Figure2-double_mutant_binding_validation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "informal-luxury",
   "metadata": {},
   "source": [
    "### Import libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "advanced-incident",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib\n",
    "font = {'weight' : 'normal',\n",
    "        'size'   : 12}\n",
    "\n",
    "matplotlib.rc('font', **font)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "friendly-telling",
   "metadata": {},
   "source": [
    "### Load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "fifth-playing",
   "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>Mutant</th>\n",
       "      <th>Expression_rep1</th>\n",
       "      <th>Expression_rep2</th>\n",
       "      <th>Binding_rep1</th>\n",
       "      <th>Binding_rep2</th>\n",
       "      <th>TLMutation</th>\n",
       "      <th>TL_percent</th>\n",
       "      <th>EVMutation</th>\n",
       "      <th>EV_percent</th>\n",
       "      <th>DeepSeq</th>\n",
       "      <th>DeepSeq_percent</th>\n",
       "      <th>Class</th>\n",
       "      <th>Color</th>\n",
       "      <th>TL_fold0</th>\n",
       "      <th>TL_fold1</th>\n",
       "      <th>TL_fold2</th>\n",
       "      <th>TL_fold3</th>\n",
       "      <th>TL_fold4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>WT</td>\n",
       "      <td>1.156660</td>\n",
       "      <td>0.843340</td>\n",
       "      <td>1.023075</td>\n",
       "      <td>0.976925</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WT</td>\n",
       "      <td>grey</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>F28D; A46W</td>\n",
       "      <td>0.745019</td>\n",
       "      <td>0.763487</td>\n",
       "      <td>0.023874</td>\n",
       "      <td>0.105803</td>\n",
       "      <td>-18.076826</td>\n",
       "      <td>0.999662</td>\n",
       "      <td>-17.960366</td>\n",
       "      <td>0.995714</td>\n",
       "      <td>-28.863635</td>\n",
       "      <td>0.986305</td>\n",
       "      <td>neg_control</td>\n",
       "      <td>crimson</td>\n",
       "      <td>-15.786639</td>\n",
       "      <td>-18.076826</td>\n",
       "      <td>-18.076826</td>\n",
       "      <td>-18.101686</td>\n",
       "      <td>-15.824563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Y50P; W349P</td>\n",
       "      <td>0.997041</td>\n",
       "      <td>0.927166</td>\n",
       "      <td>0.054720</td>\n",
       "      <td>0.202464</td>\n",
       "      <td>-17.016798</td>\n",
       "      <td>0.998548</td>\n",
       "      <td>-16.943444</td>\n",
       "      <td>0.986788</td>\n",
       "      <td>-21.973219</td>\n",
       "      <td>0.892830</td>\n",
       "      <td>neg_control</td>\n",
       "      <td>crimson</td>\n",
       "      <td>-10.636222</td>\n",
       "      <td>-11.440193</td>\n",
       "      <td>-10.694138</td>\n",
       "      <td>-13.658496</td>\n",
       "      <td>-11.440193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>E75K; N394D</td>\n",
       "      <td>1.057647</td>\n",
       "      <td>0.843297</td>\n",
       "      <td>1.157251</td>\n",
       "      <td>1.211598</td>\n",
       "      <td>3.339824</td>\n",
       "      <td>0.000493</td>\n",
       "      <td>-1.900263</td>\n",
       "      <td>0.028570</td>\n",
       "      <td>-0.100751</td>\n",
       "      <td>0.013544</td>\n",
       "      <td>top1</td>\n",
       "      <td>royalblue</td>\n",
       "      <td>0.388158</td>\n",
       "      <td>-0.595151</td>\n",
       "      <td>0.302469</td>\n",
       "      <td>-0.615753</td>\n",
       "      <td>-0.615757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>D67A;A387N</td>\n",
       "      <td>0.992135</td>\n",
       "      <td>0.925720</td>\n",
       "      <td>1.077320</td>\n",
       "      <td>0.967616</td>\n",
