code/08.Anteroposterior-Enrichment.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from collections import defaultdict\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "import seaborn as sns\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "\n",
    "import itertools, scipy\n",
    "from sklearn.metrics.pairwise import euclidean_distances, manhattan_distances\n",
    "\n",
    "import cell2cell as c2c\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "output_folder = '../results/CCI-Anteroposterior-Enrichment/'\n",
    "if not os.path.isdir(output_folder):\n",
    "    os.mkdir(output_folder)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3D Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "atlas = pd.read_csv('../data/Digital-3D-Map/Celegans_L1_3D_Atlas_CellTypes.csv')\n",
    "atlas = atlas.loc[~atlas['Cell Type'].isnull()].reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\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>Cell</th>\n",
       "      <th>Lineage Name</th>\n",
       "      <th>Description</th>\n",
       "      <th>Cell2</th>\n",
       "      <th>Name2</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>Z</th>\n",
       "      <th>Cell Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ADEshL</td>\n",
       "      <td>AB arppaaaa</td>\n",
       "      <td>Anterior deirid sheath</td>\n",
       "      <td>ADESHL</td>\n",
       "      <td>ABARPPAAAA</td>\n",
       "      <td>11.134</td>\n",
       "      <td>84.340</td>\n",
       "      <td>12.852</td>\n",
       "      <td>Am/PH_sheath_cells</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ADEshR</td>\n",
       "      <td>AB arpppaaa</td>\n",
       "      <td>Anterior deirid sheath</td>\n",
       "      <td>ADESHR</td>\n",
       "      <td>ABARPPPAAA</td>\n",
       "      <td>16.990</td>\n",
       "      <td>85.075</td>\n",
       "      <td>13.130</td>\n",
       "      <td>Am/PH_sheath_cells</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ALML</td>\n",
       "      <td>AB.arppaappa</td>\n",
       "      <td>Anterior lateral microtubule cell, touch receptor</td>\n",
       "      <td>ALML</td>\n",
       "      <td>ABARPPAAPPA</td>\n",
       "      <td>11.759</td>\n",
       "      <td>120.005</td>\n",
       "      <td>16.090</td>\n",
       "      <td>Touch_receptor_neurons</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ALMR</td>\n",
       "      <td>AB arpppappa</td>\n",
       "      <td>Anterior lateral microtubule cell, touch receptor</td>\n",
       "      <td>ALMR</td>\n",
       "      <td>ABARPPPAPPA</td>\n",
       "      <td>16.467</td>\n",
       "      <td>119.037</td>\n",
       "      <td>15.870</td>\n",
       "      <td>Touch_receptor_neurons</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ALNL</td>\n",
       "      <td>AB plapappppap</td>\n",
       "      <td>Neuron associated with ALM</td>\n",
       "      <td>ALNL</td>\n",
       "      <td>ABPLAPAPPPPAP</td>\n",
       "      <td>12.884</td>\n",
       "      <td>199.753</td>\n",
       "      <td>15.437</td>\n",
       "      <td>Oxygen_sensory_neurons</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Cell    Lineage Name                                        Description  \\\n",
       "0  ADEshL     AB arppaaaa                             Anterior deirid sheath   \n",
       "1  ADEshR     AB arpppaaa                             Anterior deirid sheath   \n",
       "2    ALML    AB.arppaappa  Anterior lateral microtubule cell, touch receptor   \n",
       "3    ALMR    AB arpppappa  Anterior lateral microtubule cell, touch receptor   \n",
       "4    ALNL  AB plapappppap                         Neuron associated with ALM   \n",
       "\n",
       "    Cell2          Name2       X        Y       Z               Cell Type  \n",
       "0  ADESHL     ABARPPAAAA  11.134   84.340  12.852      Am/PH_sheath_cells  \n",
       "1  ADESHR     ABARPPPAAA  16.990   85.075  13.130      Am/PH_sheath_cells  \n",
       "2    ALML    ABARPPAAPPA  11.759  120.005  16.090  Touch_receptor_neurons  \n",
       "3    ALMR    ABARPPPAPPA  16.467  119.037  15.870  Touch_receptor_neurons  \n",
       "4    ALNL  ABPLAPAPPPPAP  12.884  199.753  15.437  Oxygen_sensory_neurons  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "atlas.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load LR list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "lr_pairs = pd.read_csv('../data/PPI-Networks/Celegans-GA-BrayCurtis-Selected-LR-pairs.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "lr_pairs = lr_pairs.sort_values(by=['LR Function', 'index'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\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>Ligand_WB</th>\n",
       "      <th>Receptor_WB</th>\n",
       "      <th>Ligand_symbol</th>\n",
       "      <th>Receptor_symbol</th>\n",
       "      <th>score</th>\n",
       "      <th>index</th>\n",
       "      <th>LR Function</th>\n",
       "      <th>L Function</th>\n",
       "      <th>R Function</th>\n",
       "      <th>Ligand_desc_WormBase_versionWS277</th>\n",
       "      <th>Receptor_desc_WormBase_versionWS277</th>\n",
       "      <th>Pair_confidence</th>\n",
       "      <th>Location_type</th>\n",
       "      <th>Confidence_evidence</th>\n",
       "      <th>Location_evidence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>WBGene00002881</td>\n",
       "      <td>WBGene00006894</td>\n",
