{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Generate figures\n",
    "This notebook will generate all main and supplemental figures that are not already generated by notebook 4."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import sys\n",
    "import pickle\n",
    "\n",
    "import matplotlib as mpl\n",
    "import matplotlib.patches as mpatches\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.axes_grid1 import make_axes_locatable\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from scipy import stats\n",
    "import logomaker\n",
    "from pybedtools import BedTool\n",
    "from IPython.display import display\n",
    "\n",
    "sys.path.insert(0, \"utils\")\n",
    "from utils import fasta_seq_parse_manip, gkmsvm, modeling, plot_utils, predicted_occupancy, sequence_annotation_processing\n",
    "\n",
    "data_dir = os.path.join(\"Data\")\n",
    "seq_bins_dir = os.path.join(data_dir, \"ActivityBins\")\n",
    "models_dir = os.path.join(\"Models\", \"StrongEnhancerVsSilencer\")\n",
    "figures_dir = os.path.join(\"Figures\")\n",
    "all_seqs = fasta_seq_parse_manip.read_fasta(os.path.join(data_dir, \"library1And2.fasta\"))\n",
    "# Drop scrambled sequences\n",
    "all_seqs = all_seqs[~(all_seqs.index.str.contains(\"scr\"))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "plot_utils.set_manuscript_params()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load in all the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Mapping activity class to a color\n",
    "color_mapping = {\n",
    "    \"Silencer\": \"#e31a1c\",\n",
    "    \"Inactive\": \"#33a02c\",\n",
    "    \"Weak enhancer\": \"#a6cee3\",\n",
    "    \"Strong enhancer\": \"#1f78b4\",\n",
    "    np.nan: \"grey\"\n",
    "}\n",
    "color_mapping = pd.Series(color_mapping)\n",
    "\n",
    "# Sort order for the four activity bins\n",
    "class_sort_order = [\"Silencer\", \"Inactive\", \"Weak enhancer\", \"Strong enhancer\"]\n",
    "\n",
    "# MPRA measurements\n",
    "activity_df = pd.read_csv(os.path.join(data_dir, \"wildtypeMutantPolylinkerActivityAnnotated.txt\"), sep=\"\\t\", index_col=0)\n",
    "activity_df[\"group_name_WT\"] = sequence_annotation_processing.to_categorical(activity_df[\"group_name_WT\"])\n",
    "activity_df[\"group_name_MUT\"] = sequence_annotation_processing.to_categorical(activity_df[\"group_name_MUT\"])\n",
    "\n",
    "# TF occupancy metrics, also separate out the WT sequences\n",
    "occupancy_df = pd.read_csv(os.path.join(data_dir, \"predictedOccupancies.txt\"), sep=\"\\t\", index_col=0)\n",
    "wt_occupancy_df = occupancy_df[occupancy_df.index.str.contains(\"WT$\")].copy()\n",
    "wt_occupancy_df = sequence_annotation_processing.remove_mutations_from_seq_id(wt_occupancy_df)\n",
    "wt_occupancy_df = wt_occupancy_df.loc[activity_df.index]\n",
    "n_tfs = len(wt_occupancy_df.columns)\n",
    "\n",
    "# Entropy and related metrics, also separate out WT and MUT\n",
    "entropy_df = pd.read_csv(os.path.join(data_dir, \"entropyDiversityOccupancy.txt\"), sep=\"\\t\", index_col=0)\n",
    "wt_entropy_df = entropy_df[entropy_df.index.str.contains(\"WT$\")].copy()\n",
    "wt_entropy_df = sequence_annotation_processing.remove_mutations_from_seq_id(wt_entropy_df)\n",
    "wt_entropy_df = wt_entropy_df.loc[activity_df.index]\n",
    "\n",
    "mut_entropy_df = entropy_df[entropy_df.index.str.contains(\"MUT\")].copy()\n",
    "mut_entropy_df = sequence_annotation_processing.remove_mutations_from_seq_id(mut_entropy_df)\n",
    "mut_entropy_df = mut_entropy_df.loc[activity_df.index]\n",
    "\n",
    "# Occupancy logistic regression (need this to sort by feature importance)\n",
    "occ_clf = pickle.load(open(os.path.join(models_dir, \"logit_model.pkl\"), \"rb\"))\n",
    "\n",
    "# Axis ticks for Rho assay\n",
    "rho_ticks = np.arange(-10, 7, 2)\n",
    "\n",
    "# xaxis for ROC/PR curves\n",
    "modeling_xaxis = np.linspace(0, 1, 100)\n",
    "\n",
    "# Model performance metrics with a helper function\n",
    "def read_metrics(filename, input_dir=models_dir):\n",
    "    return pd.read_csv(os.path.join(input_dir, filename), sep=\"\\t\", header=None)\n",
    "\n",
    "# Cross-validated metrics\n",
    "svm_tpr_cv = read_metrics(\"svmTprCv.txt\")\n",
    "svm_prec_cv = read_metrics(\"svmPrecCv.txt\")\n",
    "crx_occ_tpr_cv = read_metrics(\"crxTprCv.txt\")\n",
    "crx_occ_prec_cv = read_metrics(\"crxPrecCv.txt\")\n",
    "entropy_tpr_cv = read_metrics(\"entropyTprCv.txt\")\n",
    "entropy_prec_cv = read_metrics(\"entropyPrecCv.txt\")\n",
    "occ_tpr_cv = read_metrics(\"occupancyTprCv.txt\")\n",
    "occ_prec_cv = read_metrics(\"occupancyPrecCv.txt\")\n",
    "\n",
    "# White 2013 test set\n",
    "white_svm_tpr = read_metrics(\"whiteSvmTpr.txt\").squeeze()\n",
    "white_svm_prec = read_metrics(\"whiteSvmPrec.txt\").squeeze()\n",
    "white_occ_tpr = read_metrics(\"whiteOccTpr.txt\").squeeze()\n",
    "white_occ_prec = read_metrics(\"whiteOccPrec.txt\").squeeze()\n",
    "\n",
    "# Random PWMs background\n",
    "random_occ_tprs = read_metrics(\"randomFeaturesMeanTprs.txt\")\n",
    "random_occ_precs = read_metrics(\"randomFeaturesMeanPrecs.txt\")\n",
    "\n",
    "# Strong enhancer vs. inactive for info content\n",
    "inactive_entropy_tpr_cv = read_metrics(\"entropyTprCv.txt\", input_dir=os.path.join(\"Models\", \"StrongEnhancerVsInactive\"))\n",
    "inactive_entropy_prec_cv = read_metrics(\"entropyPrecCv.txt\", input_dir=os.path.join(\"Models\", \"StrongEnhancerVsInactive\"))\n",
    "\n",
    "# PWMs\n",
    "pwms = predicted_occupancy.read_pwm_files(os.path.join(\"Data\", \"Downloaded\", \"Pwm\", \"photoreceptorAndEnrichedMotifs.meme\"))\n",
    "pwms = pwms.rename(lambda x: x.split(\"_\")[0])\n",
    "motif_len = pwms.apply(len)\n",
    "mu = 9\n",
    "ewms = pwms.apply(predicted_occupancy.ewm_from_letter_prob).apply(predicted_occupancy.ewm_to_dict)\n",
    "\n",
    "# Reverse compliment RAX for display purposes\n",
    "rax = pwms[\"RAX\"].copy()\n",
    "rax = rax[::-1].reset_index(drop=True)\n",
    "rax_rc = rax.copy()\n",
    "rax_rc[\"A\"] = rax[\"T\"]\n",
    "rax_rc[\"C\"] = rax[\"G\"]\n",
    "rax_rc[\"G\"] = rax[\"C\"]\n",
    "rax_rc[\"T\"] = rax[\"A\"]\n",
    "pwms[\"RAX\"] = rax_rc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Figure 1: Activity of putative cis-regulatory sequences with CRX motifs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Frequency of each activity bin in WT sequences:\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Silencer           0.173615\n",
       "Inactive           0.192491\n",
       "Weak enhancer      0.282099\n",
       "Strong enhancer    0.218005\n",
       "NaN                0.133790\n",
       "Name: group_name_WT, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Frequency of activity bins vs. CRX binding status:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\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>group_name_WT</th>\n",
       "      <th>Silencer</th>\n",
       "      <th>Inactive</th>\n",
       "      <th>Weak enhancer</th>\n",
       "      <th>Strong enhancer</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>crx_bound</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ATAC-seq</th>\n",
       "      <td>281</td>\n",
       "      <td>363</td>\n",
       "      <td>430</td>\n",
       "      <td>211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ChIP-seq</th>\n",
       "      <td>556</td>\n",
       "      <td>565</td>\n",
       "      <td>930</td>\n",
       "      <td>840</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "group_name_WT  Silencer  Inactive  Weak enhancer  Strong enhancer\n",
       "crx_bound                                                        \n",
       "ATAC-seq            281       363            430              211\n",
       "ChIP-seq            556       565            930              840"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ChIP-seq status is independent of if a sequence is inactive, Fisher's exact test p=2e-07, odds ratio=1.49\n",
      "ChIP-seq status is independent of if a sequence is inactive, Fisher's exact test p=1e-21, odds ratio=2.16\n"
     ]
    },
    {
     "data": {
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>group_name_WT</th>\n",
       "      <th>Silencer</th>\n",
       "      <th>Inactive</th>\n",
       "      <th>Weak enhancer</th>\n",
       "      <th>Strong enhancer</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>crx_bound</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ATAC-seq</th>\n",
       "      <td>0.218677</td>\n",
       "      <td>0.282490</td>\n",
       "      <td>0.334630</td>\n",
       "      <td>0.164202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ChIP-seq</th>\n",