       "      <td>5.997397</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>6.489677</td>\n",
       "      <td>0.000003</td>\n",
       "      <td>5.860262</td>\n",
       "      <td>0.000092</td>\n",
       "      <td>top1</td>\n",
       "      <td>royalblue</td>\n",
       "      <td>2.932764</td>\n",
       "      <td>2.821391</td>\n",
       "      <td>2.733569</td>\n",
       "      <td>2.545163</td>\n",
       "      <td>2.654022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>N90D;R514K</td>\n",
       "      <td>0.958774</td>\n",
       "      <td>0.944211</td>\n",
       "      <td>1.669795</td>\n",
       "      <td>1.490177</td>\n",
       "      <td>5.032539</td>\n",
       "      <td>0.000025</td>\n",
       "      <td>-5.387709</td>\n",
       "      <td>0.149803</td>\n",
       "      <td>-5.154831</td>\n",
       "      <td>0.124252</td>\n",
       "      <td>top1</td>\n",
       "      <td>royalblue</td>\n",
       "      <td>-1.795245</td>\n",
       "      <td>-3.354939</td>\n",
       "      <td>2.281159</td>\n",
       "      <td>-3.402038</td>\n",
       "      <td>-3.377958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>A387N; S511Q</td>\n",
       "      <td>1.058588</td>\n",
       "      <td>0.834387</td>\n",
       "      <td>1.019664</td>\n",
       "      <td>1.020921</td>\n",
       "      <td>5.586625</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>-2.930621</td>\n",
       "      <td>0.049975</td>\n",
       "      <td>-6.103829</td>\n",
       "      <td>0.161441</td>\n",
       "      <td>top1</td>\n",
       "      <td>royalblue</td>\n",
       "      <td>-0.483490</td>\n",
       "      <td>-5.873912</td>\n",
       "      <td>-0.483490</td>\n",
       "      <td>-5.873912</td>\n",
       "      <td>-5.873912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>N394D; S511Q</td>\n",
       "      <td>1.099153</td>\n",
       "      <td>1.022185</td>\n",
       "      <td>1.026274</td>\n",
       "      <td>0.990713</td>\n",
       "      <td>5.383255</td>\n",
       "      <td>0.000012</td>\n",
       "      <td>-5.241368</td>\n",
       "      <td>0.141629</td>\n",
       "      <td>-7.616584</td>\n",
       "      <td>0.228458</td>\n",
       "      <td>top1</td>\n",
       "      <td>royalblue</td>\n",
       "      <td>-0.736253</td>\n",
       "      <td>-6.383886</td>\n",
       "      <td>-0.736253</td>\n",
       "      <td>-6.383886</td>\n",
       "      <td>-6.383886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>N61K; N330K</td>\n",
       "      <td>1.086917</td>\n",
       "      <td>0.983730</td>\n",
       "      <td>1.717869</td>\n",
       "      <td>1.893085</td>\n",
       "      <td>1.791659</td>\n",
       "      <td>0.005175</td>\n",
       "      <td>0.437857</td>\n",
       "      <td>0.004052</td>\n",
       "      <td>0.642944</td>\n",
       "      <td>0.008294</td>\n",
       "      <td>top1</td>\n",
       "      <td>royalblue</td>\n",
       "      <td>1.083437</td>\n",
       "      <td>-0.598765</td>\n",
       "      <td>1.069638</td>\n",
       "      <td>-0.598765</td>\n",
       "      <td>-0.598765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>L91P; N330Y</td>\n",
       "      <td>1.249711</td>\n",
       "      <td>1.138712</td>\n",
       "      <td>2.399121</td>\n",
       "      <td>2.881767</td>\n",
       "      <td>2.001828</td>\n",
       "      <td>0.004014</td>\n",
       "      <td>-2.660733</td>\n",
       "      <td>0.043210</td>\n",
       "      <td>-0.472655</td>\n",
       "      <td>0.016925</td>\n",
       "      <td>top1</td>\n",
       "      <td>royalblue</td>\n",
       "      <td>2.019087</td>\n",
       "      <td>-0.142242</td>\n",
       "      <td>2.019087</td>\n",
       "      <td>-0.142242</td>\n",
       "      <td>-0.118387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>N33D; R518G</td>\n",
       "      <td>0.636913</td>\n",