       "      <td>let-756</td>\n",
       "      <td>ver-1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7</td>\n",
       "      <td>Canonical RTK-Ras-ERK signaling</td>\n",
       "      <td>FGF</td>\n",
       "      <td>fms-related tyrosine kinase 1</td>\n",
       "      <td>Is an ortholog of human FGF16 (fibroblast grow...</td>\n",
       "      <td>Is an ortholog of human FLT1 (fms related rece...</td>\n",
       "      <td>Putative based on literature</td>\n",
       "      <td>Secreted</td>\n",
       "      <td>Orthology, protein-protein interaction (STRING...</td>\n",
       "      <td>wormbase: let-756 is found in the cytoplasm;ex...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>WBGene00000527</td>\n",
       "      <td>WBGene00001687</td>\n",
       "      <td>cle-1</td>\n",
       "      <td>gpn-1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>13</td>\n",
       "      <td>Cell adhesion</td>\n",
       "      <td>Collagen</td>\n",
       "      <td>Glypican (co-receptor) Frizzled homolog</td>\n",
       "      <td>Is an ortholog of human COL15A1 (collagen type...</td>\n",
       "      <td>Is an ortholog of human GPC1 (glypican 1) and ...</td>\n",
       "      <td>Literature supported</td>\n",
       "      <td>ECM-component</td>\n",
       "      <td>WormBook</td>\n",
       "      <td>wormbase: cle-1 is found in the extracellular ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>WBGene00002280</td>\n",
       "      <td>WBGene00003930</td>\n",
       "      <td>let-2</td>\n",
       "      <td>pat-3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>26</td>\n",
       "      <td>Cell adhesion</td>\n",
       "      <td>Collagen</td>\n",
       "      <td>Integrin</td>\n",
       "      <td>Is an ortholog of human COL4A5 (collagen type ...</td>\n",
       "      <td>Is an ortholog of human ITGB1 (integrin subuni...</td>\n",
       "      <td>Literature supported</td>\n",
       "      <td>ECM-component</td>\n",
       "      <td>10.1083/jcb.201903124</td>\n",
       "      <td>Wormbase: let-2 is located in the extracellula...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>WBGene00000674</td>\n",
       "      <td>WBGene00016104</td>\n",
       "      <td>col-99</td>\n",
       "      <td>ddr-1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>35</td>\n",
       "      <td>Cell adhesion</td>\n",
       "      <td>Collagen</td>\n",
       "      <td>Discoidin domain receptor</td>\n",
       "      <td>Is an ortholog of human COL13A1 (collagen type...</td>\n",
       "      <td>Is an ortholog of human DDR1 (discoidin domain...</td>\n",
       "      <td>Literature supported</td>\n",
       "      <td>ECM-component</td>\n",
       "      <td>DOI: 10.1016/j.mcn.2018.03.003</td>\n",
       "      <td>wormbase: col-99 is located in the extracellul...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>WBGene00003738</td>\n",
       "      <td>WBGene00004215</td>\n",
       "      <td>nid-1</td>\n",
       "      <td>ptp-3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>46</td>\n",
       "      <td>Cell adhesion</td>\n",
       "      <td>Nidogen</td>\n",
       "      <td>LAR-RPTP</td>\n",
       "      <td>Is an ortholog of human NID1 (nidogen 1) and N...</td>\n",
       "      <td>Is an ortholog of human PTPRD (protein tyrosin...</td>\n",
       "      <td>Literature supported</td>\n",
       "      <td>ECM-component</td>\n",
       "      <td>WormBook</td>\n",
       "      <td>wormbase: nid-1 is located in the extracellula...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Ligand_WB     Receptor_WB Ligand_symbol Receptor_symbol  score  index  \\\n",
       "1  WBGene00002881  WBGene00006894       let-756           ver-1    1.0      7   \n",
       "2  WBGene00000527  WBGene00001687         cle-1           gpn-1    1.0     13   \n",
       "3  WBGene00002280  WBGene00003930         let-2           pat-3    1.0     26   \n",
       "6  WBGene00000674  WBGene00016104        col-99           ddr-1    1.0     35   \n",
       "8  WBGene00003738  WBGene00004215         nid-1           ptp-3    1.0     46   \n",
       "\n",
       "                       LR Function L Function  \\\n",
       "1  Canonical RTK-Ras-ERK signaling        FGF   \n",
       "2                    Cell adhesion   Collagen   \n",
       "3                    Cell adhesion   Collagen   \n",
       "6                    Cell adhesion   Collagen   \n",
       "8                    Cell adhesion    Nidogen   \n",
       "\n",
       "                                R Function  \\\n",
       "1            fms-related tyrosine kinase 1   \n",
       "2  Glypican (co-receptor) Frizzled homolog   \n",
       "3                                 Integrin   \n",
       "6                Discoidin domain receptor   \n",
       "8                                 LAR-RPTP   \n",
       "\n",
       "                   Ligand_desc_WormBase_versionWS277  \\\n",
       "1  Is an ortholog of human FGF16 (fibroblast grow...   \n",
       "2  Is an ortholog of human COL15A1 (collagen type...   \n",
       "3  Is an ortholog of human COL4A5 (collagen type ...   \n",
       "6  Is an ortholog of human COL13A1 (collagen type...   \n",
       "8  Is an ortholog of human NID1 (nidogen 1) and N...   \n",
       "\n",
       "                 Receptor_desc_WormBase_versionWS277  \\\n",
       "1  Is an ortholog of human FLT1 (fms related rece...   \n",