       "      <td>0.192321</td>\n",
       "      <td>0.195434</td>\n",
       "      <td>0.321688</td>\n",
       "      <td>0.290557</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "group_name_WT  Silencer  Inactive  Weak enhancer  Strong enhancer\n",
       "crx_bound                                                        \n",
       "ATAC-seq       0.218677  0.282490       0.334630         0.164202\n",
       "ChIP-seq       0.192321  0.195434       0.321688         0.290557"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted CRX occupancies:\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>group_name_WT</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Silencer</th>\n",
       "      <td>837.0</td>\n",
       "      <td>2.822068</td>\n",
       "      <td>1.474613</td>\n",
       "      <td>0.013521</td>\n",
       "      <td>1.598510</td>\n",
       "      <td>2.724195</td>\n",
       "      <td>3.916786</td>\n",
       "      <td>8.028408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Inactive</th>\n",
       "      <td>928.0</td>\n",
       "      <td>2.232489</td>\n",
       "      <td>1.342345</td>\n",
       "      <td>0.001052</td>\n",
       "      <td>1.173444</td>\n",
       "      <td>2.048457</td>\n",
       "      <td>3.136282</td>\n",
       "      <td>6.759976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Weak enhancer</th>\n",
       "      <td>1360.0</td>\n",
       "      <td>2.216861</td>\n",
       "      <td>1.220496</td>\n",
       "      <td>0.000385</td>\n",
       "      <td>1.235126</td>\n",
       "      <td>2.113810</td>\n",
       "      <td>2.988673</td>\n",
       "      <td>7.801177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Strong enhancer</th>\n",
       "      <td>1051.0</td>\n",
       "      <td>2.534010</td>\n",
       "      <td>1.169460</td>\n",
       "      <td>0.003694</td>\n",
       "      <td>1.616414</td>\n",
       "      <td>2.490314</td>\n",
       "      <td>3.285321</td>\n",
       "      <td>7.368500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  count      mean       std       min       25%       50%  \\\n",
       "group_name_WT                                                               \n",
       "Silencer          837.0  2.822068  1.474613  0.013521  1.598510  2.724195   \n",
       "Inactive          928.0  2.232489  1.342345  0.001052  1.173444  2.048457   \n",
       "Weak enhancer    1360.0  2.216861  1.220496  0.000385  1.235126  2.113810   \n",
       "Strong enhancer  1051.0  2.534010  1.169460  0.003694  1.616414  2.490314   \n",
       "\n",
       "                      75%       max  \n",
       "group_name_WT                        \n",
       "Silencer         3.916786  8.028408  \n",
       "Inactive         3.136282  6.759976  \n",
       "Weak enhancer    2.988673  7.801177  \n",
       "Strong enhancer  3.285321  7.368500  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Strong enhancers and inactive sequences have the same CRX occupancy, Mann-Whitney U test p = 6e-10 U = 566045.00\n",
      "Silencers and inactive sequences have the same CRX occupancy, Mann-Whitney U test p = 6e-17, U = 477843.00\n"
     ]
    }
   ],
   "source": [
    "# Can only plot points that were detected in DNA\n",
    "activity_measured_wt_df = activity_df[activity_df[\"expression_log2_WT\"].notna()]\n",
    "print(\"Frequency of each activity bin in WT sequences:\")\n",
    "display(activity_measured_wt_df[\"group_name_WT\"].value_counts(normalize=True, dropna=False, sort=False))\n",
    "\n",
    "# Count frequency of activity bins for CRX bound/unbound\n",
    "crx_bound_grouper = activity_df.groupby(\"crx_bound\")\n",
    "chip_activity_bin_freqs = crx_bound_grouper[\"group_name_WT\"].value_counts().unstack()\n",
    "chip_activity_bin_freqs = chip_activity_bin_freqs[class_sort_order].rename(index=lambda x: \"ChIP-seq\" if x else \"ATAC-seq\")\n",
    "\n",
    "# Different ways to format group names\n",
    "chip_group_names_with_n = [f\"{i}\\nn={j.sum()}\" for i, j in chip_activity_bin_freqs.iterrows()]\n",
    "chip_group_names_with_n_oneline = [\" \".join(i.split()) for i in chip_group_names_with_n]\n",
    "chip_group_names = chip_activity_bin_freqs.index.values\n",
    "chip_group_count = [j.sum() for i, j in chip_activity_bin_freqs.iterrows()]\n",
    "\n",
    "# Display the data behind Fig 1b\n",
    "print(\"Frequency of activity bins vs. CRX binding status:\")\n",
    "display(chip_activity_bin_freqs)\n",
    "\n",
    "# Test if CRX binding and inactive status is independent\n",
    "chip_group_inactive_counts = crx_bound_grouper[\"group_name_WT\"].apply(lambda x: (x == \"Inactive\").value_counts()).unstack()\n",
    "oddsratio, pval = stats.fisher_exact(chip_group_inactive_counts)\n",
    "# Take inverse of odds ratio to match language of manuscript and be more intuitive to the reader\n",
    "print(f\"ChIP-seq status is independent of if a sequence is inactive, Fisher's exact test p={pval:.0e}, odds ratio={1/oddsratio:.2f}\")\n",
    "\n",
    "# Same for strong enhancer\n",
    "chip_group_inactive_counts = crx_bound_grouper[\"group_name_WT\"].apply(lambda x: (x == \"Strong enhancer\").value_counts()).unstack()\n",
    "oddsratio, pval = stats.fisher_exact(chip_group_inactive_counts)\n",
    "# Take inverse of odds ratio to match language of manuscript and be more intuitive to the reader\n",
    "print(f\"ChIP-seq status is independent of if a sequence is inactive, Fisher's exact test p={pval:.0e}, odds ratio={oddsratio:.2f}\")\n",
    "\n",
    "# Row-normalize the counts\n",
    "chip_activity_bin_freqs = chip_activity_bin_freqs.div(chip_activity_bin_freqs.sum(axis=1), axis=0)\n",
    "display(chip_activity_bin_freqs)\n",
    "\n",
    "# Setup for some downstream stuff\n",
    "wt_activity_grouper = activity_df.groupby(\"group_name_WT\")\n",
    "wt_activity_names_oneline = [\"Silencer\", \"Inactive\", \"Weak enh.\", \"Strong enh.\"]\n",
    "wt_activity_count = [len(j) for i, j in wt_activity_grouper]\n",
    "\n",
    "# Predicted CRX occupancy vs. WT group\n",
    "wt_occupancy_grouper = wt_occupancy_df.groupby(activity_df[\"group_name_WT\"])\n",
    "wt_occupancy_grouper_crx = wt_occupancy_grouper[\"CRX\"]\n",
    "print(\"Predicted CRX occupancies:\")\n",
    "display(wt_occupancy_grouper_crx.describe())\n",
    "\n",
    "# Statistics for differences in CRX occupancy between groups\n",
    "ustat, pval = stats.mannwhitneyu(wt_occupancy_grouper_crx.get_group(\"Strong enhancer\"), wt_occupancy_grouper_crx.get_group(\"Inactive\"), alternative=\"two-sided\")\n",
    "print(f\"Strong enhancers and inactive sequences have the same CRX occupancy, Mann-Whitney U test p = {pval:.0e} U = {ustat:.2f}\")\n",
    "ustat, pval = stats.mannwhitneyu(wt_occupancy_grouper_crx.get_group(\"Silencer\"), wt_occupancy_grouper_crx.get_group(\"Inactive\"), alternative=\"two-sided\")\n",
    "print(f\"Silencers and inactive sequences have the same CRX occupancy, Mann-Whitney U test p = {pval:.0e}, U = {ustat:.2f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x576 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Setup the figure\n",
    "gs_kw = dict(width_ratios=[1, 3])\n",
    "fig, ax_list = plt.subplots(nrows=2, ncols=2, figsize=(6, 8), gridspec_kw=gs_kw)\n",
    "gs = ax_list[0, 0].get_gridspec()\n",
    "for ax in ax_list[0, :]:\n",
    "    ax.remove()\n",
    "    \n",
    "axbig = fig.add_subplot(gs[0, :])\n",
    "ax = axbig\n",
    "\n",
    "# 1a: Volcano plot\n",
    "fig = plot_utils.volcano_plot(activity_measured_wt_df, \"expression_log2_WT\", \"expression_qvalue_WT\",\n",
    "                             activity_measured_wt_df[\"plot_color_WT\"], xaxis_label=\"log2 Enhancer Activity/Rho\",\n",
    "                             yaxis_label=\"-log10 FDR\", xline=-np.log10(0.05), yline=[-1, 1],\n",
    "                             xticks=rho_ticks[1:], figax=(fig, ax))\n",
    "ax.set_yticks(np.arange(5))\n",
    "plot_utils.add_letter(ax, -0.125, 1, \"a\")\n",
    "\n",
    "# 1b: CRX binding status vs. activity classes\n",
    "ax = ax_list[1, 0]\n",
    "fig = plot_utils.stacked_bar_plots(chip_activity_bin_freqs, \"Fraction of group\", chip_group_names, color_mapping, figax=(fig, ax), vert=True)\n",
    "ax.set_yticks(np.linspace(0, 1, 6))\n",
    "plot_utils.rotate_ticks(ax.get_xticklabels())    \n",
    "\n",
    "# Add ticks above to show the n\n",
    "ax_twin = ax.twiny()\n",
    "ax_twin.set_xticks(ax.get_xticks())\n",
    "ax_twin.set_xlim(ax.get_xlim())\n",
    "ax_twin.set_xticklabels(chip_group_count, fontsize=10, rotation=45)\n",
    "plot_utils.add_letter(ax, -0.7, 1.03, \"b\")\n",
    "\n",
    "# 1c: Predicted CRX occupancy of different groups\n",
    "ax = ax_list[1, 1]\n",
