_Y350</td>\n",
       "      <td>PIK3R2_Y464</td>\n",
       "      <td>0.227273</td>\n",
       "      <td>0.750000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                       site_1           site_2  pairwise_P  \\\n",
       "ITGB4_Y1207; PXN_Y118             ITGB4_Y1207         PXN_Y118    0.250000   \n",
       "KIAA1217_Y393; PTK2_Y397        KIAA1217_Y393        PTK2_Y397    0.163636   \n",
       "SHC1_Y349; CTNND1_Y228              SHC1_Y349      CTNND1_Y228    0.218182   \n",
       "MAPK3_Y204; CTNND1_Y228            MAPK3_Y204      CTNND1_Y228    0.236364   \n",
       "CRKL_Y132; PRPF4B_Y849              CRKL_Y132      PRPF4B_Y849    0.177273   \n",
       "ANXA2_Y238; TFRC_Y20               ANXA2_Y238         TFRC_Y20    0.163636   \n",
       "MAPK1_Y187; CTNND1_Y228            MAPK1_Y187      CTNND1_Y228    0.227273   \n",
       "PTK2_Y397; EPHB2_Y602               PTK2_Y397       EPHB2_Y602    0.163636   \n",
       "EFNB2_Y304; PTK2_Y397              EFNB2_Y304        PTK2_Y397    0.218182   \n",
       "TNK2_Y859; CAV1_Y14                 TNK2_Y859         CAV1_Y14    0.245455   \n",
       "EPHA2_Y588_Y594; PTPN11_Y62   EPHA2_Y588_Y594       PTPN11_Y62    0.163636   \n",
       "EFNB2_Y304; EPHA2_Y588             EFNB2_Y304       EPHA2_Y588    0.218182   \n",
       "BCAR3_Y266; BCAR1_Y327             BCAR3_Y266       BCAR1_Y327    0.090909   \n",
       "GIT1_Y545; PXN_S84_Y88              GIT1_Y545      PXN_S84_Y88    0.190909   \n",
       "TFRC_Y20; PTPN11_Y62                 TFRC_Y20       PTPN11_Y62    0.163636   \n",
       "MAPK14_Y182; PTK2_Y576            MAPK14_Y182        PTK2_Y576    0.200000   \n",
       "EGFR_Y1092; CAV1_Y14               EGFR_Y1092         CAV1_Y14    0.227273   \n",
       "MAPK1_T185_Y187; PIK3R2_Y464  MAPK1_T185_Y187      PIK3R2_Y464    0.204545   \n",
       "CAV1_Y14; INPPL1_Y986                CAV1_Y14      INPPL1_Y986    0.227273   \n",
       "FAM59A_Y453; PIK3R2_Y464          FAM59A_Y453      PIK3R2_Y464    0.250000   \n",
       "SHC1_Y427; GPRC5A_Y347              SHC1_Y427      GPRC5A_Y347    0.236364   \n",
       "ANXA2_Y238; EPHA2_Y588_Y594        ANXA2_Y238  EPHA2_Y588_Y594    0.163636   \n",
       "PRPF4B_Y849; PXN_Y118             PRPF4B_Y849         PXN_Y118    0.168182   \n",
       "SHC1_Y349_Y350; PIK3R2_Y464    SHC1_Y349_Y350      PIK3R2_Y464    0.227273   \n",
       "\n",
       "                              pairwise_24H  \n",
       "ITGB4_Y1207; PXN_Y118             1.000000  \n",
       "KIAA1217_Y393; PTK2_Y397          0.972727  \n",
       "SHC1_Y349; CTNND1_Y228            0.972727  \n",
       "MAPK3_Y204; CTNND1_Y228           0.950000  \n",
       "CRKL_Y132; PRPF4B_Y849            0.931818  \n",
       "ANXA2_Y238; TFRC_Y20              0.918182  \n",
       "MAPK1_Y187; CTNND1_Y228           0.913636  \n",
       "PTK2_Y397; EPHB2_Y602             0.895455  \n",
       "EFNB2_Y304; PTK2_Y397             0.881818  \n",
       "TNK2_Y859; CAV1_Y14               0.881818  \n",
       "EPHA2_Y588_Y594; PTPN11_Y62       0.872727  \n",
       "EFNB2_Y304; EPHA2_Y588            0.859091  \n",
       "BCAR3_Y266; BCAR1_Y327            0.859091  \n",
       "GIT1_Y545; PXN_S84_Y88            0.831818  \n",
       "TFRC_Y20; PTPN11_Y62              0.813636  \n",