       "2  Is an ortholog of human GPC1 (glypican 1) and ...   \n",
       "3  Is an ortholog of human ITGB1 (integrin subuni...   \n",
       "6  Is an ortholog of human DDR1 (discoidin domain...   \n",
       "8  Is an ortholog of human PTPRD (protein tyrosin...   \n",
       "\n",
       "                Pair_confidence  Location_type  \\\n",
       "1  Putative based on literature       Secreted   \n",
       "2          Literature supported  ECM-component   \n",
       "3          Literature supported  ECM-component   \n",
       "6          Literature supported  ECM-component   \n",
       "8          Literature supported  ECM-component   \n",
       "\n",
       "                                 Confidence_evidence  \\\n",
       "1  Orthology, protein-protein interaction (STRING...   \n",
       "2                                           WormBook   \n",
       "3                              10.1083/jcb.201903124   \n",
       "6                     DOI: 10.1016/j.mcn.2018.03.003   \n",
       "8                                           WormBook   \n",
       "\n",
       "                                   Location_evidence  \n",
       "1  wormbase: let-756 is found in the cytoplasm;ex...  \n",
       "2  wormbase: cle-1 is found in the extracellular ...  \n",
       "3  Wormbase: let-2 is located in the extracellula...  \n",
       "6  wormbase: col-99 is located in the extracellul...  \n",
       "8  wormbase: nid-1 is located in the extracellula...  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr_pairs.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# LR information"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "labels_dict = dict()\n",
    "for pair in lr_pairs.iterrows():\n",
    "    original = (pair[1]['Ligand_WB'], pair[1]['Receptor_WB'])\n",
    "    new = pair[1]['Ligand_symbol']+' / '+pair[1]['Receptor_symbol']\n",
    "    labels_dict[original] = new "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "functions = ['Cell migration', 'Wnt signaling', 'Cell adhesion', 'Notch signaling',\n",
    "       'Insulin signaling', 'TGF-B signaling', 'Hedgehog signaling',\n",
    "       'Mechanosensory mechanism', 'Canonical RTK-Ras-ERK signaling',\n",
    "       'Neuronal communication', 'Eph receptor signaling',\n",
    "       'Epidermal development', 'Lipid homeostasis', 'Immune response',\n",
    "       'Trypsin-like proteolysis', 'Longevity', 'PCP pathway',\n",
    "       'Receptor-Mediated-Endocytosis', 'Stress response', 'Apoptosis']\n",
    "function_colors = c2c.plotting.get_colors_from_labels(functions, cmap='tab20')\n",
    "\n",
    "func_color_dict = dict()\n",
    "row_cols = []\n",
    "for idx, row in lr_pairs.iterrows():\n",
    "    name = str(row['Ligand_symbol']) + ' / ' + str(row['Receptor_symbol'])\n",
    "    func = str(row['LR Function'])\n",
    "    func_color_dict[name] = function_colors[func]\n",
    "    row_cols.append((name, function_colors[func]))\n",
    "row_cols = pd.DataFrame.from_records(row_cols, columns=['LR', 'Function']).set_index('LR')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Cell-Cell Interactions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Setups**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_folder = '../data/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "files = dict()\n",
    "files['rnaseq'] = data_folder + '/RNA-Seq/Celegans_RNASeqData_Cell.xlsx'\n",
    "files['metadata'] = data_folder + '/RNA-Seq/Celegans_cell_metadata.tsv'\n",
    "files['ppi'] = data_folder + '/PPI-Networks/Celegans-GA-BrayCurtis-Selected-LR-pairs.csv'\n",
    "files['phenotype'] = data_folder + '/Digital-3D-Map/Celegans_Physical_Distances_Min.csv'\n",
    "files['output_folder'] = output_folder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "rnaseq_setup = dict()\n",
    "rnaseq_setup['gene_col'] = 'gene_id'\n",
    "rnaseq_setup['drop_nangenes'] = True\n",
    "rnaseq_setup['log_transform'] = False\n",
    "\n",
    "meta_setup = dict()\n",
    "meta_setup['sample_col'] = '#SampleID'\n",
    "meta_setup['group_col'] = 'Groups'\n",
    "\n",
    "ppi_setup = dict()\n",
    "ppi_setup['protein_cols'] = ['Ligand', 'Receptor']\n",
    "\n",
    "cutoff_setup = dict()\n",
    "cutoff_setup['type'] = 'constant_value'\n",
    "cutoff_setup['parameter'] = 10 # TPM\n",
    "\n",
    "analysis_setup = dict()\n",
    "analysis_setup['communication_score'] = 'expression_thresholding'\n",
    "analysis_setup['cci_score'] = 'bray_curtis'\n",
    "analysis_setup['cci_type'] = 'undirected'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**RNA-seq**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Opening RNAseq datasets from ../data//RNA-Seq/Celegans_RNASeqData_Cell.xlsx\n",
      "../data//RNA-Seq/Celegans_RNASeqData_Cell.xlsx was correctly loaded\n"
     ]
    }
   ],
   "source": [
    "rnaseq_data = c2c.io.load_rnaseq(rnaseq_file=files['rnaseq'],\n",
    "                                 gene_column=rnaseq_setup['gene_col'],\n",
    "                                 drop_nangenes=rnaseq_setup['drop_nangenes'],\n",
    "                                 log_transformation=rnaseq_setup['log_transform'],\n",
    "                                 format='auto')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Metadata**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "../data//RNA-Seq/Celegans_cell_metadata.tsv was correctly loaded\n"
     ]
    }