       "      <td>1.222184</td>\n",
       "      <td>1.426667</td>\n",
       "      <td>1.616898</td>\n",
       "      <td>3.117430</td>\n",
       "      <td>0.000719</td>\n",
       "      <td>-6.678014</td>\n",
       "      <td>0.238467</td>\n",
       "      <td>-9.234876</td>\n",
       "      <td>0.308273</td>\n",
       "      <td>top1</td>\n",
       "      <td>royalblue</td>\n",
       "      <td>-0.996600</td>\n",
       "      <td>-4.166220</td>\n",
       "      <td>2.116202</td>\n",
       "      <td>-4.166220</td>\n",
       "      <td>-4.193211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>L79V; N90D</td>\n",
       "      <td>0.697713</td>\n",
       "      <td>1.133847</td>\n",
       "      <td>3.046408</td>\n",
       "      <td>3.109714</td>\n",
       "      <td>1.490602</td>\n",
       "      <td>0.007549</td>\n",
       "      <td>-2.828556</td>\n",
       "      <td>0.047210</td>\n",
       "      <td>-0.643014</td>\n",
       "      <td>0.018716</td>\n",
       "      <td>top1</td>\n",
       "      <td>royalblue</td>\n",
       "      <td>-2.460257</td>\n",
       "      <td>1.678362</td>\n",
       "      <td>1.616147</td>\n",
       "      <td>1.631262</td>\n",
       "      <td>1.655343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>N90D; L351F</td>\n",
       "      <td>1.120653</td>\n",
       "      <td>0.884943</td>\n",
       "      <td>1.998368</td>\n",
       "      <td>1.951853</td>\n",
       "      <td>-0.552047</td>\n",
       "      <td>0.066049</td>\n",
       "      <td>-3.464747</td>\n",
       "      <td>0.065285</td>\n",
       "      <td>-4.794594</td>\n",
       "      <td>0.111416</td>\n",
       "      <td>add</td>\n",
       "      <td>gold</td>\n",
       "      <td>-2.796835</td>\n",
       "      <td>-1.975583</td>\n",
       "      <td>1.279569</td>\n",
       "      <td>-2.022682</td>\n",
       "      <td>-1.998602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>T27L; W69A</td>\n",
       "      <td>1.095821</td>\n",
       "      <td>0.951237</td>\n",
       "      <td>1.792123</td>\n",
       "      <td>1.812266</td>\n",
       "      <td>-4.216807</td>\n",
       "      <td>0.404266</td>\n",
       "      <td>-5.642978</td>\n",
       "      <td>0.164967</td>\n",
       "      <td>-7.201157</td>\n",
       "      <td>0.209267</td>\n",
       "      <td>add</td>\n",
       "      <td>gold</td>\n",
       "      <td>-4.109629</td>\n",
       "      <td>-5.009378</td>\n",
       "      <td>-4.091780</td>\n",
       "      <td>-5.757405</td>\n",
       "      <td>-4.194835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>L79P; R518G</td>\n",
       "      <td>0.921781</td>\n",
       "      <td>0.967212</td>\n",
       "      <td>1.928623</td>\n",
       "      <td>1.774617</td>\n",
       "      <td>-0.963481</td>\n",
       "      <td>0.091497</td>\n",
       "      <td>-10.383958</td>\n",
       "      <td>0.579821</td>\n",
       "      <td>-13.594620</td>\n",
       "      <td>0.543085</td>\n",
       "      <td>add</td>\n",
       "      <td>gold</td>\n",
       "      <td>-1.964709</td>\n",
       "      <td>-8.274123</td>\n",
       "      <td>-1.964709</td>\n",
       "      <td>-8.274123</td>\n",
       "      <td>-8.274123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Q42L; E75R</td>\n",
       "      <td>1.067247</td>\n",
       "      <td>1.115757</td>\n",
       "      <td>2.162817</td>\n",
       "      <td>2.092630</td>\n",
       "      <td>-1.168311</td>\n",
       "      <td>0.106192</td>\n",
       "      <td>-5.198427</td>\n",
       "      <td>0.139030</td>\n",
       "      <td>-3.719715</td>\n",
       "      <td>0.077704</td>\n",
       "      <td>add</td>\n",
       "      <td>gold</td>\n",
       "      <td>-1.043873</td>\n",
       "      <td>-2.254479</td>\n",
       "      <td>-1.290997</td>\n",
