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  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Calculating synthetic lethal gene and reaction pairs\n",
      "\n",
      "#### An example notebook to accompany Systems biology-guided identification of new combination antibiotics based on synthetic lethality\n",
      "###### Aziz et al, Scientific Reports, Under Review"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#### Required imports:\n",
      "##### cobrapy: https://github.com/opencobra/cobrapy\n",
      "##### pandas: http://pandas.pydata.org/"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from cobra.flux_analysis.double_deletion import double_gene_deletion_fba, double_reaction_deletion_fba\n",
      "from cobra.io import load_matlab_model, save_matlab_model\n",
      "import pandas as pd"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 12
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import os\n",
      "os.chdir('/media/users/jmonk/helper/models/')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Load the model\n",
      "model = load_matlab_model('iJO1366.mat')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Model is pre-defined with M9 media bounds - check its predicted growth rate:\n",
      "model.optimize()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "<Solution 0.98 at 0x7fbc6b4aa0d0>"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Set model to grow on in-silico LB media"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "LBMEDIA = {}\n",
      "rxn_exchange_dict = {}\n",
      "\n",
      "LBMEDIA['EX_glc_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_ala_DASH_L_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_arg_DASH_L_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_asp_DASH_L_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_cys_DASH_L_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_glu_DASH_L_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_gly_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_his_DASH_L_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_ile_DASH_L_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_leu_DASH_L_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_lys_DASH_L_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_met_DASH_L_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_pro_DASH_L_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_thr_DASH_L_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_tyr_DASH_L_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_phe_DASH_L_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_ser_DASH_L_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_trp_DASH_L_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_val_DASH_L_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_pnto_DASH_R_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_nac_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_na1_LPAREN_e_RPAREN_'] = -1000\n",
      "LBMEDIA['EX_cl_LPAREN_e_RPAREN_'] = -1000\n",
      "LBMEDIA['EX_so4_LPAREN_e_RPAREN_'] = -1000\n",
      "LBMEDIA['EX_k_LPAREN_e_RPAREN_'] = -1000\n",
      "LBMEDIA['EX_pi_LPAREN_e_RPAREN_'] = -1000\n",
      "LBMEDIA['EX_ca2_LPAREN_e_RPAREN_'] = -1000\n",
      "LBMEDIA['EX_mg2_LPAREN_e_RPAREN_'] = -1000\n",
      "LBMEDIA['EX_zn2_LPAREN_e_RPAREN_'] = -1000\n",
      "LBMEDIA['EX_aso3_LPAREN_e_RPAREN_'] = -1000\n",
      "LBMEDIA['EX_cd2_LPAREN_e_RPAREN_'] = -1000\n",
      "LBMEDIA['EX_hg2_LPAREN_e_RPAREN_'] = -1000\n",
      "LBMEDIA['EX_h_LPAREN_e_RPAREN_'] = -100\n",
      "LBMEDIA['EX_h2o_LPAREN_e_RPAREN_'] = -100\n",
      "LBMEDIA['EX_o2_LPAREN_e_RPAREN_'] = -18.5\n",
