walk.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy\n",
    "import pandas\n",
    "\n",
    "import rwwr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# restart probability\n",
    "r = 0.2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "90"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read genetic overlap between diseases\n",
    "dice_df = pandas.read_table('data/disease-similarity.tsv', index_col=0)\n",
    "len(dice_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "82"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Filter diseases without any similarity\n",
    "doid_ids = dice_df.columns[(dice_df > 0).sum() > 1]\n",
    "dice_df = dice_df.loc[doid_ids, doid_ids]\n",
    "len(dice_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Run random walk for each disease\n",
    "rows = list()\n",
    "\n",
    "for doid_id in dice_df.columns:\n",
    "    df = dice_df.copy()\n",
    "    df = df.drop(doid_id, axis=0) # drop row\n",
    "    seed = df[doid_id]\n",
    "    df = df.drop(doid_id, axis=1) # drop column\n",
    "    mat = df.as_matrix()\n",
    "    probs, steps = rwwr.walk(r, seed, mat)\n",
    "    rows.extend(zip([doid_id] * len(df), df.columns, probs))\n",
    "\n",
    "rw_df = pandas.DataFrame(rows, columns=['source_id', 'target_id', 'proximity'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Add Disease Ontology names\n",
    "url = 'https://raw.githubusercontent.com/dhimmel/disease-ontology/72614ade9f1cc5a5317b8f6836e1e464b31d5587/data/term-names.tsv'\n",
    "doid_df = pandas.read_table(url).query(\"type == 'name'\").drop('type', 1)\n",
    "s_df = doid_df.rename(columns={'doid': 'source_id', 'name': 'source_name'})\n",
    "t_df = doid_df.rename(columns={'doid': 'target_id', 'name': 'target_name'})\n",
    "rw_df = s_df.merge(t_df.merge(rw_df))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Sort by disease_name and proximity\n",
    "rw_df = rw_df.sort(['source_name', 'proximity'], ascending=[True, False])\n",
    "# Save as a tsv\n",
    "rw_df.to_csv('data/proximities.tsv', sep='\\t', index=False, float_format='%.6f')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>source_id</th>\n",
       "      <th>source_name</th>\n",
       "      <th>target_id</th>\n",
       "      <th>target_name</th>\n",
       "      <th>proximity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1411</th>\n",
       "      <td>DOID:2377</td>\n",
       "      <td>multiple sclerosis</td>\n",
       "      <td>DOID:10608</td>\n",
       "      <td>celiac disease</td>\n",
       "      <td>0.080378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1385</th>\n",
       "      <td>DOID:2377</td>\n",
       "      <td>multiple sclerosis</td>\n",
       "      <td>DOID:8778</td>\n",
       "      <td>Crohn's disease</td>\n",
       "      <td>0.061036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1407</th>\n",
       "      <td>DOID:2377</td>\n",
       "      <td>multiple sclerosis</td>\n",
       "      <td>DOID:12236</td>\n",
       "      <td>primary biliary cirrhosis</td>\n",
       "      <td>0.052170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1457</th>\n",
       "      <td>DOID:2377</td>\n",
       "      <td>multiple sclerosis</td>\n",
       "      <td>DOID:9744</td>\n",
       "      <td>type 1 diabetes mellitus</td>\n",
       "      <td>0.049153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1404</th>\n",
       "      <td>DOID:2377</td>\n",
       "      <td>multiple sclerosis</td>\n",
       "      <td>DOID:8577</td>\n",
       "      <td>ulcerative colitis</td>\n",
       "      <td>0.045905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1395</th>\n",
       "      <td>DOID:2377</td>\n",
       "      <td>multiple sclerosis</td>\n",
       "      <td>DOID:7148</td>\n",
       "      <td>rheumatoid arthritis</td>\n",
       "      <td>0.040804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1454</th>\n",
       "      <td>DOID:2377</td>\n",
       "      <td>multiple sclerosis</td>\n",
       "      <td>DOID:2841</td>\n",
       "      <td>asthma</td>\n",
       "      <td>0.040312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1423</th>\n",
       "      <td>DOID:2377</td>\n",