       "      <td>-1.022163</td>\n",
       "      <td>-1.047560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>T27Y; L79T</td>\n",
       "      <td>0.812693</td>\n",
       "      <td>1.125428</td>\n",
       "      <td>2.427530</td>\n",
       "      <td>2.533880</td>\n",
       "      <td>-1.567672</td>\n",
       "      <td>0.138461</td>\n",
       "      <td>-4.362677</td>\n",
       "      <td>0.098636</td>\n",
       "      <td>-0.868901</td>\n",
       "      <td>0.021295</td>\n",
       "      <td>v2.4</td>\n",
       "      <td>green</td>\n",
       "      <td>-1.566906</td>\n",
       "      <td>-1.565011</td>\n",
       "      <td>-2.739032</td>\n",
       "      <td>-1.555588</td>\n",
       "      <td>-1.555588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>T27Y; N330Y</td>\n",
       "      <td>0.702773</td>\n",
       "      <td>1.053403</td>\n",
       "      <td>2.281702</td>\n",
       "      <td>2.681948</td>\n",
       "      <td>0.175096</td>\n",
       "      <td>0.031476</td>\n",
       "      <td>-6.812914</td>\n",
       "      <td>0.249163</td>\n",
       "      <td>-4.560345</td>\n",
       "      <td>0.103595</td>\n",
       "      <td>v2.4</td>\n",
       "      <td>green</td>\n",
       "      <td>-0.825086</td>\n",
       "      <td>-2.491593</td>\n",
       "      <td>-0.813767</td>\n",
       "      <td>-2.482170</td>\n",
       "      <td>-2.482170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>L79T; N330Y</td>\n",
       "      <td>0.959579</td>\n",
       "      <td>1.000268</td>\n",
       "      <td>2.278992</td>\n",
       "      <td>2.558608</td>\n",
       "      <td>-0.175264</td>\n",
       "      <td>0.046738</td>\n",
       "      <td>-5.580385</td>\n",
       "      <td>0.161265</td>\n",
       "      <td>-3.766773</td>\n",
       "      <td>0.079031</td>\n",
       "      <td>v2.4</td>\n",
       "      <td>green</td>\n",
       "      <td>-1.147492</td>\n",
       "      <td>-2.815894</td>\n",
       "      <td>-2.330936</td>\n",
       "      <td>-2.815894</td>\n",
       "      <td>-2.815894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>v2.4</td>\n",
       "      <td>1.060865</td>\n",
       "      <td>1.189972</td>\n",
       "      <td>3.161481</td>\n",
       "      <td>3.202987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>green</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>T27Y</td>\n",
       "      <td>1.160444</td>\n",
       "      <td>0.996978</td>\n",
       "      <td>1.826368</td>\n",
       "      <td>1.837353</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>green</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>L79T</td>\n",
       "      <td>0.769638</td>\n",
       "      <td>1.037820</td>\n",
       "      <td>2.073510</td>\n",
       "      <td>1.790932</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>green</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>N330Y</td>\n",
       "      <td>1.002080</td>\n",
       "      <td>1.010674</td>\n",
       "      <td>1.948252</td>\n",
       "      <td>1.939575</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>green</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Mutant  Expression_rep1  Expression_rep2  Binding_rep1  \\\n",
       "0             WT         1.156660         0.843340      1.023075   \n",
       "1     F28D; A46W         0.745019         0.763487      0.023874   \n",
       "2    Y50P; W349P         0.997041         0.927166      0.054720   \n",
       "3    E75K; N394D         1.057647         0.843297      1.157251   \n",
       "4     D67A;A387N         0.992135         0.925720      1.077320   \n",
       "5     N90D;R514K         0.958774         0.944211      1.669795   \n",
       "6   A387N; S511Q         1.058588         0.834387      1.019664   \n",
       "7   N394D; S511Q         1.099153         1.022185      1.026274   \n",