       "MAPK14_Y182; PTK2_Y576            0.809091  \n",
       "EGFR_Y1092; CAV1_Y14              0.800000  \n",
       "MAPK1_T185_Y187; PIK3R2_Y464      0.800000  \n",
       "CAV1_Y14; INPPL1_Y986             0.800000  \n",
       "FAM59A_Y453; PIK3R2_Y464          0.795455  \n",
       "SHC1_Y427; GPRC5A_Y347            0.795455  \n",
       "ANXA2_Y238; EPHA2_Y588_Y594       0.768182  \n",
       "PRPF4B_Y849; PXN_Y118             0.768182  \n",
       "SHC1_Y349_Y350; PIK3R2_Y464       0.750000  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_top24H_bottP.sort('pairwise_24H', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AFAP1L2_Y413:2\n",
      "ALB_Y164:1\n",
      "ANXA2_Y238:7\n",
      "BCAR1_Y234:2\n",
      "BCAR3_Y266:3\n",
      "CAV1_Y14:2\n",
      "CDK1_Y15:1\n",
      "CRKL_Y132:2\n",
      "CTNND1_Y228:2\n",
      "DSC3_Y818:4\n",
      "DYRK1A_Y321:2\n",
      "EGFR_Y1197:1\n",
      "ENO1_Y44:2\n",
      "EPHA2_Y588:4\n",
      "EPHA2_Y772:2\n",
      "EPHB2_Y602:2\n",
      "ERBB2IP_Y1104:7\n",
      "ERBB2_Y1248:4\n",
      "FAM59A_Y453:1\n",
      "GPRC5A_Y347:2\n",
      "INSR_Y1185:2\n",
      "INSR_Y1189:3\n",
      "KIAA1217_Y393:2\n",
      "MAPK1_T185_Y187:1\n",
      "MPZL1_Y263:1\n",
      "PIK3R2_Y464:4\n",
      "PKP3_Y176:2\n",
      "PTK2_Y397:5\n",
      "PTK2_Y576:7\n",
      "PTPN11_Y62:1\n",
      "PTPRA_Y798:4\n",
      "PXN_S84_Y88:3\n",
      "PXN_Y118:3\n",
      "SH2D3A_S218_Y231:1\n",
      "SHB_Y268:2\n",
      "SHC1_Y427:1\n",
      "SLC38A2_Y20:3\n",
      "TFRC_Y20:2\n",
      "YES1_Y426:4\n"
     ]
    }
   ],
   "source": [
    "## COUNT the number of times an object has made a major shift with a partner \n",
    "#use site_1 or site_2 to get a list of unique things, then count the number of times\n",
    "dfX = df_topP_bott24H\n",
    "movedTogether = []\n",
    "movedTogether.extend(dfX['site_1'].values.tolist())\n",
    "movedTogether.extend(dfX['site_2'].values.tolist())\n",
    "\n",
    "uniqueList = np.unique(movedTogether)\n",
    "for item in uniqueList:\n",
    "    print(\"%s:%d\"%(item, movedTogether.count(item)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting Finished Solutions in 3D space"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "dataObj = oe.data(dataObj_P.df, dataObj_P.x['parent'])\n",
    "dataObj.transform('parent', 'PCA', 'pca', n_components=3)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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JMUVXA0r63hoB6V1KURQ8Hk9W+NJMgc4siXyqiUSYlCvzPN9qwnI2iadSpKJvZi+0Q9rK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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12f9919e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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iw00HmXAnpAJZH/ED5nIAxkA+QhGmaRoOh4P3Cac7R1jKp5zt16AhugLi5d4qCRao7XVA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      "text/plain": [
       "<matplotlib.figure.Figure at 0x12f9919b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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iw00HmXAnpAJZH/ED5nIAxkA+QhGmaRoOh4P3Cac7R1jKp5zt16AhugLi5d4qCRao7XVA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\nRkZGRP4fvHJ8agIsciYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12f9919b0>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "labels = c_link_P.labels['co_occ_linkage']\n",