      "LBMEDIA['EX_ins_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_hxan_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_dcyt_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_thymd_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_ura_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_uri_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_dad_DASH_2_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_adn_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_co2_LPAREN_e_RPAREN_'] = -1000\n",
      "LBMEDIA['EX_cobalt2_LPAREN_e_RPAREN_'] = -1000\n",
      "LBMEDIA['EX_cu2_LPAREN_e_RPAREN_'] = -1000\n",
      "LBMEDIA['EX_fe2_LPAREN_e_RPAREN_'] = -1000\n",
      "LBMEDIA['EX_fe3_LPAREN_e_RPAREN_'] = -1000\n",
      "LBMEDIA['EX_mn2_LPAREN_e_RPAREN_'] = -1000\n",
      "LBMEDIA['EX_mobd_LPAREN_e_RPAREN_'] = -1000\n",
      "LBMEDIA['EX_tungs_LPAREN_e_RPAREN_'] = -1000\n",
      "LBMEDIA['EX_cbl1_LPAREN_e_RPAREN_'] = -0.01\n",
      "LBMEDIA['EX_fru_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_gal_LPAREN_e_RPAREN_'] = -5\n",
      "LBMEDIA['EX_ni2_LPAREN_e_RPAREN_'] = -1000.0\n",
      "LBMEDIA['EX_sel_LPAREN_e_RPAREN_'] = -1000.0\n",
      "LBMEDIA['EX_slnt_LPAREN_e_RPAREN_'] = -1000.0"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for r in model.reactions:\n",
      "    if r.startswith('EX_'):\n",
      "        r.lower_bound = 0\n",
      "    if r.id in LBMEDIA.keys():\n",
      "        r.lower_bound = LBMEDIA[r.id]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Check model predicted growth rate on LB media\n",
      "model.optimize()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 9,
       "text": [
        "<Solution 3.50 at 0x7fbc6b504450>"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Perform double gene deletion analysis"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "dko_genes = double_gene_deletion_fba(model, return_frame=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 18
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "dko_genes.head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
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        "      <td> 3.50329</td>\n",
        "      <td> 3.50329</td>\n",
        "      <td> 3.50329</td>\n",
        "      <td> 3.50329</td>\n",
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        "      <td> 3.50329</td>\n",
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        "      <td> 3.50329</td>\n",
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        "      <td> 3.50329</td>\n",
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        "      <td>...</td>\n",
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        "    <tr>\n",
        "      <th>b0929</th>\n",
        "      <td> 3.50329</td>\n",
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        "      <td> 3.50329</td>\n",
        "      <td> 3.50329</td>\n",
        "      <td> 3.50329</td>\n",
        "      <td> 3.50329</td>\n",
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        "      <td> 3.50329</td>\n",
        "      <td> 3.364163</td>\n",
        "      <td> 3.50329</td>\n",
        "      <td> 3.50329</td>\n",
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        "      <td> 3.50329</td>\n",
        "      <td> 3.50329</td>\n",
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        "    <tr>\n",
        "      <th>b4034</th>\n",
        "      <td> 3.50329</td>\n",
        "      <td> 3.50329</td>\n",
        "      <td> 3.50329</td>\n",
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        "      <td> 3.50329</td>\n",
        "      <td> 3.364163</td>\n",
        "      <td> 3.50329</td>\n",
        "      <td> 3.50329</td>\n",
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        "      <td> 3.50329</td>\n",
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        "      <td> 3.50329</td>\n",
        "      <td> 3.50329</td>\n",
        "      <td>...</td>\n",