   ],
   "source": [
    "meta = c2c.io.load_metadata(metadata_file=files['metadata'],\n",
    "                            cell_labels=rnaseq_data.columns,\n",
    "                            format='auto')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**PPI Network**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Opening PPI datasets from ../data//PPI-Networks/Celegans-GA-BrayCurtis-Selected-LR-pairs.csv\n",
      "../data//PPI-Networks/Celegans-GA-BrayCurtis-Selected-LR-pairs.csv was correctly loaded\n",
      "Removing bidirectionality of PPI network\n",
      "Simplying PPI network\n"
     ]
    }
   ],
   "source": [
    "ppi_data = c2c.io.load_ppi(ppi_file=files['ppi'] ,\n",
    "                           interaction_columns=['Ligand_WB', 'Receptor_WB'],\n",
    "                           sort_values=['LR Function', 'index'],\n",
    "                           #score='score',\n",
    "                           format='auto')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ligands: 30\n",
      "Receptors: 29\n",
      "Pairs: 37\n"
     ]
    }
   ],
   "source": [
    "print('Ligands: {}\\nReceptors: {}\\nPairs: {}'.format(len(ppi_data['A'].unique()),\n",
    "                                                     len(ppi_data['B'].unique()),\n",
    "                                                     len(ppi_data[['A', 'B']].values)\n",
    "                                                    )\n",
    "     )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Analysis**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "interaction_space = c2c.analysis.BulkInteractions(rnaseq_data=rnaseq_data,\n",
    "                                                  ppi_data=ppi_data,\n",
    "                                                  metadata=meta,\n",
    "                                                  interaction_columns=('A', 'B'),\n",
    "                                                  communication_score=analysis_setup['communication_score'],\n",
    "                                                  cci_score=analysis_setup['cci_score'],\n",
    "                                                  cci_type=analysis_setup['cci_type'],\n",
    "                                                  sample_col='#SampleID',\n",
    "                                                  group_col='Groups',\n",
    "                                                  expression_threshold=cutoff_setup['parameter'],\n",
    "                                                  complex_sep=None,\n",
    "                                                  verbose=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "interaction_space.compute_pairwise_communication_scores(verbose=False,\n",
    "                                                        ref_ppi_data=ppi_data,\n",
    "                                                        cci_type='directed')\n",
    "interaction_matrix = interaction_space.interaction_space.interaction_elements['communication_matrix']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "interaction_matrix.index = interaction_matrix.index.map(labels_dict)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Body sections of *C. elegans*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Assign Major Cell type to each Cell type**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "atlas['Major Cell Type'] = atlas['Cell Type'].apply(lambda x: meta.loc[meta['#SampleID'] == x] \\\n",
    "                                                                  ['Groups'].values[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Antero-posterior"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Coordinates Information**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "min_y = atlas['Y'].min()\n",
    "max_y = atlas['Y'].max()\n",
    "range_y =  max_y - min_y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Min position in Y-axis: 16.674\n",
      "Max position in Y-axis: 221.966\n",
      "Range in Y-axis (worm length in micrometers): 205.292\n"
     ]
    }
   ],
   "source": [
    "print('Min position in Y-axis: {}'.format(min_y))\n",
    "print('Max position in Y-axis: {}'.format(max_y))\n",
    "print('Range in Y-axis (worm length in micrometers): {}'.format(range_y))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Body regions**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "body_regions = [min_y, 84, 189, max_y]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Generate Bins**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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C7g6HM4Dnhn7UftmZMzf8uwzOKxiM084kr0qylcEvC7+x1vWNQ5IAVwMHq+rTQ13Nn1M+obrGkvwqg6t1GLz+4R+q6lNJXg/cCPwy8ARwflUt9RdmzUhyPXAWg1exPgNcCvwj84xN9x/u3zK4A+SHwPuranocda+1BcbpLAZTMgU8Dvzh88GU5JPABxjcPfLhqvrqmhc9BkneBvwbcD/w0675Ewzm3Zs+pwx3SWqQ0zKS1CDDXZIaZLhLUoMMd0lqkOEuSQ0y3CWpQYa7JDXo/wBiUPBK/GSeDAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "counts = plt.hist(atlas['Y'].values, \n",
    "                  bins=body_regions\n",
    "                 )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "counts[1][-1] += 1.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    332.000000\n",
       "mean      13.028699\n",
       "std        2.578641\n",
       "min        8.259000\n",
       "25%       11.123250\n",
       "50%       12.818000\n",
       "75%       15.157500\n",
       "max       18.027000\n",