       "8    N61K; N330K         1.086917         0.983730      1.717869   \n",
       "9    L91P; N330Y         1.249711         1.138712      2.399121   \n",
       "10   N33D; R518G         0.636913         1.222184      1.426667   \n",
       "11    L79V; N90D         0.697713         1.133847      3.046408   \n",
       "12   N90D; L351F         1.120653         0.884943      1.998368   \n",
       "13    T27L; W69A         1.095821         0.951237      1.792123   \n",
       "14   L79P; R518G         0.921781         0.967212      1.928623   \n",
       "15    Q42L; E75R         1.067247         1.115757      2.162817   \n",
       "16    T27Y; L79T         0.812693         1.125428      2.427530   \n",
       "17   T27Y; N330Y         0.702773         1.053403      2.281702   \n",
       "18   L79T; N330Y         0.959579         1.000268      2.278992   \n",
       "19          v2.4         1.060865         1.189972      3.161481   \n",
       "20          T27Y         1.160444         0.996978      1.826368   \n",
       "21          L79T         0.769638         1.037820      2.073510   \n",
       "22         N330Y         1.002080         1.010674      1.948252   \n",
       "\n",
       "    Binding_rep2  TLMutation  TL_percent  EVMutation  EV_percent    DeepSeq  \\\n",
       "0       0.976925         NaN         NaN         NaN         NaN        NaN   \n",
       "1       0.105803  -18.076826    0.999662  -17.960366    0.995714 -28.863635   \n",
       "2       0.202464  -17.016798    0.998548  -16.943444    0.986788 -21.973219   \n",
       "3       1.211598    3.339824    0.000493   -1.900263    0.028570  -0.100751   \n",
       "4       0.967616    5.997397    0.000002    6.489677    0.000003   5.860262   \n",
       "5       1.490177    5.032539    0.000025   -5.387709    0.149803  -5.154831   \n",
       "6       1.020921    5.586625    0.000007   -2.930621    0.049975  -6.103829   \n",
       "7       0.990713    5.383255    0.000012   -5.241368    0.141629  -7.616584   \n",
       "8       1.893085    1.791659    0.005175    0.437857    0.004052   0.642944   \n",
       "9       2.881767    2.001828    0.004014   -2.660733    0.043210  -0.472655   \n",
       "10      1.616898    3.117430    0.000719   -6.678014    0.238467  -9.234876   \n",
       "11      3.109714    1.490602    0.007549   -2.828556    0.047210  -0.643014   \n",
       "12      1.951853   -0.552047    0.066049   -3.464747    0.065285  -4.794594   \n",
       "13      1.812266   -4.216807    0.404266   -5.642978    0.164967  -7.201157   \n",
       "14      1.774617   -0.963481    0.091497  -10.383958    0.579821 -13.594620   \n",
       "15      2.092630   -1.168311    0.106192   -5.198427    0.139030  -3.719715   \n",
       "16      2.533880   -1.567672    0.138461   -4.362677    0.098636  -0.868901   \n",
       "17      2.681948    0.175096    0.031476   -6.812914    0.249163  -4.560345   \n",
       "18      2.558608   -0.175264    0.046738   -5.580385    0.161265  -3.766773   \n",
       "19      3.202987         NaN         NaN         NaN         NaN        NaN   \n",
       "20      1.837353         NaN         NaN         NaN         NaN        NaN   \n",
       "21      1.790932         NaN         NaN         NaN         NaN        NaN   \n",
       "22      1.939575         NaN         NaN         NaN         NaN        NaN   \n",
       "\n",
       "    DeepSeq_percent        Class      Color   TL_fold0   TL_fold1   TL_fold2  \\\n",
       "0               NaN           WT       grey        NaN        NaN        NaN   \n",
       "1          0.986305  neg_control    crimson -15.786639 -18.076826 -18.076826   \n",
       "2          0.892830  neg_control    crimson -10.636222 -11.440193 -10.694138   \n",
       "3          0.013544         top1  royalblue   0.388158  -0.595151   0.302469   \n",
       "4          0.000092         top1  royalblue   2.932764   2.821391   2.733569   \n",