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        "  </tbody>\n",
        "</table>\n",
        "<p>5 rows \u00d7 1367 columns</p>\n",
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       "output_type": "pyout",
       "prompt_number": 20,
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        "         b0241    b2215    b1377    b0929    b4034    b4035    b4033    b4032  \\\n",
        "b0241  3.50329  3.50329  3.50329  3.50329  3.50329  3.50329  3.50329  3.50329   \n",
        "b2215  3.50329  3.50329  3.50329  3.50329  3.50329  3.50329  3.50329  3.50329   \n",
        "b1377  3.50329  3.50329  3.50329  3.50329  3.50329  3.50329  3.50329  3.50329   \n",
        "b0929  3.50329  3.50329  3.50329  3.50329  3.50329  3.50329  3.50329  3.50329   \n",
        "b4034  3.50329  3.50329  3.50329  3.50329  3.50329  3.50329  3.50329  3.50329   \n",
        "\n",
        "         b4036    b4213    b2835     b2836    b3553    b0446    b1134  \\\n",
        "b0241  3.50329  3.50329  3.50329  3.364163  3.50329  3.50329  3.50329   \n",
        "b2215  3.50329  3.50329  3.50329  3.364163  3.50329  3.50329  3.50329   \n",
        "b1377  3.50329  3.50329  3.50329  3.364163  3.50329  3.50329  3.50329   \n",
        "b0929  3.50329  3.50329  3.50329  3.364163  3.50329  3.50329  3.50329   \n",
        "b4034  3.50329  3.50329  3.50329  3.364163  3.50329  3.50329  3.50329   \n",
        "\n",
        "         b1009    b0954  b0180    b0347    b3580      \n",
        "b0241  3.50329  3.50329      0  3.50329  3.50329 ...  \n",
        "b2215  3.50329  3.50329      0  3.50329  3.50329 ...  \n",
        "b1377  3.50329  3.50329      0  3.50329  3.50329 ...  \n",
        "b0929  3.50329  3.50329      0  3.50329  3.50329 ...  \n",
        "b4034  3.50329  3.50329      0  3.50329  3.50329 ...  \n",
        "\n",
        "[5 rows x 1367 columns]"
       ]
      }
     ],
     "prompt_number": 20
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Deleting RXNs (instead of genes)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "dko_reactions = double_reaction_deletion_fba(model, return_frame=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "dko_reactions.head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
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        "      <th></th>\n",
        "      <th>DM_4CRSOL</th>\n",
        "      <th>DM_5DRIB</th>\n",
        "      <th>DM_AACALD</th>\n",
        "      <th>DM_AMOB</th>\n",
        "      <th>DM_MTHTHF</th>\n",
        "      <th>DM_OXAM</th>\n",
        "      <th>Ec_biomass_iJO1366_WT_53p95M</th>\n",
        "      <th>Ec_biomass_iJO1366_core_53p95M</th>\n",
        "      <th>EX_12ppd_DASH_R_LPAREN_e_RPAREN_</th>\n",
        "      <th>EX_12ppd_DASH_S_LPAREN_e_RPAREN_</th>\n",
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        "      <th>EX_15dap_LPAREN_e_RPAREN_</th>\n",
        "      <th>EX_23camp_LPAREN_e_RPAREN_</th>\n",
        "      <th>EX_23ccmp_LPAREN_e_RPAREN_</th>\n",
        "      <th>EX_23cgmp_LPAREN_e_RPAREN_</th>\n",
        "      <th>EX_23cump_LPAREN_e_RPAREN_</th>\n",
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        "      <td> 0.000000e+00</td>\n",
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        "      <td> 0</td>\n",
        "      <td> 0.000000e+00</td>\n",
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        "      <td> 0.000000e+00</td>\n",
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        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td>...</td>\n",
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        "    <tr>\n",
        "      <th>DM_5DRIB</th>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0.00000</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>DM_AACALD</th>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 3.50329</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 3.503290e+00</td>\n",