       "Name: Z, dtype: float64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "atlas['Z'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Assign Bins**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "atlas['Bins'] = np.digitize(atlas['Y'].values, counts[1], right=False)    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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>Cell</th>\n",
       "      <th>Lineage Name</th>\n",
       "      <th>Description</th>\n",
       "      <th>Cell2</th>\n",
       "      <th>Name2</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>Z</th>\n",
       "      <th>Cell Type</th>\n",
       "      <th>Major Cell Type</th>\n",
       "      <th>Bins</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ADEshL</td>\n",
       "      <td>AB arppaaaa</td>\n",
       "      <td>Anterior deirid sheath</td>\n",
       "      <td>ADESHL</td>\n",
       "      <td>ABARPPAAAA</td>\n",
       "      <td>11.134</td>\n",
       "      <td>84.340</td>\n",
       "      <td>12.852</td>\n",
       "      <td>Am/PH_sheath_cells</td>\n",
       "      <td>Excretory/Socket/Sheath cells</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ADEshR</td>\n",
       "      <td>AB arpppaaa</td>\n",
       "      <td>Anterior deirid sheath</td>\n",
       "      <td>ADESHR</td>\n",
       "      <td>ABARPPPAAA</td>\n",
       "      <td>16.990</td>\n",
       "      <td>85.075</td>\n",
       "      <td>13.130</td>\n",
       "      <td>Am/PH_sheath_cells</td>\n",
       "      <td>Excretory/Socket/Sheath cells</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ALML</td>\n",
       "      <td>AB.arppaappa</td>\n",
       "      <td>Anterior lateral microtubule cell, touch receptor</td>\n",
       "      <td>ALML</td>\n",
       "      <td>ABARPPAAPPA</td>\n",
       "      <td>11.759</td>\n",
       "      <td>120.005</td>\n",
       "      <td>16.090</td>\n",
       "      <td>Touch_receptor_neurons</td>\n",
       "      <td>Neurons</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ALMR</td>\n",
       "      <td>AB arpppappa</td>\n",
       "      <td>Anterior lateral microtubule cell, touch receptor</td>\n",
       "      <td>ALMR</td>\n",
       "      <td>ABARPPPAPPA</td>\n",
       "      <td>16.467</td>\n",
       "      <td>119.037</td>\n",
       "      <td>15.870</td>\n",
       "      <td>Touch_receptor_neurons</td>\n",
       "      <td>Neurons</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ALNL</td>\n",
       "      <td>AB plapappppap</td>\n",
       "      <td>Neuron associated with ALM</td>\n",
       "      <td>ALNL</td>\n",
       "      <td>ABPLAPAPPPPAP</td>\n",
       "      <td>12.884</td>\n",
       "      <td>199.753</td>\n",
       "      <td>15.437</td>\n",
       "      <td>Oxygen_sensory_neurons</td>\n",
       "      <td>Neurons</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Cell    Lineage Name                                        Description  \\\n",
       "0  ADEshL     AB arppaaaa                             Anterior deirid sheath   \n",
       "1  ADEshR     AB arpppaaa                             Anterior deirid sheath   \n",
       "2    ALML    AB.arppaappa  Anterior lateral microtubule cell, touch receptor   \n",
       "3    ALMR    AB arpppappa  Anterior lateral microtubule cell, touch receptor   \n",
       "4    ALNL  AB plapappppap                         Neuron associated with ALM   \n",
       "\n",
       "    Cell2          Name2       X        Y       Z               Cell Type  \\\n",
       "0  ADESHL     ABARPPAAAA  11.134   84.340  12.852      Am/PH_sheath_cells   \n",
       "1  ADESHR     ABARPPPAAA  16.990   85.075  13.130      Am/PH_sheath_cells   \n",
       "2    ALML    ABARPPAAPPA  11.759  120.005  16.090  Touch_receptor_neurons   \n",
       "3    ALMR    ABARPPPAPPA  16.467  119.037  15.870  Touch_receptor_neurons   \n",
       "4    ALNL  ABPLAPAPPPPAP  12.884  199.753  15.437  Oxygen_sensory_neurons   \n",
       "\n",
       "                 Major Cell Type  Bins  \n",
       "0  Excretory/Socket/Sheath cells     2  \n",
       "1  Excretory/Socket/Sheath cells     2  \n",
       "2                        Neurons     2  \n",
       "3                        Neurons     2  \n",
       "4                        Neurons     3  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "atlas.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Extract Spatial use of LRs**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "lr_list = interaction_matrix.index #.map(labels_dict)\n",
    "spatial_lr = pd.DataFrame(index=lr_list)\n",
    "spatial_enr = pd.DataFrame(index=lr_list)\n",
    "\n",
    "bin_interactions = dict()\n",
    "for group, df in atlas.groupby('Bins'):\n",
    "    # Get pairwise interactions per bin\n",
    "    cells = df['Cell Type'].values.tolist()\n",
    "    #bin_interactions['Bin-{}'.format(group)] = list(itertools.product(cells, cells))\n",
    "    bin_interactions['Bin-{}'.format(group)] = c2c.core.interaction_space.generate_pairs(cells=cells,\n",
    "                                                                                         cci_type='directed',\n",
    "                                                                                         self_interaction=True,\n",
    "                                                                                         remove_duplicates=False\n",