       "5          0.124252         top1  royalblue  -1.795245  -3.354939   2.281159   \n",
       "6          0.161441         top1  royalblue  -0.483490  -5.873912  -0.483490   \n",
       "7          0.228458         top1  royalblue  -0.736253  -6.383886  -0.736253   \n",
       "8          0.008294         top1  royalblue   1.083437  -0.598765   1.069638   \n",
       "9          0.016925         top1  royalblue   2.019087  -0.142242   2.019087   \n",
       "10         0.308273         top1  royalblue  -0.996600  -4.166220   2.116202   \n",
       "11         0.018716         top1  royalblue  -2.460257   1.678362   1.616147   \n",
       "12         0.111416          add       gold  -2.796835  -1.975583   1.279569   \n",
       "13         0.209267          add       gold  -4.109629  -5.009378  -4.091780   \n",
       "14         0.543085          add       gold  -1.964709  -8.274123  -1.964709   \n",
       "15         0.077704          add       gold  -1.043873  -2.254479  -1.290997   \n",
       "16         0.021295         v2.4      green  -1.566906  -1.565011  -2.739032   \n",
       "17         0.103595         v2.4      green  -0.825086  -2.491593  -0.813767   \n",
       "18         0.079031         v2.4      green  -1.147492  -2.815894  -2.330936   \n",
       "19              NaN          NaN      green        NaN        NaN        NaN   \n",
       "20              NaN          NaN      green        NaN        NaN        NaN   \n",
       "21              NaN          NaN      green        NaN        NaN        NaN   \n",
       "22              NaN          NaN      green        NaN        NaN        NaN   \n",
       "\n",
       "     TL_fold3   TL_fold4  \n",
       "0         NaN        NaN  \n",
       "1  -18.101686 -15.824563  \n",
       "2  -13.658496 -11.440193  \n",
       "3   -0.615753  -0.615757  \n",
       "4    2.545163   2.654022  \n",
       "5   -3.402038  -3.377958  \n",
       "6   -5.873912  -5.873912  \n",
       "7   -6.383886  -6.383886  \n",
       "8   -0.598765  -0.598765  \n",
       "9   -0.142242  -0.118387  \n",
       "10  -4.166220  -4.193211  \n",
       "11   1.631262   1.655343  \n",
       "12  -2.022682  -1.998602  \n",
       "13  -5.757405  -4.194835  \n",
       "14  -8.274123  -8.274123  \n",
       "15  -1.022163  -1.047560  \n",
       "16  -1.555588  -1.555588  \n",
       "17  -2.482170  -2.482170  \n",
       "18  -2.815894  -2.815894  \n",
       "19        NaN        NaN  \n",
       "20        NaN        NaN  \n",
       "21        NaN        NaN  \n",
       "22        NaN        NaN  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(\"Figure2-3-S2-double_mutant_validation.csv\")\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "reverse-jones",
   "metadata": {},
   "source": [
    "### Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "destroyed-marsh",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bind_average = data[['Binding_rep1', 'Binding_rep2']].mean(axis=1)\n",
    "bind_range = np.abs(data['Binding_rep1'] - data['Binding_rep2'])\n",
    "\n",
    "plt.figure(figsize=(16,6))\n",
    "\n",
    "plt.bar(range(len(bind_average)), bind_average, yerr=bind_range, capsize=2, edgecolor='k',  color=data[\"Color\"])\n",
    "plt.xticks(range(len(bind_average)), data[\"Mutant\"], rotation=90)\n",
    "\n",
    "plt.ylim([0,4])\n",
    "plt.xlim([-0.7, 22.7])\n",
    "plt.grid(axis='y', linestyle=\":\")\n",
    "\n",
    "plt.plot([-1,30],[1,1], 'k--', linewidth=1.25)\n",
    "\n",
    "plt.xlabel(\"ACE2 variant\")\n",
    "plt.ylabel(\"Relataive Binding of RBS-sfGFP\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "functioning-china",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "affecting-transsexual",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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