        "      <td> 3.503290e+00</td>\n",
        "      <td> 0</td>\n",
        "      <td> 3.503290e+00</td>\n",
        "      <td> 3.503290e+00</td>\n",
        "      <td> 3.503290e+00</td>\n",
        "      <td> 3.503290e+00</td>\n",
        "      <td> 3.503290e+00</td>\n",
        "      <td> 3.503290e+00</td>\n",
        "      <td> 3.503290e+00</td>\n",
        "      <td> 3.503290e+00</td>\n",
        "      <td> 3.503290e+00</td>\n",
        "      <td> 3.503290e+00</td>\n",
        "      <td> 3.503290e+00</td>\n",
        "      <td> 3.503290e+00</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>DM_AMOB</th>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0.00000</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td> 0.000000e+00</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>DM_MTHTHF</th>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0.00000</td>\n",
        "      <td> 0</td>\n",
        "      <td>-4.510340e-13</td>\n",
        "      <td> 3.165575e-12</td>\n",
        "      <td> 3.165575e-12</td>\n",
        "      <td> 0</td>\n",
        "      <td> 3.165575e-12</td>\n",
        "      <td> 3.165575e-12</td>\n",
        "      <td> 3.165575e-12</td>\n",
        "      <td> 3.165575e-12</td>\n",
        "      <td> 3.165575e-12</td>\n",
        "      <td> 3.165575e-12</td>\n",
        "      <td> 3.165575e-12</td>\n",
        "      <td> 3.165575e-12</td>\n",
        "      <td> 3.165575e-12</td>\n",
        "      <td> 7.035882e-25</td>\n",
        "      <td> 3.165575e-12</td>\n",
        "      <td> 3.165575e-12</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>5 rows \u00d7 2583 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 17,
       "text": [
        "           DM_4CRSOL  DM_5DRIB  DM_AACALD  DM_AMOB     DM_MTHTHF  \\\n",
        "DM_4CRSOL          0         0    0.00000        0  0.000000e+00   \n",
        "DM_5DRIB           0         0    0.00000        0  0.000000e+00   \n",
        "DM_AACALD          0         0    3.50329        0  0.000000e+00   \n",
        "DM_AMOB            0         0    0.00000        0  0.000000e+00   \n",
        "DM_MTHTHF          0         0    0.00000        0 -4.510340e-13   \n",
        "\n",
        "                DM_OXAM  Ec_biomass_iJO1366_WT_53p95M  \\\n",
        "DM_4CRSOL  0.000000e+00                  0.000000e+00   \n",
        "DM_5DRIB   0.000000e+00                  0.000000e+00   \n",
        "DM_AACALD  3.503290e+00                  3.503290e+00   \n",
        "DM_AMOB    0.000000e+00                  0.000000e+00   \n",
        "DM_MTHTHF  3.165575e-12                  3.165575e-12   \n",
        "\n",
        "           Ec_biomass_iJO1366_core_53p95M  EX_12ppd_DASH_R_LPAREN_e_RPAREN_  \\\n",
        "DM_4CRSOL                               0                      0.000000e+00   \n",
        "DM_5DRIB                                0                      0.000000e+00   \n",
        "DM_AACALD                               0                      3.503290e+00   \n",
        "DM_AMOB                                 0                      0.000000e+00   \n",
        "DM_MTHTHF                               0                      3.165575e-12   \n",
        "\n",
        "           EX_12ppd_DASH_S_LPAREN_e_RPAREN_  EX_14glucan_LPAREN_e_RPAREN_  \\\n",
        "DM_4CRSOL                      0.000000e+00                  0.000000e+00   \n",
        "DM_5DRIB                       0.000000e+00                  0.000000e+00   \n",
        "DM_AACALD                      3.503290e+00                  3.503290e+00   \n",
        "DM_AMOB                        0.000000e+00                  0.000000e+00   \n",
        "DM_MTHTHF                      3.165575e-12                  3.165575e-12   \n",