    "                                                                                        )\n",
    "    # Extract active interactions per bin\n",
    "    tmp_df = pd.DataFrame()\n",
    "    tmp_interactions = []\n",
    "    for interaction in bin_interactions['Bin-{}'.format(group)]:\n",
    "        tmp_interactions.append(interaction[0]+';'+interaction[1])\n",
    "    tmp_df = interaction_matrix.loc[:, tmp_interactions]\n",
    "    if len(tmp_df) != 0:\n",
    "        spatial_lr['Bin-{}'.format(group)] = tmp_df.mean(axis=1).values\n",
    "        spatial_enr['Bin-{}'.format(group)] = tmp_df.sum(axis=1).values\n",
    "    else:\n",
    "        spatial_lr['Bin-{}'.format(group)] = [0]*len(lr_list)\n",
    "        spatial_enr['Bin-{}'.format(group)] = [0]*len(lr_list)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Compute LR enrichment per bin**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "across_body = True # Enrichment across body (True) or across bins (False)\n",
    "\n",
    "if across_body:\n",
    "    N = sum([len(v) for v in bin_interactions.values()])\n",
    "\n",
    "    active_lrs = spatial_enr.sum(axis=1).to_dict()\n",
    "\n",
    "    spatial_pvals = spatial_enr.copy()\n",
    "    spatial_pvals2 = spatial_enr.copy()\n",
    "\n",
    "    n = dict()\n",
    "    for k, v in bin_interactions.items():\n",
    "        n[k] = len(v)\n",
    "\n",
    "        def row_fn(row):\n",
    "            return c2c.stats.fisher_representation(n[k], row[k], N, active_lrs[row.name])\n",
    "        spatial_pvals[k] = spatial_enr.apply(lambda x: row_fn(x)['pval'][1], axis=1)\n",
    "        spatial_pvals2[k] = spatial_enr.apply(lambda x: row_fn(x)['pval'][0], axis=1)\n",
    "else:\n",
    "    N = spatial_enr.sum(axis=1).sum()\n",
    "\n",
    "    active_lrs = spatial_enr.sum(axis=1).to_dict()\n",
    "\n",
    "    spatial_pvals = spatial_enr.copy()\n",
    "    spatial_pvals2 = spatial_enr.copy()\n",
    "\n",
    "    n = dict()\n",
    "    for k, v in bin_interactions.items():\n",
    "        n[k] = spatial_enr.sum(axis=0)[k]\n",
    "\n",
    "        def row_fn(row):\n",
    "            return c2c.stats.fisher_representation(n[k], row[k], N, active_lrs[row.name])\n",
    "        spatial_pvals[k] = spatial_enr.apply(lambda x: row_fn(x)['pval'][1], axis=1)\n",
    "        spatial_pvals2[k] = spatial_enr.apply(lambda x: row_fn(x)['pval'][0], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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>Bin-1</th>\n",
       "      <th>Bin-2</th>\n",
       "      <th>Bin-3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>let-756 / ver-1</th>\n",
       "      <td>196.0</td>\n",
       "      <td>168.0</td>\n",
       "      <td>42.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cle-1 / gpn-1</th>\n",
       "      <td>570.0</td>\n",
       "      <td>3024.0</td>\n",
       "      <td>132.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>let-2 / pat-3</th>\n",
       "      <td>21456.0</td>\n",
       "      <td>17423.0</td>\n",
       "      <td>1850.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>col-99 / ddr-1</th>\n",
       "      <td>3906.0</td>\n",
       "      <td>2600.0</td>\n",
       "      <td>240.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nid-1 / ptp-3</th>\n",
       "      <td>6048.0</td>\n",
       "      <td>11004.0</td>\n",
       "      <td>450.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Bin-1    Bin-2   Bin-3\n",
       "let-756 / ver-1    196.0    168.0    42.0\n",
       "cle-1 / gpn-1      570.0   3024.0   132.0\n",
       "let-2 / pat-3    21456.0  17423.0  1850.0\n",
       "col-99 / ddr-1    3906.0   2600.0   240.0\n",
       "nid-1 / ptp-3     6048.0  11004.0   450.0"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Number of pairs of cells using each LR pair per bin\n",
    "spatial_enr.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Bin-1': 22201, 'Bin-2': 17689, 'Bin-3': 2500}"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#  Number of pairs of cells per Bin\n",
    "n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**FDR correction**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "from statsmodels.stats.multitest import fdrcorrection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "fdr = 0.01"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "rej, adj_pvals = fdrcorrection(spatial_pvals.values.flatten(), alpha=fdr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "spatial_pvals = pd.DataFrame(adj_pvals.reshape(spatial_pvals.shape),\n",
    "                             index=spatial_pvals.index,\n",
    "                             columns=spatial_pvals.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "rej2, adj_pvals2 = fdrcorrection(spatial_pvals2.values.flatten(), alpha=fdr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "spatial_pvals2 = pd.DataFrame(adj_pvals2.reshape(spatial_pvals2.shape),\n",
    "                             index=spatial_pvals2.index,\n",
    "                             columns=spatial_pvals2.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "raw_pval = False\n",
    "if raw_pval == False:\n",
    "    for k in bin_interactions.keys():\n",
    "        spatial_pvals[k] = spatial_pvals[k].apply(lambda x: 1 if x < fdr else 0)\n",
    "        spatial_pvals2[k] = spatial_pvals2[k].apply(lambda x: -1. if x < fdr else 0)\n",
    "else:\n",