       "      <td>multiple sclerosis</td>\n",
       "      <td>DOID:8893</td>\n",
       "      <td>psoriasis</td>\n",
       "      <td>0.037900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1394</th>\n",
       "      <td>DOID:2377</td>\n",
       "      <td>multiple sclerosis</td>\n",
       "      <td>DOID:7147</td>\n",
       "      <td>ankylosing spondylitis</td>\n",
       "      <td>0.035559</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1409</th>\n",
       "      <td>DOID:2377</td>\n",
       "      <td>multiple sclerosis</td>\n",
       "      <td>DOID:4481</td>\n",
       "      <td>allergic rhinitis</td>\n",
       "      <td>0.035437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1431</th>\n",
       "      <td>DOID:2377</td>\n",
       "      <td>multiple sclerosis</td>\n",
       "      <td>DOID:8567</td>\n",
       "      <td>Hodgkin's lymphoma</td>\n",
       "      <td>0.031840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1452</th>\n",
       "      <td>DOID:2377</td>\n",
       "      <td>multiple sclerosis</td>\n",
       "      <td>DOID:9074</td>\n",
       "      <td>systemic lupus erythematosus</td>\n",
       "      <td>0.029657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1402</th>\n",
       "      <td>DOID:2377</td>\n",
       "      <td>multiple sclerosis</td>\n",
       "      <td>DOID:12306</td>\n",
       "      <td>vitiligo</td>\n",
       "      <td>0.029418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1448</th>\n",
       "      <td>DOID:2377</td>\n",
       "      <td>multiple sclerosis</td>\n",
       "      <td>DOID:5082</td>\n",
       "      <td>liver cirrhosis</td>\n",
       "      <td>0.029288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1410</th>\n",
       "      <td>DOID:2377</td>\n",
       "      <td>multiple sclerosis</td>\n",
       "      <td>DOID:332</td>\n",
       "      <td>amyotrophic lateral sclerosis</td>\n",
       "      <td>0.026867</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      source_id         source_name   target_id  \\\n",
       "1411  DOID:2377  multiple sclerosis  DOID:10608   \n",
       "1385  DOID:2377  multiple sclerosis   DOID:8778   \n",
       "1407  DOID:2377  multiple sclerosis  DOID:12236   \n",
       "1457  DOID:2377  multiple sclerosis   DOID:9744   \n",
       "1404  DOID:2377  multiple sclerosis   DOID:8577   \n",
       "1395  DOID:2377  multiple sclerosis   DOID:7148   \n",
       "1454  DOID:2377  multiple sclerosis   DOID:2841   \n",
       "1423  DOID:2377  multiple sclerosis   DOID:8893   \n",
       "1394  DOID:2377  multiple sclerosis   DOID:7147   \n",
       "1409  DOID:2377  multiple sclerosis   DOID:4481   \n",
       "1431  DOID:2377  multiple sclerosis   DOID:8567   \n",
       "1452  DOID:2377  multiple sclerosis   DOID:9074   \n",
       "1402  DOID:2377  multiple sclerosis  DOID:12306   \n",
       "1448  DOID:2377  multiple sclerosis   DOID:5082   \n",
       "1410  DOID:2377  multiple sclerosis    DOID:332   \n",
       "\n",
       "                        target_name  proximity  \n",
       "1411                 celiac disease   0.080378  \n",
       "1385                Crohn's disease   0.061036  \n",
       "1407      primary biliary cirrhosis   0.052170  \n",
       "1457       type 1 diabetes mellitus   0.049153  \n",
       "1404             ulcerative colitis   0.045905  \n",
       "1395           rheumatoid arthritis   0.040804  \n",
       "1454                         asthma   0.040312  \n",
       "1423                      psoriasis   0.037900  \n",
       "1394         ankylosing spondylitis   0.035559  \n",
       "1409              allergic rhinitis   0.035437  \n",
       "1431             Hodgkin's lymphoma   0.031840  \n",
       "1452   systemic lupus erythematosus   0.029657  \n",
       "1402                       vitiligo   0.029418  \n",
       "1448                liver cirrhosis   0.029288  \n",
       "1410  amyotrophic lateral sclerosis   0.026867  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Top MS proximities\n",
    "rw_df.query(\"source_name == 'multiple sclerosis'\").head(15)"
   ]
  }
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