schistosome_orthologue_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "import os.path\n",
    "\n",
    "from IPython.display import Image, display\n",
    "import pandas as pd\n",
    "\n",
    "from utils.statistics import cov"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 10,
     "metadata": {
      "image/png": {
       "width": 900
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(\"plots/N0.HOG0008263.png\", width=900)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![title](plots/N0.HOG0008263.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sort_items_by_cov(path):\n",
    "    with open(path, \"r\") as f:\n",
    "        data = json.load(f)\n",
    "    return sorted(data.items(), key=lambda item: cov(item[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "hog_by_closest_prot_lengths = sort_items_by_cov(\"prot_lengths.json\")\n",
    "hog_by_closest_exon_counts = sort_items_by_cov(\"exon_counts.json\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pick out examples of HOGs that have the greatest variation of prot lengths / exon counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "('N0.HOG0005898', [1, 3, 1, 1, 1, 1, 1, 10])\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/png": {
       "width": 900
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "start_idx = 0\n",
    "for idx, hog in enumerate(list(reversed(hog_by_closest_exon_counts))[start_idx:]):\n",
    "    plot_path = \"plots/\" + hog[0] + \".png\"\n",
    "    if os.path.exists(plot_path):\n",
    "        print(idx + start_idx)\n",
    "        print(hog)\n",
    "        display(Image(plot_path, width=900))\n",
    "        break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "prot_length_covs = {}\n",
    "for (hog, prot_lengths) in hog_by_closest_prot_lengths:\n",
    "    prot_length_covs[hog] = cov(prot_lengths)\n",
    "\n",
    "exon_count_covs = {}\n",
    "for (hog, exon_counts) in hog_by_closest_exon_counts:\n",
    "    exon_count_covs[hog] = cov(exon_counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "hog_covs = {}\n",
    "for (hog, _) in hog_by_closest_exon_counts:\n",
    "    hog_covs[hog] = [prot_length_covs[hog], exon_count_covs[hog]]\n",
    "\n",
    "# Sorted by highest overall COVs\n",
    "sort = sorted(hog_covs.items(), key=lambda item: sum(item[1]))\n",
    "\n",
    "# Sorted by protein length COV vs exon count COV\n",
    "sort = sorted(hog_covs.items(), key=lambda x: (x[1][0]-x[1][1]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pick out examples of HOGs based on their combined COV scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "('N0.HOG0005007', [1.7788391757893334, 0.038745577051317676])\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/png": {
       "width": 900
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "start_idx = 0\n",
    "for idx, hog in enumerate(list(reversed(sort))[start_idx:]):\n",
    "    plot_path = \"plots/\" + hog[0] + \".png\"\n",
    "    if os.path.exists(plot_path):\n",
    "        print(idx + start_idx)\n",
    "        print(hog)\n",
    "        display(Image(plot_path, width=900))\n",
    "        break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>prot_length_covs</th>\n",
       "      <th>exon_count_covs</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>N0.HOG0007956</th>\n",
       "      <td>0.838784</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N0.HOG0007459</th>\n",
       "      <td>0.392315</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N0.HOG0005441</th>\n",
       "      <td>0.331996</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N0.HOG0003141</th>\n",
       "      <td>0.305012</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N0.HOG0001509</th>\n",
       "      <td>0.304165</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               prot_length_covs  exon_count_covs\n",
       "N0.HOG0007956          0.838784              0.0\n",
       "N0.HOG0007459          0.392315              0.0\n",
       "N0.HOG0005441          0.331996              0.0\n",
       "N0.HOG0003141          0.305012              0.0\n",
       "N0.HOG0001509          0.304165              0.0"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame.from_records(hog_covs, index=[\"prot_length_covs\", \"exon_count_covs\"]).T\n",
    "df[df[\"exon_count_covs\"] == 0].sort_values(\"prot_length_covs\", ascending=False).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>prot_length_covs</th>\n",
       "      <th>exon_count_covs</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>N0.HOG0000603</th>\n",
       "      <td>0.004561</td>\n",
       "      <td>0.942809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N0.HOG0005826</th>\n",
       "      <td>0.007655</td>\n",
       "      <td>0.617213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N0.HOG0005448</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.565685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N0.HOG0005465</th>\n",
       "      <td>0.004441</td>\n",
       "      <td>0.376399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N0.HOG0003969</th>\n",
       "      <td>0.008647</td>\n",
       "      <td>0.370328</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               prot_length_covs  exon_count_covs\n",
       "N0.HOG0000603          0.004561         0.942809\n",
       "N0.HOG0005826          0.007655         0.617213\n",
       "N0.HOG0005448          0.000000         0.565685\n",
       "N0.HOG0005465          0.004441         0.376399\n",
       "N0.HOG0003969          0.008647         0.370328"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df[\"prot_length_covs\"] <= 0.01].sort_values(\"exon_count_covs\", ascending=False).head()"
   ]
  }
 ],
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