luck_analyses.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from domain_vis.domain_vis_luck import visualize_domains_and_plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chain_id</th>\n",
       "      <th>ted_id</th>\n",
       "      <th>HMM-superfamily</th>\n",
       "      <th>TED-superfamily</th>\n",
       "      <th>hmm_evalue</th>\n",
       "      <th>overlap_percentage</th>\n",
       "      <th>hmm_boundaries</th>\n",
       "      <th>foldseek_boundaries</th>\n",
       "      <th>s95-HMM-superfamily</th>\n",
       "      <th>match</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AF-M0R2J8-F1-model_v4</td>\n",
       "      <td>AF-M0R2J8-F1-model_v4_TED01</td>\n",
       "      <td>3.10.20.230</td>\n",
       "      <td>3.10.20.230</td>\n",
       "      <td>4.500000e-04</td>\n",
       "      <td>96.30</td>\n",
       "      <td>173-253</td>\n",
       "      <td>175-252</td>\n",
       "      <td>2dnfA01</td>\n",
       "      <td>match</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AF-M0R2J8-F1-model_v4</td>\n",
       "      <td>AF-M0R2J8-F1-model_v4_TED02</td>\n",
       "      <td>3.10.20.230</td>\n",
       "      <td>3.10.20.230</td>\n",
       "      <td>8.100000e-04</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1397-1486</td>\n",
       "      <td>294-474</td>\n",
       "      <td>1mg4A00</td>\n",
       "      <td>match</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AF-M0R2J8-F1-model_v4</td>\n",
       "      <td>AF-M0R2J8-F1-model_v4_TED03</td>\n",
       "      <td>3.10.20.230</td>\n",
       "      <td>3.10.20.230</td>\n",
       "      <td>8.100000e-04</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1397-1486</td>\n",
       "      <td>492-580</td>\n",
       "      <td>1mg4A00</td>\n",
       "      <td>match</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AF-M0R2J8-F1-model_v4</td>\n",
       "      <td>AF-M0R2J8-F1-model_v4_TED07</td>\n",
       "      <td>2.80.10.50</td>\n",
       "      <td>2.80.10.50</td>\n",
       "      <td>1.200000e-04</td>\n",
       "      <td>67.09</td>\n",
       "      <td>1141-1267</td>\n",
       "      <td>1045-1067_1162-1275</td>\n",
       "      <td>2vlcA04</td>\n",
       "      <td>match</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AF-M0R2J8-F1-model_v4</td>\n",
       "      <td>AF-M0R2J8-F1-model_v4_TED09</td>\n",
       "      <td>3.10.20.230</td>\n",
       "      <td>3.10.20.230</td>\n",
       "      <td>6.400000e-07</td>\n",
       "      <td>63.20</td>\n",
       "      <td>1631-1755</td>\n",
       "      <td>1668-1746</td>\n",
       "      <td>2bqqA00</td>\n",
       "      <td>match</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                chain_id                       ted_id HMM-superfamily  \\\n",
       "0  AF-M0R2J8-F1-model_v4  AF-M0R2J8-F1-model_v4_TED01     3.10.20.230   \n",
       "1  AF-M0R2J8-F1-model_v4  AF-M0R2J8-F1-model_v4_TED02     3.10.20.230   \n",
       "2  AF-M0R2J8-F1-model_v4  AF-M0R2J8-F1-model_v4_TED03     3.10.20.230   \n",
       "3  AF-M0R2J8-F1-model_v4  AF-M0R2J8-F1-model_v4_TED07      2.80.10.50   \n",
       "4  AF-M0R2J8-F1-model_v4  AF-M0R2J8-F1-model_v4_TED09     3.10.20.230   \n",
       "\n",
       "  TED-superfamily    hmm_evalue  overlap_percentage hmm_boundaries  \\\n",
       "0     3.10.20.230  4.500000e-04               96.30        173-253   \n",
       "1     3.10.20.230  8.100000e-04                0.00      1397-1486   \n",
       "2     3.10.20.230  8.100000e-04                0.00      1397-1486   \n",
       "3      2.80.10.50  1.200000e-04               67.09      1141-1267   \n",
       "4     3.10.20.230  6.400000e-07               63.20      1631-1755   \n",
       "\n",
       "   foldseek_boundaries s95-HMM-superfamily  match  \n",
       "0              175-252             2dnfA01  match  \n",
       "1              294-474             1mg4A00  match  \n",
       "2              492-580             1mg4A00  match  \n",
       "3  1045-1067_1162-1275             2vlcA04  match  \n",
       "4            1668-1746             2bqqA00  match  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"data/luck_analyses_human/luck_results.tsv\", sep = \"\\t\", header = None)\n",
    "df.columns = ['chain_id', 'ted_id', 'HMM-superfamily', 'TED-superfamily', 'hmm_evalue', 'overlap_percentage', 'hmm_boundaries', 'foldseek_boundaries', 's95-HMM-superfamily']\n",
    "df['match'] = df.apply(lambda row: 'match' if row['HMM-superfamily'] == row['TED-superfamily'] else 'no match', axis=1)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<>:1: SyntaxWarning: invalid escape sequence '\\s'\n",
      "<>:1: SyntaxWarning: invalid escape sequence '\\s'\n",
      "/var/folders/n4/sdx4zvks1m76mtqqpm6rw32w0000gn/T/ipykernel_5782/431429933.py:1: SyntaxWarning: invalid escape sequence '\\s'\n",
      "  df2 = pd.read_csv(\"data/luck_analyses_human/all_luck_domains_in_ted\", sep='\\s', header= None)\n",
      "/var/folders/n4/sdx4zvks1m76mtqqpm6rw32w0000gn/T/ipykernel_5782/431429933.py:1: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n",
      "  df2 = pd.read_csv(\"data/luck_analyses_human/all_luck_domains_in_ted\", sep='\\s', header= None)\n"
     ]