        "\n",
        "           EX_15dap_LPAREN_e_RPAREN_  EX_23camp_LPAREN_e_RPAREN_  \\\n",
        "DM_4CRSOL               0.000000e+00                0.000000e+00   \n",
        "DM_5DRIB                0.000000e+00                0.000000e+00   \n",
        "DM_AACALD               3.503290e+00                3.503290e+00   \n",
        "DM_AMOB                 0.000000e+00                0.000000e+00   \n",
        "DM_MTHTHF               3.165575e-12                3.165575e-12   \n",
        "\n",
        "           EX_23ccmp_LPAREN_e_RPAREN_  EX_23cgmp_LPAREN_e_RPAREN_  \\\n",
        "DM_4CRSOL                0.000000e+00                0.000000e+00   \n",
        "DM_5DRIB                 0.000000e+00                0.000000e+00   \n",
        "DM_AACALD                3.503290e+00                3.503290e+00   \n",
        "DM_AMOB                  0.000000e+00                0.000000e+00   \n",
        "DM_MTHTHF                3.165575e-12                3.165575e-12   \n",
        "\n",
        "           EX_23cump_LPAREN_e_RPAREN_  EX_23dappa_LPAREN_e_RPAREN_  \\\n",
        "DM_4CRSOL                0.000000e+00                 0.000000e+00   \n",
        "DM_5DRIB                 0.000000e+00                 0.000000e+00   \n",
        "DM_AACALD                3.503290e+00                 3.503290e+00   \n",
        "DM_AMOB                  0.000000e+00                 0.000000e+00   \n",
        "DM_MTHTHF                3.165575e-12                 3.165575e-12   \n",
        "\n",
        "           EX_26dap_DASH_M_LPAREN_e_RPAREN_  EX_2ddglcn_LPAREN_e_RPAREN_  \\\n",
        "DM_4CRSOL                      0.000000e+00                 0.000000e+00   \n",
        "DM_5DRIB                       0.000000e+00                 0.000000e+00   \n",
        "DM_AACALD                      3.503290e+00                 3.503290e+00   \n",
        "DM_AMOB                        0.000000e+00                 0.000000e+00   \n",
        "DM_MTHTHF                      7.035882e-25                 3.165575e-12   \n",
        "\n",
        "           EX_34dhpac_LPAREN_e_RPAREN_      \n",
        "DM_4CRSOL                 0.000000e+00 ...  \n",
        "DM_5DRIB                  0.000000e+00 ...  \n",
        "DM_AACALD                 3.503290e+00 ...  \n",
        "DM_AMOB                   0.000000e+00 ...  \n",
        "DM_MTHTHF                 3.165575e-12 ...  \n",
        "\n",
        "[5 rows x 2583 columns]"
       ]
      }
     ],
     "prompt_number": 17
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Analyze the lethal and synthetic lethal genes"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def run_all(dkos, org):\n",
      "    # get singly essential and synthetic lethal genes:\n",
      "    essential = []\n",
      "    syn_lethal = []\n",
      "    for i in dkos.index:\n",
      "        if sum(dkos.ix[i]) < 0.01:\n",
      "            essential.append(i)\n",
      "        else:\n",
      "            for g in dkos.ix[i].index:\n",
      "                if dkos[g].sum() > 0.01:\n",
      "                    if dkos.ix[i][g] < 0.01:\n",
      "                        syn_lethal.append(str(i)+','+str(g))\n",
      "    print len(essential), 'essential genes'\n",
      "    print len(syn_lethal), 'syn lethal genes'\n",
      "    \n",
      "    return {'syn':syn_lethal,'essential':essential}"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 24
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "eco = run_all(dko_genes, 'eco')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "146 essential genes\n",
        "136 syn lethal genes\n"
       ]
      }
     ],
     "prompt_number": 25
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#print essential genes\n",