    "fig = plot_utils.violin_plot_groupby(wt_occupancy_grouper_crx, \"Predicted CRX occupancy\", class_names=wt_activity_names_oneline, class_colors=color_mapping, figax=(fig, ax))\n",
    "ax.set_yticks(np.linspace(0, 8, 5))\n",
    "plot_utils.rotate_ticks(ax.get_xticklabels())\n",
    "\n",
    "# Add ticks above to show the n\n",
    "ax_twin = ax.twiny()\n",
    "ax_twin.set_xticks(ax.get_xticks())\n",
    "ax_twin.set_xlim(ax.get_xlim())\n",
    "ax_twin.set_xticklabels(wt_activity_count, fontsize=10, rotation=45)\n",
    "plot_utils.add_letter(ax, -0.2, 1.03, \"c\")\n",
    "\n",
    "plot_utils.save_fig(fig, os.path.join(figures_dir, \"figure1\"), timestamp=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Figure 2: Strong enhancers contain a diverse array of motifs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Panels a and b\n",
    "Also Supplemental Figure 3: Precision recall curve for strong enhancer vs. silencer classifiers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model metrics:\n",
      "SVM\tAUROC=0.781+/-0.013\tAUPR=0.812+/-0.020\n",
      "8 TFs\tAUROC=0.698+/-0.036\tAUPR=0.745+/-0.032\n",
      "CRX\tAUROC=0.548+/-0.023\tAUPR=0.571+/-0.020\n",
      "Total predicted occupancy of all TFs in each group:\n"
     ]
    },
    {
     "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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>group_name_WT</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Silencer</th>\n",
       "      <td>837.0</td>\n",
       "      <td>3.588419</td>\n",
       "      <td>1.848387</td>\n",
       "      <td>0.067069</td>\n",
       "      <td>2.167386</td>\n",
       "      <td>3.408131</td>\n",
       "      <td>4.845272</td>\n",
       "      <td>11.848887</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Inactive</th>\n",
       "      <td>928.0</td>\n",
       "      <td>3.005903</td>\n",
       "      <td>1.690368</td>\n",
       "      <td>0.034470</td>\n",
       "      <td>1.777625</td>\n",
       "      <td>2.810142</td>\n",
       "      <td>3.968906</td>\n",
       "      <td>12.011682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Weak enhancer</th>\n",
       "      <td>1360.0</td>\n",
       "      <td>3.068334</td>\n",
       "      <td>1.582532</td>\n",
       "      <td>0.010029</td>\n",
       "      <td>1.935493</td>\n",
       "      <td>2.921969</td>\n",
       "      <td>4.031018</td>\n",
       "      <td>12.521734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Strong enhancer</th>\n",
       "      <td>1051.0</td>\n",
       "      <td>3.782727</td>\n",
       "      <td>1.622289</td>\n",
       "      <td>0.021160</td>\n",
       "      <td>2.577761</td>\n",
       "      <td>3.664645</td>\n",
       "      <td>4.762179</td>\n",
       "      <td>10.185356</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  count      mean       std       min       25%       50%  \\\n",
       "group_name_WT                                                               \n",
       "Silencer          837.0  3.588419  1.848387  0.067069  2.167386  3.408131   \n",
       "Inactive          928.0  3.005903  1.690368  0.034470  1.777625  2.810142   \n",
       "Weak enhancer    1360.0  3.068334  1.582532  0.010029  1.935493  2.921969   \n",
       "Strong enhancer  1051.0  3.782727  1.622289  0.021160  2.577761  3.664645   \n",
       "\n",
       "                      75%        max  \n",
       "group_name_WT                         \n",
       "Silencer         4.845272  11.848887  \n",
       "Inactive         3.968906  12.011682  \n",
       "Weak enhancer    4.031018  12.521734  \n",
       "Strong enhancer  4.762179  10.185356  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax_list = plot_utils.setup_multiplot(2, sharex=False, sharey=False)\n",
    "# Separate figure handle for the PR curves\n",
    "fig_pr, ax_pr = plt.subplots()\n",
    "\n",
    "# 2a and supplemental figure 3: ROC and PR curves with SVM, TF occupancies, CRX occupancy\n",
    "model_data = [ # (TPR, precision, name, color)\n",
    "    (svm_tpr_cv, svm_prec_cv, \"SVM\", \"black\"),\n",
    "    (occ_tpr_cv, occ_prec_cv, f\"{n_tfs} TFs\", \"#E69B04\"),\n",
    "    (crx_occ_tpr_cv, crx_occ_prec_cv, \"CRX\", \"#009980\")\n",
    "]\n",
    "\n",
    "model_tprs, model_precs, model_names, model_colors = zip(*model_data)\n",
    "prc_chance = activity_df[\"group_name_WT\"].str.contains(\"Strong\").sum() / activity_df[\"group_name_WT\"].str.contains(\"Strong|Silencer\").sum()\n",
    "\n",
    "# Generate figures\n",
    "_, model_aurocs, model_aurocs_std, model_auprs, model_auprs_std = plot_utils.roc_pr_curves(\n",
    "    modeling_xaxis, model_tprs, model_precs, model_names, model_colors=model_colors,\n",
    "    prc_chance=prc_chance, figax=([fig, fig_pr], [ax_list[0], ax_pr])\n",
    ")\n",
    "ax_list[0].set_xticks(np.linspace(0, 1, 6))\n",
    "plot_utils.add_letter(ax_list[0], -0.25, 1.03, \"a\")\n",
    "\n",
    "# Display model metrics\n",
    "print(\"Model metrics:\")\n",
    "for name, auroc, auroc_std, aupr, aupr_std in zip(model_names, model_aurocs, model_aurocs_std, model_auprs, model_auprs_std):\n",
    "    print(f\"{name}\\tAUROC={auroc:.3f}+/-{auroc_std:.3f}\\tAUPR={aupr:.3f}+/-{aupr_std:.3f}\")\n",
    "\n",
    "# Calculate total predicted occupancy of each class\n",
    "wt_entropy_grouper = wt_entropy_df.groupby(activity_df[\"group_name_WT\"])\n",
    "print(\"Total predicted occupancy of all TFs in each group:\")\n",
    "display(wt_entropy_grouper[\"total_occupancy\"].describe())\n",
    "\n",
    "# 2b: Total predicted occupancy of each class\n",
    "ax = ax_list[1]\n",
    "fig = plot_utils.violin_plot_groupby(wt_entropy_grouper[\"total_occupancy\"], \"Total predicted TF occupancy\", class_names=wt_activity_names_oneline, class_colors=color_mapping, figax=(fig, ax))\n",
    "plot_utils.rotate_ticks(ax.get_xticklabels())\n",
    "plot_utils.add_letter(ax, -0.25, 1.03, \"b\")\n",
    "\n",
    "# Add ticks above to show the n\n",
    "ax_twin = ax.twiny()\n",
    "ax_twin.set_xticks(ax.get_xticks())\n",
    "ax_twin.set_xlim(ax.get_xlim())\n",
    "ax_twin.set_xticklabels(wt_activity_count, fontsize=10, rotation=45)\n",
    "\n",
    "plot_utils.save_fig(fig, os.path.join(figures_dir, \"figure2ab\"), timestamp=False, tight_pad=0)\n",
    "plot_utils.save_fig(fig_pr, os.path.join(figures_dir, \"supplementalFigure3\"), timestamp=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Panel c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "in validate_matrix(): Row sums in df are not close to 1. Reormalizing rows...\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 11 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculate motif frequency in each class\n",
    "occupied_cutoff = 0.5\n",
    "motif_freq_df = wt_occupancy_grouper.apply(lambda x: (x > occupied_cutoff).sum() / len(x))\n",
    "# Sort by the feature importance in the logistic model\n",
    "feature_importance = occ_clf.coef_[0]\n",
    "feature_order = feature_importance.argsort()\n",
    "motif_freq_df = motif_freq_df.iloc[:, feature_order]\n",
    "\n",
    "# Make the fig\n",
    "fig, ax_list = plt.subplots(nrows=8, ncols=2, figsize=(6, 4), gridspec_kw=dict(width_ratios=[1, 2]))\n",
    "gs = ax_list[0, 0].get_gridspec()\n",
    "for ax in ax_list[:, 1]:\n",
    "    ax.remove()\n",
    "    \n",
    "axbig = fig.add_subplot(gs[:, 1])\n",
    "\n",
    "ax = axbig\n",
    "vmax = 0.25\n",
    "thresh = vmax / 2\n",
    "motif_freq_no_crx_df = motif_freq_df.drop(columns=\"CRX\")\n",
    "heatmap = ax.imshow(motif_freq_no_crx_df.T, aspect=\"auto\", vmin=0, vmax=vmax, cmap=\"Reds\")\n",
    "ax.set_xticks(np.arange(len(wt_activity_names_oneline)))\n",
    "ax.set_xticklabels(wt_activity_names_oneline, rotation=90)\n",
    "ax.set_yticks(np.arange(len(motif_freq_no_crx_df.columns)))\n",
    "ax.set_yticklabels(motif_freq_no_crx_df.columns)\n",
    "plot_utils.annotate_heatmap(ax, motif_freq_no_crx_df, thresh)\n",
    "\n",
    "# Add the logos\n",
    "for cax, tf in zip(ax_list[1:, 0], motif_freq_no_crx_df.columns):\n",
    "    pwm = logomaker.transform_matrix(pwms[tf], from_type=\"probability\", to_type=\"information\")\n",
    "    logomaker.Logo(pwm, ax=cax, color_scheme=\"colorblind_safe\", show_spines=False)\n",
    "    # Right-align the logos\n",
    "    cax.set_xlim(left=motif_len[tf] - motif_len.max() - 0.5)\n",
    "    cax.set_ylim(top=2)\n",
    "    cax.set_xticks([])\n",
    "    cax.set_yticks([])\n",
    "\n",
    "# Add a colorbar\n",
    "divider = make_axes_locatable(ax)\n",
    "cax = divider.append_axes(\"right\", size=\"5%\", pad=\"2%\")\n",
    "colorbar = fig.colorbar(heatmap, cax=cax, label=\"Frequency of motif\")\n",
    "ticks = cax.get_yticks()\n",
    "ticks = [f\"{i:.2f}\" for i in ticks]\n",