    "    for k in bin_interactions.keys():\n",
    "        spatial_pvals[k] = spatial_pvals[k].apply(lambda x: -1*np.log10(x) if x != 0 else -1*np.log10(1e-6))\n",
    "        spatial_pvals2[k] = spatial_pvals2[k].apply(lambda x: -1*np.log10(x) if x != 0 else -1*np.log10(1e-6))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Colors from figure S14 in C elegans paper (cell type expression data)\n",
    "lut = {'Coelomocytes': (0.6509803921568628, 0.33725490196078434, 0.1568627450980392), # Brown\n",
    "       'Neurons': (0.596078431372549, 0.3058823529411765, 0.6392156862745098), # Purple\n",
    "       'Hypodermal/rectal cells': (0.30196078431372547, 0.6862745098039216, 0.2901960784313726), # Green\n",
    "       'Pharyngeal cells': (0.21568627450980393, 0.49411764705882355, 0.7215686274509804), # Blue\n",
    "       'Intestine': (1.0, 1.0, 0.2), # Yellow\n",
    "       'Body/muscular cells': (0.8941176470588236, 0.10196078431372549, 0.10980392156862745), # Red\n",
    "       'Excretory/Socket/Sheath cells': (1.0, 0.4980392156862745, 0.0), # Orange\n",
    "       'Sexual cells': (0.9686274509803922, 0.5058823529411764, 0.7490196078431373)} # Pink"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "fontname = 'Lato'\n",
    "tick_size = 12\n",
    "axis_size = 16\n",
    "legend_size = 14\n",
    "\n",
    "inline_rc = dict(mpl.rcParams)\n",
    "#plt.rcParams[\"font.family\"] = fontname"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Worm & Bins Visualization**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/earmingol/opt/anaconda3/envs/c2c_dev/lib/python3.7/_collections_abc.py:841: MatplotlibDeprecationWarning: \n",
      "The savefig.frameon rcparam was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
      "  self[key] = other[key]\n",
      "/Users/earmingol/opt/anaconda3/envs/c2c_dev/lib/python3.7/_collections_abc.py:841: MatplotlibDeprecationWarning: \n",
      "The text.latex.unicode rcparam was deprecated in Matplotlib 3.0 and will be removed in 3.2.\n",
      "  self[key] = other[key]\n",
      "/Users/earmingol/opt/anaconda3/envs/c2c_dev/lib/python3.7/_collections_abc.py:841: MatplotlibDeprecationWarning: \n",
      "The verbose.fileo rcparam was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
      "  self[key] = other[key]\n",
      "/Users/earmingol/opt/anaconda3/envs/c2c_dev/lib/python3.7/_collections_abc.py:841: MatplotlibDeprecationWarning: \n",
      "The verbose.level rcparam was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
      "  self[key] = other[key]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mask = []\n",
    "\n",
    "NUM_COLORS = len(atlas['Cell Type'].unique())\n",
    "cm = plt.get_cmap('tab20') # gist_rainbow\n",
    "fig = plt.figure(figsize=(10, 9))\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "\n",
    "\n",
    "xx, zz = np.meshgrid(range(41), range(41))\n",
    "for bin_val in counts[1]:\n",
    "    ax.plot_surface(xx, bin_val, zz, alpha=0.2, color='red')\n",
    "\n",
    "# PLOT BY CELL TYPES\n",
    "#for i, cell in enumerate(atlas['Cell Type'].unique()):\n",
    "#    if cell not in mask:\n",
    "#        cell_type = atlas.loc[atlas['Cell Type'] == cell]\n",
    "#        ax.scatter(cell_type['X'], cell_type['Y'], cell_type['Z'], color=cm(1.*i/NUM_COLORS), s=60, label=cell)\n",
    "\n",
    "# PLOT BY CELL GROUPS\n",
    "for i, cell_type in enumerate(sorted(meta['Groups'].unique())):\n",
    "    cells = meta.loc[meta.Groups == cell_type]['#SampleID'].values\n",
    "    cell_cords = atlas.loc[atlas['Cell Type'].isin(cells)]\n",
    "    ax.scatter(cell_cords['X'],\n",
    "               cell_cords['Y'],\n",
    "               cell_cords['Z'],\n",
    "               color=lut[cell_type],\n",
    "               s=60,\n",
    "               label=cell_type,\n",
    "               alpha=0.6)\n",
    "\n",
    "             \n",
    "ax.set_xlim((0, 40))\n",
    "ax.set_ylim((min_y, max_y)) # (0, 300)\n",
    "ax.set_zlim((0, 40))\n",
    "\n",
    "\n",
    "ax.set_xlabel('X', fontsize=axis_size)\n",
    "ax.set_ylabel('Y', fontsize=axis_size)\n",
    "ax.set_zlabel('Z', fontsize=axis_size)\n",
    "\n",
    "#ax.grid(False)\n",
    "ax.set_xticks([])\n",
    "ax.set_yticks([])\n",
    "ax.set_zticks([])\n",
    "#ax.set_xticklabels(ax.get_xmajorticklabels(), fontsize = tick_size)\n",
    "\n",
    "lgd = ax.legend(loc='upper center', bbox_to_anchor=(0.5, 1.15),\n",
    "                ncol=2, fancybox=True, shadow=True, fontsize=legend_size)\n",
    "ax.view_init(10, 0.5)\n",
    "\n",
    "mpl.rcParams.update(inline_rc)\n",
    "plt.savefig(output_folder + '/Celegans-3D-Atlas-Dissected.svg', dpi=300,\n",
    "                bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Cells in each Bin**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "# The ones without 3D localization of cells\n",
    "excluded_cells = ['Distal_tip_cells',\n",
    "                  'Sex_myoblasts',\n",
    "                  'Socket_cells',\n",
    "                  'Vulval_precursors',\n",
    "                  'flp-1(+)_interneurons']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "template_cols = spatial_lr.columns\n",
    "template_idx = meta.sort_values(by=['Groups', '#SampleID'])['#SampleID']\n",
    "data = np.zeros((len(template_idx), len(template_cols)))\n",
    "template = pd.DataFrame(data, columns=template_cols, index=template_idx)\n",
    "template.index.name = ''\n",