      "eco['essential']"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 27,
       "text": [
        "['b0180',\n",
        " 'b1093',\n",
        " 'b2323',\n",
        " 'b0159',\n",
        " 'b1094',\n",
        " 's0001',\n",
        " 'b2316',\n",
        " 'b3256',\n",
        " 'b0185',\n",
        " 'b3255',\n",
        " 'b1091',\n",
        " 'b3200',\n",
        " 'b3199',\n",
        " 'b3201',\n",
        " 'b4262',\n",
        " 'b4261',\n",
        " 'b3359',\n",
        " 'b1096',\n",
        " 'b3360',\n",
        " 'b1812',\n",
        " 'b3018',\n",
        " 'b0774',\n",
        " 'b3994',\n",
        " 'b0776',\n",
        " 'b0414',\n",
        " 'b3433',\n",
        " 'b0827',\n",
        " 'b3857',\n",
        " 'b0775',\n",
        " 'b3196',\n",
        " 'b3040',\n",
        " 'b1208',\n",
        " 'b2329',\n",
        " 'b4039',\n",
        " 'b0914',\n",
        " 'b0783',\n",
        " 'b0781',\n",
        " 'b2780',\n",
        " 'b3809',\n",
        " 'b0175',\n",
        " 'b3041',\n",
        " 'b0778',\n",
        " 'b3648',\n",
        " 'b0031',\n",
        " 'b2478',\n",
        " 'b2315',\n",
        " 'b3058',\n",
        " 'b3177',\n",
        " 'b3389',\n",
        " 'b1693',\n",
        " 'b0421',\n",
        " 'b0029',\n",
        " 'b0103',\n",
        " 'b1098',\n",
        " 'b0173',\n",
        " 'b0420',\n",
        " 'b1288',\n",
        " 'b0475',\n",
        " 'b0025',\n",
        " 'b3730',\n",
        " 'b0154',\n",
        " 'b3608',\n",
        " 'b1415',\n",
        " 'b3729',\n",
        " 'b2312',\n",
        " 'b3967',\n",
        " 'b1210',\n",
        " 'b2400',\n",
        " 'b2507',\n",
        " 'b2153',\n",
        " 'b1277',\n",
        " 'b4040',\n",
        " 'b3805',\n",
        " 'b2103',\n",
        " 'b0142',\n",
        " 'b2530',\n",
        " 'b3807',\n",
        " 'b0918',\n",
        " 'b3198',\n",
        " 'b1215',\n",
        " 'b0182',\n",
        " 'b0777',\n",
        " 'b1092',\n",
        " 'b2515',\n",
        " 'b2746',\n",
        " 'b2747',\n",
        " 'b2942',\n",
        " 'b0784',\n",
        " 'b3633',\n",
        " 'b0009',\n",
        " 'b1069',\n",
        " 'b0785',\n",
        " 'b0826',\n",
        " 'b3941',\n",
        " 'b2615',\n",
        " 'b1740',\n",
        " 'b0639',\n",
        " 'b3187',\n",
        " 'b0907',\n",
        " 'b3843',\n",
        " 'b2311',\n",
        " 'b0087',\n",
        " 'b0052',\n",
        " 'b2564',\n",
        " 'b2320',\n",
        " 'b3176',\n",
        " 'b3412',\n",
        " 'b3974',\n",
        " 'b0369',\n",
        " 'b3639',\n",
        " 'b3850',\n",
        " 'b4005',\n",
        " 'b2499',\n",
        " 'b2557',\n",
        " 'b0908',\n",
        " 'b4160',\n",
        " 'b2585',\n",
        " 'b3634',\n",
        " 'b1662',\n",
        " 'b0415',\n",
        " 'b2687',\n",
        " 'b2472',\n",
        " 'b3368',\n",
        " 'b0915',\n",
        " 'b0166',\n",
        " 'b3992',\n",
        " 'b0423',\n",
        " 'b4407',\n",
        " 'b3990',\n",
        " 'b0417',\n",
        " 'b3993',\n",
        " 'b3991',\n",
        " 'b0179',\n",
        " 'b0085',\n",
        " 'b0181',\n",
        " 'b3189',\n",
        " 'b0090',\n",
        " 'b0088',\n",
        " 'b0091',\n",
        " 'b3972',\n",
        " 'b0174',\n",
        " 'b0086',\n",
        " 'b0096',\n",
        " 'b3804',\n",
        " 'b3997',\n",
        " 'b0524']"
       ]
      }
     ],
     "prompt_number": 27
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# print synthetic lethal genes\n",
      "eco['syn']"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 29,
       "text": [
        "['b2836,b0954',\n",
        " 'b0954,b2836',\n",
        " 'b0954,b3846',\n",
        " 'b0954,b0452',\n",
        " 'b2708,b3197',\n",
        " 'b3197,b2708',\n",
        " 'b1849,b2500',\n",