    "ticks[-1] = r\"$\\geq$\" + ticks[-1]\n",
    "cax.set_yticklabels(ticks)\n",
    "\n",
    "# Add CRX\n",
    "cax = divider.append_axes(\"top\", size=\"14%\", pad=\"2%\")\n",
    "heatmap = cax.imshow(motif_freq_df[\"CRX\"].to_frame().T, aspect=\"auto\", vmin=0, vmax=vmax, cmap=\"Reds\")\n",
    "cax.xaxis.tick_top()\n",
    "cax.set_xticks(ax.get_xticks())\n",
    "cax.set_xlim(ax.get_xlim())\n",
    "cax.set_xticklabels(wt_activity_count, fontsize=10, rotation=45)\n",
    "cax.set_yticks([0])\n",
    "cax.set_yticklabels([\"CRX\"])\n",
    "plot_utils.annotate_heatmap(cax, motif_freq_df[\"CRX\"].to_frame(), thresh)\n",
    "\n",
    "# Add CRX logo\n",
    "cax = ax_list[0, 0]\n",
    "pwm = logomaker.transform_matrix(pwms[\"CRX\"], from_type=\"probability\", to_type=\"information\")\n",
    "logomaker.Logo(pwm, ax=cax, color_scheme=\"colorblind_safe\", show_spines=False)\n",
    "# Right-align the logos\n",
    "cax.set_xlim(left=motif_len[tf] - motif_len.max() - 0.5)\n",
    "cax.set_ylim(top=2)\n",
    "cax.set_xticks([])\n",
    "cax.set_yticks([])\n",
    "\n",
    "plot_utils.add_letter(cax, 0, 1.03, \"c\")\n",
    "plot_utils.save_fig(fig, os.path.join(figures_dir, \"figure2c\"), timestamp=False, tight_pad=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Panels d-f"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>group_name_WT</th>\n",
       "      <th>Silencer</th>\n",
       "      <th>Inactive</th>\n",
       "      <th>Weak enhancer</th>\n",
       "      <th>Strong enhancer</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>binding_group</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>No binding</th>\n",
       "      <td>0.221493</td>\n",
       "      <td>0.286300</td>\n",
       "      <td>0.331419</td>\n",
       "      <td>0.160788</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CRX only</th>\n",
       "      <td>0.203553</td>\n",
       "      <td>0.222276</td>\n",
       "      <td>0.346615</td>\n",
       "      <td>0.227556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CRX+NRL</th>\n",
       "      <td>0.192560</td>\n",
       "      <td>0.115974</td>\n",
       "      <td>0.238512</td>\n",
       "      <td>0.452954</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CRX+MEF2D</th>\n",
       "      <td>0.145000</td>\n",
       "      <td>0.165000</td>\n",
       "      <td>0.280000</td>\n",
       "      <td>0.410000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All three</th>\n",
       "      <td>0.099338</td>\n",
       "      <td>0.105960</td>\n",
       "      <td>0.284768</td>\n",
       "      <td>0.509934</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "group_name_WT  Silencer  Inactive  Weak enhancer  Strong enhancer\n",
       "binding_group                                                    \n",
       "No binding     0.221493  0.286300       0.331419         0.160788\n",
       "CRX only       0.203553  0.222276       0.346615         0.227556\n",
       "CRX+NRL        0.192560  0.115974       0.238512         0.452954\n",
       "CRX+MEF2D      0.145000  0.165000       0.280000         0.410000\n",
       "All three      0.099338  0.105960       0.284768         0.509934"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 7 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Setup figure\n",
    "fig, ax_list = plt.subplots(nrows=2, ncols=2, figsize=(8, 4), gridspec_kw=dict(height_ratios=[3, 2]))\n",
    "ax2d = ax_list[0, 0]\n",
    "ax2f = ax_list[1, 0]\n",
    "for ax in ax_list[:, 1]:\n",
    "    ax.remove()\n",
    "\n",
    "ax2e = fig.add_subplot(ax2d.get_gridspec()[:, 1])\n",
    "\n",
    "# Calculate co-occurrance of motifs in strong enhancers\n",
    "strong_enh_coocc_df = wt_occupancy_grouper.get_group(\"Strong enhancer\")[[\"RAX\", \"NRL\", \"MAZ\", \"NDF1\", \"RORB\"]]\n",
    "strong_enh_coocc_df = (strong_enh_coocc_df > occupied_cutoff).astype(int)\n",
    "strong_enh_coocc_df = strong_enh_coocc_df.T.dot(strong_enh_coocc_df) / len(strong_enh_coocc_df)\n",
    "# Fill in lower triangle with the expected values\n",
    "for row in range(len(strong_enh_coocc_df)):\n",
    "    for col in range(row + 1, len(strong_enh_coocc_df)):\n",
    "        strong_enh_coocc_df.iloc[row, col] = strong_enh_coocc_df.iloc[row, row] * strong_enh_coocc_df.iloc[col, col]\n",
    "        \n",
    "# 2d: Make the heatmap\n",
    "ax = ax2d\n",
    "vmax = 0.25\n",
    "thresh = vmax / 2\n",
    "heatmap = ax.imshow(strong_enh_coocc_df, aspect=\"auto\", cmap=\"Reds\", vmax=vmax, vmin=0)\n",
    "ax.set_title(\"Strong enhancers\")\n",
    "ax.set_xticks(np.arange(len(strong_enh_coocc_df.columns)))\n",
    "ax.set_xticklabels(strong_enh_coocc_df.columns)\n",
    "ax.set_yticks(np.arange(len(strong_enh_coocc_df.columns)))\n",
    "ax.set_yticklabels(strong_enh_coocc_df.columns)\n",
    "plot_utils.annotate_heatmap(ax, strong_enh_coocc_df, thresh, adjust_lower_triangle=True)\n",
    "\n",
    "# Add colorbar\n",
    "divider = make_axes_locatable(ax)\n",
    "cax = divider.append_axes(\"right\", size=\"5%\", pad=\"2%\")\n",
    "colorbar = fig.colorbar(heatmap, cax=cax, label=\"Freq. motifs\\nco-occur\", ticks=[0, round(thresh, 2), vmax])\n",
    "plot_utils.add_letter(ax, -0.25, 1.03, \"d\")\n",
    "\n",
    "# Calculate activity classes for different binding combos\n",
    "binding_combos_activity_freq = activity_measured_wt_df.groupby(\"binding_group\")[\"group_name_WT\"].value_counts().unstack()\n",
    "binding_combos_activity_freq = binding_combos_activity_freq[class_sort_order]\n",
    "# Ignore cases where there is NRL or MEF2D but not CRX\n",
    "binding_combos_activity_freq = binding_combos_activity_freq.loc[[\"No binding\", \"CRX only\", \"CRX+NRL\", \"CRX+MEF2D\", \"All three\"]]\n",
    "binding_combos_activity_freq = binding_combos_activity_freq.astype(int)\n",
    "\n",
    "# Generate names then normalize data\n",
    "binding_combos_names = binding_combos_activity_freq.index.values\n",
    "binding_combos_count = [j.sum() for i, j in binding_combos_activity_freq.iterrows()]\n",
    "binding_combos_activity_freq = binding_combos_activity_freq.div(binding_combos_activity_freq.sum(axis=1), axis=0)\n",
    "display(binding_combos_activity_freq)\n",
    "\n",
    "# 2e: make plot\n",
    "ax = ax2e\n",
    "fig = plot_utils.stacked_bar_plots(binding_combos_activity_freq, \"Fraction of group\", binding_combos_names, color_mapping, figax=(fig, ax), vert=True)\n",
    "ax.set_yticks(np.linspace(0, 1, 6))\n",
    "plot_utils.rotate_ticks(ax.get_xticklabels())\n",
    "\n",
    "# Add the n\n",
    "ax_twin = ax.twiny()\n",
    "ax_twin.set_xticks(ax.get_xticks())\n",
    "ax_twin.set_xlim(ax.get_xlim())\n",
    "ax_twin.set_xticklabels(binding_combos_count, fontsize=10, rotation=45)\n",
    "plot_utils.add_letter(ax, -0.25, 1.03, \"e\")\n",
    "\n",
    "# Frequency each class is bound by each TF\n",
    "group_bound_freqs = activity_measured_wt_df.groupby(\"group_name_WT\")[[\"crx_bound\", \"nrl_bound\", \"mef2d_bound\"]].apply(lambda x: x.sum() / len(x))\n",
    "group_bound_freqs.columns = group_bound_freqs.columns.str.split(\"_\").str[0].str.upper()\n",
    "\n",
    "# 2f: Make heatmakt\n",
    "vmax = 1\n",
    "thresh = vmax / 2\n",
    "ax = ax2f\n",
    "heatmap = ax.imshow(group_bound_freqs.T, aspect=\"auto\", cmap=\"Reds\", vmax=vmax, vmin=0)\n",
    "ax.set_xticks(np.arange(len(wt_activity_names_oneline)))\n",
    "ax.set_xticklabels(wt_activity_names_oneline, rotation=90)\n",
    "ax.set_yticks(np.arange(len(group_bound_freqs.columns)))\n",
    "ax.set_yticklabels(group_bound_freqs.columns)\n",
    "plot_utils.annotate_heatmap(ax, group_bound_freqs, thresh)\n",
    "\n",
    "# Add colorbar\n",
    "divider = make_axes_locatable(ax)\n",
    "cax = divider.append_axes(\"right\", size=\"5%\", pad=\"2%\")\n",
    "colorbar = fig.colorbar(heatmap, cax=cax, label=\"Fraction\\nbound\")\n",
    "plot_utils.add_letter(ax, -0.25, 1.03, \"f\")\n",
    "\n",
    "# Add ticks above to show the n\n",
    "ax_twin = ax.twiny()\n",
    "ax_twin.set_axes_locator(ax.get_axes_locator())\n",
    "ax_twin.set_xticks(ax.get_xticks())\n",
    "ax_twin.set_xlim(ax.get_xlim())\n",
    "ax_twin.set_xticklabels(wt_activity_count, fontsize=10, rotation=45)\n",
    "\n",
    "plot_utils.save_fig(fig, os.path.join(figures_dir, \"figure2def\"), timestamp=False, tight_pad=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Supplemental figure 5: Additional validation of the 8 TF predicted occupancy logistic regression model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model performance on White 2013 test set:\n",
      "SVM\tAUROC = 0.800\tAUPR = 0.821\n",
      "8 TFs\tAUROC = 0.662\tAUPR = 0.714\n",
      "AUROCs of random features are normally distributed, KS test p = 0.80, D = 0.06\n",