    }
   ],
   "source": [
    "df2 = pd.read_csv(\"data/luck_analyses_human/all_luck_domains_in_ted\", sep='\\s', header= None)\n",
    "df2 = df2[[0, 6, 16]]\n",
    "df2.columns = ['ted_id', 'plddt', 'packing_density']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chain_id</th>\n",
       "      <th>ted_id</th>\n",
       "      <th>HMM-superfamily</th>\n",
       "      <th>TED-superfamily</th>\n",
       "      <th>hmm_evalue</th>\n",
       "      <th>overlap_percentage</th>\n",
       "      <th>hmm_boundaries</th>\n",
       "      <th>foldseek_boundaries</th>\n",
       "      <th>s95-HMM-superfamily</th>\n",
       "      <th>match</th>\n",
       "      <th>plddt</th>\n",
       "      <th>packing_density</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AF-M0R2J8-F1-model_v4</td>\n",
       "      <td>AF-M0R2J8-F1-model_v4_TED01</td>\n",
       "      <td>3.10.20.230</td>\n",
       "      <td>3.10.20.230</td>\n",
       "      <td>4.500000e-04</td>\n",
       "      <td>96.30</td>\n",
       "      <td>173-253</td>\n",
       "      <td>175-252</td>\n",
       "      <td>2dnfA01</td>\n",
       "      <td>match</td>\n",
       "      <td>87.2153</td>\n",
       "      <td>11.289</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AF-M0R2J8-F1-model_v4</td>\n",
       "      <td>AF-M0R2J8-F1-model_v4_TED02</td>\n",
       "      <td>3.10.20.230</td>\n",
       "      <td>3.10.20.230</td>\n",
       "      <td>8.100000e-04</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1397-1486</td>\n",
       "      <td>294-474</td>\n",
       "      <td>1mg4A00</td>\n",
       "      <td>match</td>\n",
       "      <td>82.1267</td>\n",
       "      <td>12.012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AF-M0R2J8-F1-model_v4</td>\n",
       "      <td>AF-M0R2J8-F1-model_v4_TED03</td>\n",
       "      <td>3.10.20.230</td>\n",
       "      <td>3.10.20.230</td>\n",
       "      <td>8.100000e-04</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1397-1486</td>\n",
       "      <td>492-580</td>\n",
       "      <td>1mg4A00</td>\n",
       "      <td>match</td>\n",
       "      <td>75.3787</td>\n",
       "      <td>11.256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AF-M0R2J8-F1-model_v4</td>\n",
       "      <td>AF-M0R2J8-F1-model_v4_TED07</td>\n",
       "      <td>2.80.10.50</td>\n",
       "      <td>2.80.10.50</td>\n",
       "      <td>1.200000e-04</td>\n",
       "      <td>67.09</td>\n",
       "      <td>1141-1267</td>\n",
       "      <td>1045-1067_1162-1275</td>\n",
       "      <td>2vlcA04</td>\n",
       "      <td>match</td>\n",
       "      <td>85.4528</td>\n",
       "      <td>12.242</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AF-M0R2J8-F1-model_v4</td>\n",
       "      <td>AF-M0R2J8-F1-model_v4_TED09</td>\n",
       "      <td>3.10.20.230</td>\n",
       "      <td>3.10.20.230</td>\n",
       "      <td>6.400000e-07</td>\n",
       "      <td>63.20</td>\n",
       "      <td>1631-1755</td>\n",
       "      <td>1668-1746</td>\n",
       "      <td>2bqqA00</td>\n",
       "      <td>match</td>\n",
       "      <td>87.4824</td>\n",
       "      <td>11.432</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                chain_id                       ted_id HMM-superfamily  \\\n",
       "0  AF-M0R2J8-F1-model_v4  AF-M0R2J8-F1-model_v4_TED01     3.10.20.230   \n",
       "1  AF-M0R2J8-F1-model_v4  AF-M0R2J8-F1-model_v4_TED02     3.10.20.230   \n",
       "2  AF-M0R2J8-F1-model_v4  AF-M0R2J8-F1-model_v4_TED03     3.10.20.230   \n",
       "3  AF-M0R2J8-F1-model_v4  AF-M0R2J8-F1-model_v4_TED07      2.80.10.50   \n",
       "4  AF-M0R2J8-F1-model_v4  AF-M0R2J8-F1-model_v4_TED09     3.10.20.230   \n",
       "\n",
       "  TED-superfamily    hmm_evalue  overlap_percentage hmm_boundaries  \\\n",
       "0     3.10.20.230  4.500000e-04               96.30        173-253   \n",
       "1     3.10.20.230  8.100000e-04                0.00      1397-1486   \n",
       "2     3.10.20.230  8.100000e-04                0.00      1397-1486   \n",
       "3      2.80.10.50  1.200000e-04               67.09      1141-1267   \n",
       "4     3.10.20.230  6.400000e-07               63.20      1631-1755   \n",
       "\n",
       "   foldseek_boundaries s95-HMM-superfamily  match    plddt  packing_density  \n",
       "0              175-252             2dnfA01  match  87.2153           11.289  \n",
       "1              294-474             1mg4A00  match  82.1267           12.012  \n",
       "2              492-580             1mg4A00  match  75.3787           11.256  \n",
       "3  1045-1067_1162-1275             2vlcA04  match  85.4528           12.242  \n",
       "4            1668-1746             2bqqA00  match  87.4824           11.432  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.merge(df, df2, on='ted_id', how='left')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "VBox(children=(VBox(children=(Dropdown(description='Sort by:', options=('Index', 'HMM E-value', 'Overlap Perce…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "visualize_domains_and_plot(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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