        " 'b1090,b4041',\n",
        " 'b0474,b2518',\n",
        " 'b0474,b1207',\n",
        " 'b0474,b4094',\n",
        " 'b0411,b1131',\n",
        " 'b0411,b4177',\n",
        " 'b1131,b0411',\n",
        " 'b4177,b0411',\n",
        " 'b0381,b0092',\n",
        " 'b0092,b0381',\n",
        " 'b1190,b4053',\n",
        " 'b4053,b1190',\n",
        " 'b3059,b4041',\n",
        " 'b0674,b3744',\n",
        " 'b3744,b0674',\n",
        " 'b0131,b3258',\n",
        " 'b2574,b0931',\n",
        " 'b1592,b0155',\n",
        " 'b0155,b1592',\n",
        " 'b2436,b3867',\n",
        " 'b3867,b2436',\n",
        " 'b3846,b0954',\n",
        " 'b0910,b0171',\n",
        " 'b0048,b1606',\n",
        " 'b1606,b0048',\n",
        " 'b1865,b0099',\n",
        " 'b0099,b1865',\n",
        " 'b1238,b2827',\n",
        " 'b2927,b1779',\n",
        " 'b1779,b2927',\n",
        " 'b0452,b0954',\n",
        " 'b0684,b2895',\n",
        " 'b3924,b1378',\n",
        " 'b2895,b0684',\n",
        " 'b4041,b1090',\n",
        " 'b4041,b3059',\n",
        " 'b2500,b1849',\n",
        " 'b1297,b3870',\n",
        " 'b3870,b1297',\n",
        " 'b0238,b2508',\n",
        " 'b0339,b0126',\n",
        " 'b0126,b0339',\n",
        " 'b4013,b0199',\n",
        " 'b4013,b0197',\n",
        " 'b4013,b0198',\n",
        " 'b2868,b2508',\n",
        " 'b2867,b2508',\n",
        " 'b2866,b2508',\n",
        " 'b2529,b1680',\n",
        " 'b2529,b1679',\n",
        " 'b2529,b1681',\n",
        " 'b2529,b1682',\n",
        " 'b2529,b1683',\n",
        " 'b2529,b1684',\n",
        " 'b2528,b1680',\n",
        " 'b2528,b1679',\n",
        " 'b2528,b1681',\n",
        " 'b2528,b1682',\n",
        " 'b2528,b1683',\n",
        " 'b2528,b1684',\n",
        " 'b2508,b0238',\n",
        " 'b2508,b2868',\n",
        " 'b2508,b2867',\n",
        " 'b2508,b2866',\n",
        " 'b0199,b4013',\n",
        " 'b0199,b3939',\n",
        " 'b0197,b4013',\n",
        " 'b0197,b3939',\n",
        " 'b0198,b4013',\n",
        " 'b0198,b3939',\n",
        " 'b4019,b3829',\n",
        " 'b3829,b4019',\n",
        " 'b0765,b2424',\n",
        " 'b0765,b2423',\n",
        " 'b0765,b2422',\n",
        " 'b0763,b2424',\n",
        " 'b0763,b2423',\n",
        " 'b0763,b2422',\n",
        " 'b2424,b0765',\n",
        " 'b2424,b0763',\n",
        " 'b2424,b0764',\n",
        " 'b2423,b0765',\n",
        " 'b2423,b0763',\n",
        " 'b2423,b0764',\n",
        " 'b2422,b0765',\n",
        " 'b2422,b0763',\n",
        " 'b2422,b0764',\n",
        " 'b0764,b2424',\n",
        " 'b0764,b2423',\n",
        " 'b0764,b2422',\n",
        " 'b0134,b3258',\n",
        " 'b0931,b2574',\n",
        " 'b0931,b0109',\n",
        " 'b0931,b0750',\n",
        " 'b2518,b0474',\n",
        " 'b0109,b0931',\n",
        " 'b0133,b3258',\n",
        " 'b3258,b0131',\n",
        " 'b3258,b0134',\n",
        " 'b3258,b0133',\n",
        " 'b1378,b3924',\n",
        " 'b1207,b0474',\n",
        " 'b1207,b4094',\n",
        " 'b1692,b3281',\n",
        " 'b0750,b0931',\n",
        " 'b4094,b0474',\n",
        " 'b4094,b1207',\n",
        " 'b1680,b2529',\n",
        " 'b1680,b2528',\n",
        " 'b1679,b2529',\n",
        " 'b1679,b2528',\n",
        " 'b1681,b2529',\n",
        " 'b1681,b2528',\n",
        " 'b1682,b2529',\n",
        " 'b1682,b2528',\n",
        " 'b1683,b2529',\n",
        " 'b1683,b2528',\n",
        " 'b1684,b2529',\n",
        " 'b1684,b2528',\n",
        " 'b3281,b1692',\n",
        " 'b0388,b3390',\n",
        " 'b3390,b0388',\n",
        " 'b3939,b0199',\n",
        " 'b3939,b0197',\n",
        " 'b3939,b0198',\n",
        " 'b2935,b2465',\n",
        " 'b2465,b2935',\n",
        " 'b2827,b1238',\n",
        " 'b0171,b0910']"
       ]
      }
     ],
     "prompt_number": 29
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}