      "Probability that the AUROC of the real features is drawn from the background distribution, one-tailed Z-test p = 0.000393\n",
      "AUPRs of random features are normally distributed, KS test p = 0.81, D = 0.06\n",
      "Probability that the AUPR of the real features is drawn from the background distribution, one-tailed Z-test p = 0.000796\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Setup figure\n",
    "fig, ax_list = plot_utils.setup_multiplot(4, n_cols=2, sharex=False, sharey=False)\n",
    "ax_list = ax_list.flatten()\n",
    "\n",
    "# Plot White 2013 test set\n",
    "_, white_aurocs, _, white_auprs, _ = plot_utils.roc_pr_curves(\n",
    "    modeling_xaxis, [white_svm_tpr, white_occ_tpr], [white_svm_prec, white_occ_prec],\n",
    "    model_names[:2], model_colors=model_colors[:2], prc_chance=white_svm_prec.iloc[-1],\n",
    "    figax=([fig, fig], ax_list[:2])\n",
    ")\n",
    "\n",
    "plot_utils.add_letter(ax_list[0], -0.15, 1.03, \"a\")\n",
    "plot_utils.add_letter(ax_list[1], -0.15, 1.03, \"b\")\n",
    "\n",
    "# Display model performance\n",
    "print(\"Model performance on White 2013 test set:\")\n",
    "print(f\"{model_names[0]}\\tAUROC = {white_aurocs[0]:.3f}\\tAUPR = {white_auprs[0]:.3f}\")\n",
    "print(f\"{model_names[1]}\\tAUROC = {white_aurocs[1]:.3f}\\tAUPR = {white_auprs[1]:.3f}\")\n",
    "\n",
    "# Plot performance of random background relative to the true features\n",
    "niter_rand = len(random_occ_tprs)\n",
    "rand_tpr_plotting = [[j] for i, j in random_occ_tprs.iterrows()] + [occ_tpr_cv]\n",
    "rand_prec_plotting = [[j] for i, j in random_occ_precs.iterrows()] + [occ_prec_cv]\n",
    "rand_names = [\"\"]  * niter_rand + [\"True features\"]\n",
    "rand_colors = [\"#8080801A\"] * niter_rand + [\"#E69B04\"]\n",
    "\n",
    "_, background_aurocs, _, background_auprs, _ = plot_utils.roc_pr_curves(\n",
    "    modeling_xaxis, rand_tpr_plotting, rand_prec_plotting, rand_names, model_colors=rand_colors,\n",
    "    prc_chance=prc_chance, figax=([fig, fig], ax_list[2:])\n",
    ")\n",
    "\n",
    "plot_utils.add_letter(ax_list[2], -0.15, 1.03, \"c\")\n",
    "plot_utils.add_letter(ax_list[3], -0.15, 1.03, \"d\")\n",
    "\n",
    "# KS test, null hypothesis: random AUROCs and AUPRs are normally distributed\n",
    "# One-tailed Z-test that the real data is drawn from this distribution\n",
    "for data, name in zip([background_aurocs, background_auprs], [\"AUROC\", \"AUPR\"]):\n",
    "    real, rand = data[niter_rand], data[:niter_rand]\n",
    "    dstat, pval = stats.kstest(stats.zscore(rand), \"norm\")\n",
    "    print(f\"{name}s of random features are normally distributed, KS test p = {pval:.2f}, D = {dstat:.2f}\")\n",
    "    zscore = (real - np.mean(rand)) / np.std(rand)\n",
    "    pval = stats.norm.cdf(-np.abs(zscore))\n",
    "    print(f\"Probability that the {name} of the real features is drawn from the background distribution, one-tailed Z-test p = {pval:2f}\")\n",
    "\n",
    "plot_utils.save_fig(fig, os.path.join(figures_dir, \"supplementalFigure5\"), timestamp=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Figure 3: Information content classifies strong enhancers\n",
    "Also supplemental figure 6: Precision recall curve of logistic regression classifier using information content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Information content for each class:\n"
     ]
    },
    {
     "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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>group_name_WT</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Silencer</th>\n",
       "      <td>837.0</td>\n",
       "      <td>1.554721</td>\n",
       "      <td>1.872824</td>\n",
       "      <td>0.000173</td>\n",
       "      <td>0.195721</td>\n",
       "      <td>0.952877</td>\n",
       "      <td>2.240308</td>\n",
       "      <td>15.248629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Inactive</th>\n",
       "      <td>928.0</td>\n",
       "      <td>1.385812</td>\n",
       "      <td>1.646322</td>\n",
       "      <td>0.000105</td>\n",
       "      <td>0.150796</td>\n",
       "      <td>0.841681</td>\n",
       "      <td>2.050814</td>\n",
       "      <td>14.738741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Weak enhancer</th>\n",
       "      <td>1360.0</td>\n",
       "      <td>1.496780</td>\n",
       "      <td>1.683849</td>\n",
       "      <td>0.000008</td>\n",
       "      <td>0.201747</td>\n",
       "      <td>1.014613</td>\n",
       "      <td>2.216628</td>\n",
       "      <td>17.960698</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Strong enhancer</th>\n",
       "      <td>1051.0</td>\n",
       "      <td>2.383258</td>\n",
       "      <td>2.178600</td>\n",
       "      <td>0.000173</td>\n",
       "      <td>0.635291</td>\n",
       "      <td>1.836731</td>\n",
       "      <td>3.453384</td>\n",
       "      <td>13.082139</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  count      mean       std       min       25%       50%  \\\n",
       "group_name_WT                                                               \n",
       "Silencer          837.0  1.554721  1.872824  0.000173  0.195721  0.952877   \n",
       "Inactive          928.0  1.385812  1.646322  0.000105  0.150796  0.841681   \n",
       "Weak enhancer    1360.0  1.496780  1.683849  0.000008  0.201747  1.014613   \n",
       "Strong enhancer  1051.0  2.383258  2.178600  0.000173  0.635291  1.836731   \n",
       "\n",
       "                      75%        max  \n",
       "group_name_WT                         \n",
       "Silencer         2.240308  15.248629  \n",
       "Inactive         2.050814  14.738741  \n",
       "Weak enhancer    2.216628  17.960698  \n",
       "Strong enhancer  3.453384  13.082139  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Strong enhancers and silencers have the same information content, Mann-Whitney U test p = 1e-23 U = 557959.00\n",
      "Strong enhancers and inactive sequences have the same information content, Mann-Whitney U test p = 7e-34, U = 641607.00\n",
      "Model metrics:\n",
      "Strong vs.\n",
      "silencer\tAUROC=0.634+/-0.008\tAUPR=0.663+/-0.014\n",
      "Strong vs.\n",
      "inactive\tAUROC=0.658+/-0.012\tAUPR=0.675+/-0.019\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Setup figures\n",
    "fig, ax_list = plot_utils.setup_multiplot(2, sharex=False, sharey=False)\n",
    "fig_pr, ax_pr = plt.subplots()\n",
    "\n",
    "# 3a: violin plot of information content\n",
    "print(\"Information content for each class:\")\n",
    "display(wt_entropy_grouper[\"entropy\"].describe())\n",
    "\n",
    "ax = ax_list[0]\n",
    "fig = plot_utils.violin_plot_groupby(wt_entropy_grouper[\"entropy\"], \"Information content\", class_names=wt_activity_names_oneline, class_colors=color_mapping, figax=(fig, ax))\n",
    "plot_utils.rotate_ticks(ax.get_xticklabels())\n",
    "ax.set_yticks(np.arange(0, wt_entropy_df[\"entropy\"].max() + 1, 2))\n",
    "plot_utils.add_letter(ax, -0.2, 1.03, \"a\")\n",
    "\n",
    "# Add ticks above to show the n\n",
    "ax_twin = ax.twiny()\n",
    "ax_twin.set_xticks(ax.get_xticks())\n",
    "ax_twin.set_xlim(ax.get_xlim())\n",
    "ax_twin.set_xticklabels(wt_activity_count, fontsize=10, rotation=45)\n",
    "\n",
    "# Statistics for differences in information content\n",
    "ustat, pval = stats.mannwhitneyu(wt_entropy_grouper[\"entropy\"].get_group(\"Strong enhancer\"), wt_entropy_grouper[\"entropy\"].get_group(\"Silencer\"), alternative=\"two-sided\")\n",
    "print(f\"Strong enhancers and silencers have the same information content, Mann-Whitney U test p = {pval:.0e} U = {ustat:.2f}\")\n",
    "ustat, pval = stats.mannwhitneyu(wt_entropy_grouper[\"entropy\"].get_group(\"Strong enhancer\"), wt_entropy_grouper[\"entropy\"].get_group(\"Inactive\"), alternative=\"two-sided\")\n",
    "print(f\"Strong enhancers and inactive sequences have the same information content, Mann-Whitney U test p = {pval:.0e}, U = {ustat:.2f}\")\n",
    "\n",
    "# 3b: ROC and PR curves with information content vs. two classes\n",
    "model_data = [\n",
    "    (entropy_tpr_cv, entropy_prec_cv, \"Strong vs.\\nsilencer\", \"#E69B04\"),\n",
    "    (inactive_entropy_tpr_cv, inactive_entropy_prec_cv, \"Strong vs.\\ninactive\", plot_utils.set_color(1))\n",
    "]\n",
    "\n",
    "model_tprs, model_precs, model_names, model_colors = zip(*model_data)\n",
    "ax = ax_list[1]\n",
    "\n",
    "# Plot the models\n",
    "_, model_aurocs, model_aurocs_std, model_auprs, model_auprs_std = plot_utils.roc_pr_curves(\n",
    "    modeling_xaxis, model_tprs, model_precs, model_names, model_colors=model_colors,\n",
    "    figax=([fig, fig_pr], [ax, ax_pr])\n",