    "dataObj.plot_data('pca', title='pca linkage', class_labels=labels)\n",
    "\n",
    "\n",
    "labels = c_g_P.labels['graph_closure']\n",
    "dataObj.plot_data('pca', fignum=1, title='pca graph', class_labels=labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The number of clusters in parental graph closure: 5\n",
      "The number of clusters in 24H graph closure: 7\n",
      "The number of clusters in parental Ward Linkage: 9\n",
      "The number of clusters in 24H Ward Linkage: 12\n"
     ]
    }
   ],
   "source": [
    "print(\"The number of clusters in parental graph closure: %d\"%(len(c_g_P.clusterNumbers['graph_closure'])))\n",
    "print(\"The number of clusters in 24H graph closure: %d\"%(len(c_g_24H.clusterNumbers['graph_closure'])))\n",
    "\n",
    "print(\"The number of clusters in parental Ward Linkage: %d\"%(len(c_link_P.clusterNumbers['co_occ_linkage'])))\n",
    "print(\"The number of clusters in 24H Ward Linkage: %d\"%(len(c_link_24H.clusterNumbers['co_occ_linkage'])))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## What networks are most changed?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Calculate a difference comatrix\n",
    "coMat_diff = coMat_P.co_matrix-coMat_24H.co_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/knaegle/anaconda/envs/py35/lib/python3.5/site-packages/ipykernel/__main__.py:2: FutureWarning: sort is deprecated, use sort_values(inplace=True) for INPLACE sorting\n",
      "  from ipykernel import kernelapp as app\n"
     ]
    }
   ],
   "source": [
    "diff = coMat_diff.abs().sum()/len(coMat_diff)\n",
    "diffSort = diff.sort(inplace=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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FEMz5ZIxblo0LzVxmyFAPjKlrxlB9/0Wa0VTjl8lymdmzp6odAsWYXuSupbr2h0Qi4Wsq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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12f89a748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# how doess the self-correlation between P and 24H compare to average difference?\n",
    "coDiff_threshold = 0.21\n",
    "\n",
    "fig = plt.figure()\n",
    "fig.patch.set_alpha(0.5)\n",
    "ax = fig.add_subplot(111)\n",
    "ax.patch.set_alpha(0.5)\n",
    "ax.scatter(diff, df_corr)\n",
    "plt.axhline(0.5, color='r')\n",
    "#plt.axhline(0.8, color='b')\n",
    "plt.axvline(coDiff_threshold, color='g')\n",
    "plt.xlabel('Average Co-Occurrence Difference')\n",
    "plt.ylabel('Pearson Correlation')\n",
    "#f.set_size_inches(4, 4, forward=True)\n",
    "fig.savefig('Correlations.svg', format='svg', bbox_inches='tight', dpi=1200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x12fede3c8>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x12f991160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "b = np.arange(0, 0.35, 0.01)\n",
    "n, bins, patches = plt.hist(diff, bins = b)\n",
    "plt.axvline(coDiff_threshold, color='g')\n",
    "plt.xlabel('Average Co-Occurrence Difference')\n",
    "plt.title('Histogram')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Percent above threshold=0.21 is 16.2%\n"
     ]
    }
   ],
   "source": [
    "l = np.cumsum(n)\n",