    "for bin_id, df in atlas.groupby('Bins'):\n",
    "    update_df = pd.DataFrame()\n",
    "    update_df['Bin-{}'.format(bin_id)] = df.groupby('Cell Type')['Cell Type'].count()\n",
    "    template.loc[update_df.index, 'Bin-{}'.format(bin_id)] = df.groupby('Cell Type')['Cell Type'].count()\n",
    "    \n",
    "template = template.loc[~template.index.isin(excluded_cells)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "cell_type_colors = []\n",
    "for idx, row in meta.sort_values(by=['Groups', '#SampleID']).iterrows():\n",
    "    if row['#SampleID'] not in excluded_cells:\n",
    "        cell_type_colors.append(lut[row['Groups']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x720 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#with sns.axes_style(\"white\"):\n",
    "fig, axes = plt.subplots(1, len(template_cols), sharey='all', sharex ='all', figsize=(16,10)) #(20,10)\n",
    "ind = np.arange(template.shape[0])\n",
    "count = 0\n",
    "idx_map = {'Bin-1' : 'Head', 'Bin-2': 'Mid-body', 'Bin-3': 'Tail'}\n",
    "for idx, col in template.T.iterrows():\n",
    "    bars = axes[count].barh(ind, col.values, color=cell_type_colors)\n",
    "    axes[count].set_xlabel(idx_map[idx] + '\\n{} Cells'.format(int(col.sum())), fontsize=26.5)\n",
    "    axes[count].tick_params(axis='x', which='major', labelsize=22) # Ex 14\n",
    "    axes[count].tick_params(axis='y', which='major', labelsize=26.5)\n",
    "    axes[count].set_yticks(ind) \n",
    "    axes[count].set_yticklabels(template.index.str.replace('_', ' '))\n",
    "    if count != 0:\n",
    "        axes[count].yaxis.set_ticks_position('none') \n",
    "    count += 1\n",
    "\n",
    "plt.xlim((0,50))\n",
    "plt.xticks(np.arange(0,50,10))\n",
    "plt.ylim((-0.5, len(template.index)-0.5))\n",
    "plt.gca().invert_yaxis()\n",
    "\n",
    "plt.subplots_adjust(wspace = 0.1)\n",
    "plt.savefig(output_folder + '/Spatial-Cell-Distribution.svg',\n",
    "            dpi=300,\n",
    "            bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fdd4e436f10>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "atlas.groupby('Cell Type')['Cell Type'].count().plot(kind='bar')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Spatial LRs**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "import scipy.cluster.hierarchy as hc\n",
    "import scipy.spatial as sp\n",
    "from sklearn.metrics import pairwise_distances"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/earmingol/opt/anaconda3/envs/c2c_dev/lib/python3.7/site-packages/ipykernel_launcher.py:11: ClusterWarning: scipy.cluster: The symmetric non-negative hollow observation matrix looks suspiciously like an uncondensed distance matrix\n",
      "  # This is added back by InteractiveShellApp.init_path()\n",
      "/Users/earmingol/opt/anaconda3/envs/c2c_dev/lib/python3.7/site-packages/ipykernel_launcher.py:12: ClusterWarning: scipy.cluster: The symmetric non-negative hollow observation matrix looks suspiciously like an uncondensed distance matrix\n",
      "  if sys.path[0] == '':\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x2160 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fontsize = 26\n",
    "\n",
    "\n",
    "X = spatial_pvals + spatial_pvals2\n",
    "X = X[(X.T != 0).any()]\n",
    "if raw_pval == False:\n",
    "    D = pairwise_distances(X, metric='cosine')\n",
    "else:\n",
    "    D = pairwise_distances(X)\n",
    "\n",
    "row_Z = hc.linkage(D, method='ward')\n",
    "opt_row_Z_2 = hc.optimal_leaf_ordering(row_Z, D)\n",
    "\n",
    "X.columns = [idx_map[idx] for idx in X.columns]\n",
    "fig2 = sns.clustermap(X,\n",
    "                      col_cluster=False,\n",
    "                      row_cluster=False,\n",
    "                      row_linkage=opt_row_Z_2,\n",
    "                      cmap='RdBu_r',\n",
    "                      figsize = (10,30),\n",
    "                      linewidths=.5,\n",
    "                      row_colors=row_cols\n",
    "                     )\n",
    "\n",
    "fig2.ax_heatmap.set_yticklabels(fig2.ax_heatmap.yaxis.get_majorticklabels(),\n",
    "                                rotation=0,\n",
    "                                ha='left', \n",
    "                                fontsize=fontsize)\n",
    "fig2.ax_heatmap.set_xticklabels(fig2.ax_heatmap.xaxis.get_majorticklabels(),\n",
    "                                rotation=90,\n",
    "                                fontsize=fontsize*1.5)\n",
    "\n",
    "cbar2 = fig2.ax_heatmap.collections[0].colorbar\n",
    "if raw_pval == False:\n",
    "    cbar_label = 'Significance'\n",
    "else:\n",
    "    cbar_label = '$-log_{10}$(q-value)'\n",
    "cbar2.ax.set_ylabel(cbar_label, fontsize=fontsize)\n",
    "cbar2.ax.tick_params(labelsize=fontsize*0.8)\n",
    "cbar2.ax.yaxis.set_label_position(\"left\")\n",
    "\n",
    "plt.savefig(output_folder + '/Spatial-LRs-EnrDep-pvals.svg',\n",
    "            dpi=300,\n",
    "            bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sns.palplot(function_colors.values())\n",
    "for i, text in enumerate(function_colors.keys()):\n",
    "    plt.text(i, 0.6, text, rotation=90, horizontalalignment='center', verticalalignment='top',fontsize=14)\n",
    "    \n",
    "plt.savefig(output_folder + '/Spatial-LR-Functions.svg',\n",
    "            dpi=300,\n",
    "            bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}