    ")\n",
    "ax.set_xticks(np.linspace(0, 1, 6))\n",
    "plot_utils.add_letter(ax, -0.2, 1.03, \"b\")\n",
    "\n",
    "# Display model metrics\n",
    "print(\"Model metrics:\")\n",
    "for name, auroc, auroc_std, aupr, aupr_std in zip(model_names, model_aurocs, model_aurocs_std, model_auprs, model_auprs_std):\n",
    "    print(f\"{name}\\tAUROC={auroc:.3f}+/-{auroc_std:.3f}\\tAUPR={aupr:.3f}+/-{aupr_std:.3f}\")\n",
    "    \n",
    "plot_utils.save_fig(fig, os.path.join(figures_dir, \"figure3\"), timestamp=False, tight_pad=0)\n",
    "plot_utils.save_fig(fig_pr, os.path.join(figures_dir, \"supplementalFigure6\"), timestamp=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Figure 4: Sequence features of autonomous and non-autonomous strong enhancers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correlation between WT activity with Rho vs. Polylinker:\n",
      "PCC = 0.338\n",
      "SCC = 0.359\n",
      "n = 4751\n",
      "Fraction of autonomous sequences belonging to each activity class:\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Strong enhancer    0.693103\n",
       "Weak enhancer      0.208621\n",
       "Inactive           0.070690\n",
       "Silencer           0.027586\n",
       "Name: group_name_WT, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fraction of each activity class that has autonomous activity:\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "group_name_WT\n",
       "Silencer           0.019394\n",
       "Inactive           0.044565\n",
       "Weak enhancer      0.090705\n",
       "Strong enhancer    0.387657\n",
       "Name: autonomous_activity, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Information content of autonomous and non-autonomous strong enhancers:\n"
     ]
    },
    {
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       "      <td>635.0</td>\n",
       "      <td>2.073301</td>\n",
       "      <td>1.964160</td>\n",
       "      <td>0.000173</td>\n",
       "      <td>0.488725</td>\n",
       "      <td>1.624789</td>\n",
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       "      <td>0.990757</td>\n",
       "      <td>2.272392</td>\n",
       "      <td>4.401275</td>\n",
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      "text/plain": [
       "                     count      mean       std       min       25%       50%  \\\n",
       "autonomous_activity                                                            \n",
       "False                635.0  2.073301  1.964160  0.000173  0.488725  1.624789   \n",
       "True                 402.0  2.888074  2.424544  0.000346  0.990757  2.272392   \n",
       "\n",
       "                          75%        max  \n",
       "autonomous_activity                       \n",
       "False                3.026204  11.747577  \n",
       "True                 4.401275  13.082139  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Autonomous and non-autonomous strong enhancers have the same information content, Mann-Whitney U test p=4e-08, U=101739.00\n",
      "Predicted CRX occupancy of autonomous and non-autonomous strong enhancers:\n"
     ]
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       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
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       "    <tr>\n",
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       "      <th>False</th>\n",
       "      <td>635.0</td>\n",
       "      <td>2.34943</td>\n",
       "      <td>1.154518</td>\n",
       "      <td>0.003694</td>\n",
       "      <td>1.471752</td>\n",
       "      <td>2.255551</td>\n",
       "      <td>3.075332</td>\n",
       "      <td>7.368500</td>\n",
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       "    <tr>\n",
       "      <th>True</th>\n",
       "      <td>402.0</td>\n",
       "      <td>2.83343</td>\n",
       "      <td>1.127028</td>\n",
       "      <td>0.015596</td>\n",
       "      <td>2.062315</td>\n",
       "      <td>2.858271</td>\n",
       "      <td>3.554521</td>\n",
       "      <td>5.852791</td>\n",
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      ],
      "text/plain": [
       "                     count     mean       std       min       25%       50%  \\\n",
       "autonomous_activity                                                           \n",
       "False                635.0  2.34943  1.154518  0.003694  1.471752  2.255551   \n",
       "True                 402.0  2.83343  1.127028  0.015596  2.062315  2.858271   \n",
       "\n",
       "                          75%       max  \n",
       "autonomous_activity                      \n",
       "False                3.075332  7.368500  \n",
       "True                 3.554521  5.852791  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Autonomous and non-autonomous strong enhancers have the same predicted CRX occupancy, Mann-Whitney U test p=9e-12, U=95541.00\n",
      "Strong enhancers with autonomous and non-autonomous activity vs. NRL bound and unbound:\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "nrl_bound            False  True \n",
       "autonomous_activity              \n",
       "False                  513    122\n",
       "True                   236    166"
      ]
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     "metadata": {},
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fisher's exact test that NRL binding and strong enhancer autonomous activity are independent, p=2e-14, odds ratio=3.0\n"
     ]
    },
    {
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\n",
      "text/plain": [
       "<Figure size 576x576 with 8 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Keep sequences where the WT and Polylinker were both measured\n",
    "poly_measured_mask = activity_df[[\"expression_log2_WT\", \"expression_log2_POLY\"]].notna().all(axis=1)\n",
    "activity_poly_df = activity_df[poly_measured_mask]\n",
    "wt_occupancy_poly_df = wt_occupancy_df[poly_measured_mask]\n",
    "wt_entropy_poly_df = wt_entropy_df[poly_measured_mask]\n",
    "\n",
    "# Setup the figure\n",
    "fig, ax_list = plot_utils.setup_multiplot(4, sharex=False, sharey=False)\n",
    "ax_list = ax_list.flatten()\n",
    "\n",
    "# 4a: scatterplot of Rho vs. Polylinker\n",
    "ax = ax_list[0]\n",
    "print(\"Correlation between WT activity with Rho vs. Polylinker:\")\n",
    "fig, ax = plot_utils.scatter_with_corr(activity_poly_df[\"expression_log2_WT\"], activity_poly_df[\"expression_log2_POLY\"], \"log2 Enhancer Activity/Rho\", \"log2 Autonomous Activity\", colors=activity_poly_df[\"plot_color_WT\"], xticks=rho_ticks, figax=(fig, ax))\n",
    "ax.axhline(0, color=\"k\", linestyle=\"--\")\n",
    "plot_utils.add_letter(ax, -0.2, 1.03, \"a\")\n",
    "\n",
    "# Display some numbers for the manuscript\n",
    "print(\"Fraction of autonomous sequences belonging to each activity class:\")\n",
    "display(activity_poly_df.loc[activity_poly_df[\"autonomous_activity\"], \"group_name_WT\"].value_counts(normalize=True))\n",
    "\n",
    "print(\"Fraction of each activity class that has autonomous activity:\")\n",
    "display(activity_poly_df.groupby(\"group_name_WT\")[\"autonomous_activity\"].apply(lambda x: x.sum() / len(x)))\n",
    "\n",
    "# Information content of strong autonomous vs. non-autonomous\n",
    "# Set up grouping\n",
    "strong_enh_poly_mask = activity_poly_df[\"group_name_WT\"].str.contains(\"Strong\")\n",
    "strong_enh_poly_mask = strong_enh_poly_mask & strong_enh_poly_mask.notna()\n",
    "autonomous_occ_grouper = wt_occupancy_poly_df[strong_enh_poly_mask].groupby(activity_poly_df.loc[strong_enh_poly_mask, \"autonomous_activity\"])\n",
    "autonomous_entropy_grouper = wt_entropy_poly_df[strong_enh_poly_mask].groupby(activity_poly_df.loc[strong_enh_poly_mask, \"autonomous_activity\"])\n",
    "\n",
    "# Set up for plotting\n",
    "strong_color = color_mapping[\"Strong enhancer\"]\n",
    "autonomous_names = [\"Non-autonomous \", \" Autonomous\"]\n",
    "autonomous_counts = [len(i) for i in autonomous_occ_grouper.groups.values()]\n",
    "\n",
    "# Do stats for difference in IC\n",
    "print(\"Information content of autonomous and non-autonomous strong enhancers:\")\n",
    "display(autonomous_entropy_grouper[\"entropy\"].describe())\n",
    "ustat, pval = stats.mannwhitneyu(*[j for i, j in autonomous_entropy_grouper[\"entropy\"]], alternative=\"two-sided\")\n",
    "print(f\"Autonomous and non-autonomous strong enhancers have the same information content, Mann-Whitney U test p={pval:.0e}, U={ustat:.2f}\")\n",
    "\n",
    "# 4b: Make the plot\n",
    "ax = ax_list[1]\n",
    "fig = plot_utils.violin_plot_groupby(autonomous_entropy_grouper[\"entropy\"], \"Information content\", class_names=autonomous_names, class_colors=[strong_color]*2, figax=(fig, ax))\n",