    "nBig = n*(bins[1:]>coDiff_threshold)\n",
    "x = np.cumsum(nBig)\n",
    "percExplained = x[-1]/l[-1]\n",
    "print(\"Percent above threshold=%0.2f is %2.1f%%\"%(coDiff_threshold, percExplained*100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "EPHA2_Y575          0.104211\n",
       "TNK2_Y859           0.109091\n",
       "RIN1_Y36            0.114439\n",
       "MAPK1_Y187          0.120521\n",
       "STAT3_Y705          0.121591\n",
       "MAPK14_Y182         0.122861\n",
       "EGFR_Y1197          0.125602\n",
       "EGFR_Y1172          0.125735\n",
       "BCAR1_Y249          0.126270\n",
       "MAPK3_Y204          0.126738\n",
       "STAT3_Y704          0.127072\n",
       "EPHA2_Y588_Y594     0.131618\n",
       "INPPL1_Y986         0.131952\n",
       "EGFR_Y1092          0.131952\n",
       "BCAR3_Y266          0.133890\n",
       "EPHA2_Y772          0.135361\n",
       "EFNB2_Y304          0.137032\n",
       "SHC1_Y349           0.140374\n",
       "PKP3_Y176           0.140508\n",
       "GIT1_Y545           0.143316\n",
       "KIAA1217_Y393       0.146123\n",
       "EPHB2_Y602          0.146123\n",
       "CDK1_Y15            0.146992\n",
       "BCAR1_Y234          0.148930\n",
       "SHC1_Y349_Y350      0.148930\n",
       "ANXA2_Y30           0.149666\n",
       "GSK3A_Y279          0.151872\n",
       "MAPK1_T185_Y187     0.152139\n",
       "BCAR1_Y387          0.153008\n",
       "MPZL1_Y263          0.153342\n",
       "TFRC_Y20            0.157019\n",
       "SLC38A2_Y20         0.158690\n",
       "BCAR1_Y327          0.159225\n",
       "INSR_Y1189          0.161765\n",
       "YES1_Y426           0.162433\n",
       "SH2D3A_S218_Y231    0.163904\n",
       "FAM59A_Y453         0.165842\n",
       "SGK223_Y413         0.168583\n",
       "ACP1_Y132           0.175267\n",
       "ITGB4_Y1207         0.181952\n",
       "ERBB2_Y1248         0.182019\n",
       "LDLR_Y845           0.182553\n",
       "ALB_Y164            0.184291\n",
       "PTRF_Y308           0.185495\n",
       "AFAP1L2_Y413        0.186297\n",
       "INSR_Y1185          0.187032\n",
       "ENO1_Y44            0.192447\n",
       "ANXA2_Y24           0.196190\n",
       "CRKL_Y132           0.198329\n",
       "PRPF4B_Y849         0.198730\n",
       "GPRC5A_Y347         0.201203\n",
       "SHB_Y268            0.201404\n",
       "ARHGAP35_Y1105      0.201738\n",
       "DYRK1A_Y321         0.203476\n",
       "PTK2_Y576           0.207821\n",
       "ERBB2IP_Y1104       0.208489\n",
       "DSC3_Y818           0.209826\n",
       "CTNND1_Y228         0.210027\n",
       "PXN_S84_Y88         0.210428\n",
       "SHC1_Y427           0.213302\n",
       "PIK3R2_Y464         0.213904\n",
       "PXN_Y118            0.218316\n",
       "PTPN11_Y62          0.221257\n",
       "CAV1_Y14            0.239238\n",
       "PTPRA_Y798          0.248128\n",
       "EPHA2_Y588          0.282019\n",
       "PTK2_Y397           0.308890\n",
       "ANXA2_Y238          0.316979\n",
       "dtype: float64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Who are the things that experience significant differences by clustering? \n",
    "diffSort "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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