    "ax.set_xlabel(\"Strong enhancers\")\n",
    "# Add ticks for the n\n",
    "ax_twin = ax.twiny()\n",
    "ax_twin.set_xticks(ax.get_xticks())\n",
    "ax_twin.set_xlim(ax.get_xlim())\n",
    "ax_twin.set_xticklabels(autonomous_counts, fontsize=10, rotation=45)\n",
    "plot_utils.add_letter(ax, -0.2, 1.03, \"b\")\n",
    "\n",
    "# Differences in CRX occupancy\n",
    "print(\"Predicted CRX occupancy of autonomous and non-autonomous strong enhancers:\")\n",
    "display(autonomous_occ_grouper[\"CRX\"].describe())\n",
    "ustat, pval = stats.mannwhitneyu(*[j for i, j in autonomous_occ_grouper[\"CRX\"]], alternative=\"two-sided\")\n",
    "print(f\"Autonomous and non-autonomous strong enhancers have the same predicted CRX occupancy, Mann-Whitney U test p={pval:.0e}, U={ustat:.2f}\")\n",
    "\n",
    "# 4c\n",
    "ax = ax_list[2]\n",
    "fig = plot_utils.violin_plot_groupby(autonomous_occ_grouper[\"CRX\"], \"Predicted CRX occupancy\", class_names=autonomous_names, class_colors=[strong_color]*2, figax=(fig, ax))\n",
    "ax.set_xlabel(\"Strong enhancers\")\n",
    "ax.set_yticks(np.arange(8))\n",
    "# Add ticks for the n\n",
    "ax_twin = ax.twiny()\n",
    "ax_twin.set_xticks(ax.get_xticks())\n",
    "ax_twin.set_xlim(ax.get_xlim())\n",
    "ax_twin.set_xticklabels(autonomous_counts, fontsize=10, rotation=45)\n",
    "plot_utils.add_letter(ax, -0.2, 1.03, \"c\")\n",
    "\n",
    "# Differences in motif frequencies\n",
    "autonomous_motif_freq_df = autonomous_occ_grouper.apply(lambda x: (x > occupied_cutoff).sum() / len(x))\n",
    "# Sort by the feature importance in the logistic model\n",
    "autonomous_motif_freq_df = autonomous_motif_freq_df.iloc[:, feature_order]\n",
    "\n",
    "# 4d: Make heatmakt, but put CRX separate\n",
    "ax = ax_list[3]\n",
    "autonomous_motif_freq_no_crx_df = autonomous_motif_freq_df.drop(columns=\"CRX\") \n",
    "vmax = 0.25\n",
    "thresh = vmax / 2\n",
    "heatmap = ax.imshow(autonomous_motif_freq_no_crx_df.T, aspect=\"auto\", cmap=\"Reds\", vmax=vmax, vmin=0)\n",
    "ax.set_xlabel(\"Strong enhancers\")\n",
    "ax.set_xticks(np.arange(len(autonomous_motif_freq_no_crx_df)))\n",
    "ax.set_xticklabels(autonomous_names)\n",
    "ax.set_yticks(np.arange(len(autonomous_motif_freq_no_crx_df.columns)))\n",
    "ax.set_yticklabels(autonomous_motif_freq_no_crx_df.columns)\n",
    "plot_utils.annotate_heatmap(ax, autonomous_motif_freq_no_crx_df, thresh)\n",
    "\n",
    "# Add colorbar\n",
    "divider = make_axes_locatable(ax)\n",
    "cax = divider.append_axes(\"right\", size=\"5%\", pad=\"2%\")\n",
    "colorbar = fig.colorbar(heatmap, cax=cax, label=\"Frequency of motif\")\n",
    "ticks = cax.get_yticks()\n",
    "ticks = [f\"{i:.2f}\" for i in ticks]\n",
    "ticks[-1] = r\"$\\geq$\" + ticks[-1]\n",
    "cax.set_yticklabels(ticks)\n",
    "\n",
    "# Add CRX\n",
    "cax = divider.append_axes(\"top\", size=\"14%\", pad=\"2%\")\n",
    "heatmap = cax.imshow(autonomous_motif_freq_df[\"CRX\"].to_frame().T, aspect=\"auto\", cmap=\"Reds\", vmax=vmax, vmin=0)\n",
    "cax.set_xticks([])\n",
    "cax.set_yticks([0])\n",
    "cax.set_yticklabels([\"CRX\"])\n",
    "plot_utils.annotate_heatmap(cax, autonomous_motif_freq_df[\"CRX\"].to_frame(), thresh)\n",
    "plot_utils.add_letter(cax, -0.2, 1.03, \"d\")\n",
    "\n",
    "# Add ticks for the n\n",
    "cax.xaxis.tick_top()\n",
    "cax.set_xticks(ax.get_xticks())\n",
    "cax.set_xlim(ax.get_xlim())\n",
    "cax.set_xticklabels(autonomous_counts, fontsize=10, rotation=45)\n",
    "\n",
    "# Test relationship between NRL binding and strong enhancer autonomous activity\n",
    "print(\"Strong enhancers with autonomous and non-autonomous activity vs. NRL bound and unbound:\")\n",
    "nrl_chip_vs_autonomous = activity_poly_df[strong_enh_poly_mask].groupby(\"autonomous_activity\")[\"nrl_bound\"].value_counts().unstack()\n",
    "display(nrl_chip_vs_autonomous)\n",
    "oddsratio, pval = stats.fisher_exact(nrl_chip_vs_autonomous)\n",
    "print(f\"Fisher's exact test that NRL binding and strong enhancer autonomous activity are independent, p={pval:.0e}, odds ratio={oddsratio:.1f}\")\n",
    "\n",
    "plot_utils.save_fig(fig, os.path.join(figures_dir, \"figure4\"), timestamp=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Figure 5: Independence of TF motifs in strong enhancers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Helper functions to visualize sequence\n",
    "def hex_to_rgb(hexcode):\n",
    "    return tuple(int(hexcode[i:i+2], 16) / 255 for i in (1, 3, 5))\n",
    "\n",
    "strong_color_rgb = hex_to_rgb(strong_color)\n",
    "weak_color_rgb = hex_to_rgb(color_mapping[\"Weak enhancer\"])\n",
    "crx_color = mpl.colors.to_rgb(\"orange\")\n",
    "other_tf_color = mpl.colors.to_rgb(\"red\")\n",
    "\n",
    "def visualize_sequence(seq_id, ax, title, below_text, basecolor):\n",
    "    seq_occupancy_df = predicted_occupancy.total_landscape(all_seqs[seq_id], ewms, mu)\n",
    "    visual = np.full(((len(seq_occupancy_df), 3)), basecolor) # (number of positions, RGB values)\n",
    "    text_mapping = [] # (name of TF, center position of motif)\n",
    "    # Loop over each TF, identify motifs, and fill in the representation with the predicted occupancy for the full motif\n",
    "    for col in seq_occupancy_df:\n",
    "        tf, orient = col.split(\"_\")\n",
    "        for motif_start, occ in seq_occupancy_df[col].iteritems():\n",
    "            if occ > occupied_cutoff:\n",
    "                motif_end = motif_start + motif_len[tf]\n",
    "                # Check and make sure all positions of the motif are zeros\n",
    "                if (visual[motif_start:motif_end] != basecolor).all(axis=1).any():\n",
    "                    print(f\"Error, motif already in the range {motif_start}-{motif_end}! Skipping.\")\n",
    "                else:\n",
    "                    color = crx_color if tf == \"CRX\" else other_tf_color\n",
    "                    visual[motif_start:motif_end] = color\n",
    "                    text_mapping.append((tf, (motif_start + motif_end) / 2))\n",
    "        \n",
    "    heatmap = ax.imshow(visual[np.newaxis, :], aspect=\"auto\", cmap=\"Reds\")\n",
    "    ax.set_yticks([])\n",
    "    # Add text showing which motif is where\n",
    "    for tf, x in text_mapping:\n",
    "        ax.text(x, 0, tf, ha=\"center\", va=\"center\", color=\"white\", rotation=90)\n",
    "\n",
    "    ax.set_title(title)\n",
    "    ax.set_xlabel(below_text)\n",
    "    \n",
    "    return ax, heatmap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correlation between WT and MUT activities:\n",
      "PCC = 0.608\n",
      "SCC = 0.706\n",
      "n = 4123\n",
      "Information content of strong enhancers with different mutant activities:\n"
     ]
    },
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       "                count      mean       std       min       25%       50%  \\\n",
       "group_name_MUT                                                            \n",
       "False           586.0  2.321663  2.067846  0.000346  0.641760  1.849581   \n",
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       "\n",
       "                     75%        max  \n",
       "group_name_MUT                       \n",
       "False           3.333561  11.676515  \n",
       "True            3.969305  13.082139  "
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     "text": [
      "Predicted CRX occupancy of strong enhancers with different mutant activities:\n"
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       "                count      mean       std       min       25%       50%  \\\n",
       "group_name_MUT                                                            \n",
       "False           586.0  2.876820  1.069855  0.927761  2.085474  2.857976   \n",
       "True            344.0  2.454016  1.009155  0.964684  1.626097  2.338718   \n",
       "\n",
       "                     75%       max  \n",
       "group_name_MUT                      \n",
       "False           3.575210  7.368500  \n",
       "True            3.110073  5.730406  "
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     "text": [
      "Strong enhancers that remain strong vs. do not have the same CRX occupancy, Mann-Whitney U test p=2e-09, U=124411.00\n",
      "Residual information content of strong enhancers with different mutant activities:\n"
     ]
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       "                count      mean       std       min       25%       50%  \\\n",
       "group_name_MUT                                                            \n",
       "False           586.0  1.026129  1.283253  0.000001  0.097540  0.493644   \n",
       "True            344.0  1.536551  1.638575  0.000136  0.264872  1.046836   \n",
       "\n",
       "                     75%       max  \n",
       "group_name_MUT                      \n",
       "False           1.472322  7.129248  \n",
       "True            2.338690  9.819172  "
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     "text": [
      "Strong enhancers that stay strong vs. do not have the same residual information content, Mann-Whitney U test p=1e-07, U=79938.00\n"
     ]
    },
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\n",
      "text/plain": [
       "<Figure size 504x720 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Setup for sequences where both WT and MUT was measured\n",
    "wt_mut_mask = activity_df[\"wt_vs_mut_log2\"].notna()\n",
    "activity_wt_mut_measured_df = activity_df[wt_mut_mask]\n",
    "wt_occ_mut_measured_df = wt_occupancy_df[wt_mut_mask]\n",
    "wt_entropy_mut_measured_df = wt_entropy_df[wt_mut_mask]\n",
    "mut_entropy_measured_df = mut_entropy_df[wt_mut_mask]\n",
    "\n",
    "# Figure setup\n",
    "gs_kw = dict(height_ratios=[5, 5, 1, 1])\n",
    "fig, ax_list = plt.subplots(nrows=4, ncols=2, figsize=(7, 10), gridspec_kw=gs_kw)\n",
    "gs = ax_list[0, 0].get_gridspec()\n",
    "for row in [2, 3]:\n",
    "    for ax in ax_list[row]:\n",
    "        ax.remove()\n",
    "    \n",
    "axstrong = fig.add_subplot(gs[2, :])\n",
    "axweak = fig.add_subplot(gs[3, :])\n",
    "\n",
    "# 5a: Scatter plot of WT and MUT activities\n",
    "ax = ax_list[0, 0]\n",
    "print(\"Correlation between WT and MUT activities:\")\n",
    "fig, ax = plot_utils.scatter_with_corr(activity_wt_mut_measured_df[\"expression_log2_WT\"], activity_wt_mut_measured_df[\"expression_log2_MUT\"],\n",
    "                                      \"log2 WT Activity/Rho\", \"log2 MUT Activity/Rho\", colors=activity_wt_mut_measured_df[\"plot_color_WT\"],\n",
    "                                      xticks=rho_ticks, yticks=rho_ticks, figax=(fig, ax))\n",
    "# Plot y = x line\n",
    "ax.plot(rho_ticks, rho_ticks, color=\"black\", linewidth=1)\n",
    "# Show cutoffs for different classes\n",
    "strong_cutoff = activity_df.groupby(\"group_name_WT\")[\"expression_log2_WT\"].get_group(\"Strong enhancer\").min()\n",
    "for line in [-1, 1, strong_cutoff]:\n",
    "    ax.axhline(line, color=\"black\", linestyle=\"--\", linewidth=1)\n",
    "    \n",
    "# Add colorbar to show the cutoffs\n",
    "divider = make_axes_locatable(ax)\n",
    "color_ax = divider.append_axes(\"right\", size=\"5%\")\n",
    "color_ax.set_ylim(ax.get_ylim())\n",
    "color_ax.barh([(-1 - ax.get_ylim()[0]) / 2 + ax.get_ylim()[0], 0, (strong_cutoff - 1) / 2 + 1, (ax.get_ylim()[1] - strong_cutoff) / 2 + strong_cutoff], # Midpoint of the bars\n",
    "             [1, 1, 1, 1], # Bar height\n",
    "             [-1 - ax.get_ylim()[0], 2, strong_cutoff - 1, ax.get_ylim()[1] - strong_cutoff], # Bar width\n",
    "             color=color_mapping)\n",
    "color_ax.set_xticks([])\n",
    "color_ax.set_yticks([])\n",
    "color_ax.set_xlim(right=1)\n",
    "\n",
    "plot_utils.add_letter(ax, -0.35, 1.03, \"a\")\n",
    "\n",
    "# Setup strong enhancer->mutant activity groupings\n",
    "strong_mask = activity_wt_mut_measured_df[\"group_name_WT\"].str.contains(\"Strong\")\n",
    "strong_mask = strong_mask & strong_mask.notna()\n",
    "activity_strong_df = activity_wt_mut_measured_df[strong_mask]\n",
    "\n",
    "# Group the data based on CRX-dependence (whether or not it stay strong) and name the groups accordingly\n",
    "stay_strong_mask = activity_strong_df[\"group_name_MUT\"].str.contains(\"Strong\") & activity_strong_df[\"group_name_MUT\"].notna()\n",
    "wt_occ_strong_grouper = wt_occ_mut_measured_df[strong_mask].groupby(stay_strong_mask)\n",
    "wt_entropy_strong_grouper = wt_entropy_mut_measured_df[strong_mask].groupby(stay_strong_mask)\n",
    "strong_mutant_names = wt_entropy_strong_grouper[\"entropy\"].count().rename({False: \"High\", True: \"Low\"}).index.values.tolist()\n",
    "strong_mutant_counts = wt_entropy_strong_grouper[\"entropy\"].count().astype(int).values\n",
    "\n",
    "# Differences in information content\n",
    "print(\"Information content of strong enhancers with different mutant activities:\")\n",
    "display(wt_entropy_strong_grouper[\"entropy\"].describe())\n",
    "\n",
    "# 5b: Information content\n",
    "ax = ax_list[0, 1]\n",
    "fig = plot_utils.violin_plot_groupby(wt_entropy_strong_grouper[\"entropy\"], \"Information content\", class_names=strong_mutant_names, class_colors=color_mapping[[\"Weak enhancer\", \"Strong enhancer\"]], figax=(fig, ax))\n",
    "ax.set_xlabel(\"CRX-dependence\\nStrong enhancers\")\n",
    "ax.set_yticks(np.arange(0, 13, 2))\n",
    "ax_twin = ax.twiny()\n",
    "ax_twin.set_xticks(ax.get_xticks())\n",
    "ax_twin.set_xlim(ax.get_xlim())\n",
    "ax_twin.set_xticklabels(strong_mutant_counts, fontsize=10, rotation=45)\n",
    "plot_utils.add_letter(ax, -0.25, 1.03, \"b\")\n",
    "\n",
    "# Differences in predicted CRX occupancy of strong enhancers with different CRX-dependences\n",
    "print(\"Predicted CRX occupancy of strong enhancers with different mutant activities:\")\n",
    "display(wt_occ_strong_grouper[\"CRX\"].describe())\n",
    "ustat, pval = stats.mannwhitneyu(*[j for i, j in wt_occ_strong_grouper[\"CRX\"]], alternative=\"two-sided\")\n",
    "print(f\"Strong enhancers that remain strong vs. do not have the same CRX occupancy, Mann-Whitney U test p={pval:.0e}, U={ustat:.2f}\")\n",
    "\n",
    "# 5c: predicted CRX occupancy\n",
    "ax = ax_list[1, 0]\n",
    "fig = plot_utils.violin_plot_groupby(wt_occ_strong_grouper[\"CRX\"], \"Predicted CRX occupancy\", class_names=strong_mutant_names, class_colors=color_mapping[[\"Weak enhancer\", \"Strong enhancer\"]], figax=(fig, ax))\n",
    "ax.set_xlabel(\"CRX-dependence\\nStrong enhancers\")\n",
    "ax.set_yticks(np.arange(0, 8, 2))\n",
    "ax_twin = ax.twiny()\n",
    "ax_twin.set_xticks(ax.get_xticks())\n",
    "ax_twin.set_xlim(ax.get_xlim())\n",
    "ax_twin.set_xticklabels(strong_mutant_counts, fontsize=10, rotation=45)\n",
    "plot_utils.add_letter(ax, -0.25, 1.03, \"c\")\n",
    "\n",
    "# Differences in redisual IC\n",
    "print(\"Residual information content of strong enhancers with different mutant activities:\")\n",
    "mut_entropy_strong_grouper = mut_entropy_measured_df[strong_mask].groupby(stay_strong_mask)\n",
    "display(mut_entropy_strong_grouper[\"entropy\"].describe())\n",
    "ustat, pval = stats.mannwhitneyu(*[j for i, j in mut_entropy_strong_grouper[\"entropy\"]], alternative=\"two-sided\")\n",
    "print(f\"Strong enhancers that stay strong vs. do not have the same residual information content, Mann-Whitney U test p={pval:.0e}, U={ustat:.2f}\")\n",
    "\n",
    "# 5d: Residual information content\n",
    "ax = ax_list[1, 1]\n",
    "fig = plot_utils.violin_plot_groupby(mut_entropy_strong_grouper[\"entropy\"], \"Residual information content\", class_names=strong_mutant_names, class_colors=color_mapping[[\"Weak enhancer\", \"Strong enhancer\"]], figax=(fig, ax))\n",
    "ax.set_xlabel(\"CRX-dependence\\nStrong enhancers\")\n",
    "ax.set_yticks(np.arange(0, 11, 2))\n",
    "ax_twin = ax.twiny()\n",
    "ax_twin.set_xticks(ax.get_xticks())\n",
    "ax_twin.set_xlim(ax.get_xlim())\n",
    "ax_twin.set_xticklabels(strong_mutant_counts, fontsize=10, rotation=45)\n",
    "plot_utils.add_letter(ax, -0.25, 1.03, \"d\")\n",
    "\n",
    "# 5e Visualize the two depresentative sequences\n",
    "ax = axstrong\n",
    "become_weak_example_id = \"chr16-43945747-43945911_UPPE\"\n",
    "become_weak_text = become_weak_example_id.split(\"_\")[0] + \"\\n\" + f\"{wt_entropy_df.loc[become_weak_example_id, 'entropy']:.1f}\" + \" bits, \" + f\"{mut_entropy_df.loc[become_weak_example_id, 'entropy']:.1f}\" + \" residual bits\"\n",
    "ax, become_weak_visual = visualize_sequence(become_weak_example_id + \"_WT\", ax, \"High CRX-dependence\", become_weak_text, weak_color_rgb)\n",
    "plot_utils.add_letter(ax, -0.05, 1.03, \"e\")\n",
    "\n",
    "ax = axweak\n",
    "stay_strong_example_id = \"chr11-114685176-114685340_CPPE\"\n",
    "stay_strong_text = stay_strong_example_id.split(\"_\")[0] + \"\\n\" + f\"{wt_entropy_df.loc[stay_strong_example_id, 'entropy']:.1f}\" + \" bits, \" + f\"{mut_entropy_df.loc[stay_strong_example_id, 'entropy']:.1f}\" + \" residual bits\"\n",
    "ax, stay_strong_visual = visualize_sequence(stay_strong_example_id + \"_WT\", ax, \"Low CRX-dependence\", stay_strong_text, strong_color_rgb)\n",
    "\n",
    "plot_utils.save_fig(fig, os.path.join(figures_dir, \"figure5\"), timestamp=False)"
   ]
  }
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