Excel_add_calculated_values.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Excel._add_calculated_values(self)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.5/dist-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  from ._conv import register_converters as _register_converters\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>gene_symbol</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>genes</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ENSMUSG00000000567</th>\n",
       "      <td>Gnai3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSMUSG00000000568</th>\n",
       "      <td>Pbsn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSMUSG00000000569</th>\n",
       "      <td>Cdc45l</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSMUSG00000000570</th>\n",
       "      <td>H19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSMUSG00000000571</th>\n",
       "      <td>Scml2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   gene_symbol\n",
       "genes                         \n",
       "ENSMUSG00000000567       Gnai3\n",
       "ENSMUSG00000000568        Pbsn\n",
       "ENSMUSG00000000569      Cdc45l\n",
       "ENSMUSG00000000570         H19\n",
       "ENSMUSG00000000571       Scml2"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import os, sys\n",
    "sys.path.append('/home/dolley/gear/lib')\n",
    "import gear.datasetuploader as datasetuploader\n",
    "\n",
    "test_file = '/home/dolley/gear/tests/base_template.xlsx'\n",
    "dataset = datasetuploader.DatasetUploader.upload_dataset('excel')\n",
    "# adata = dataset._read_file(test_file)\n",
    "# adata\n",
    "dataset._read_file(test_file)\n",
    "dataset.adata.var.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<gear.exceluploader.ExcelUploader at 0x7fda2409cac8>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# adata.var.head()\n",
    "# adata._add_calculated_values()\n",
    "adata = dataset.adata\n",
    "dataset._add_calculated_values(adata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[72., 79., 40., ..., 87., 11., 84.],\n",
       "       [92., 15., 15., ..., 81., 50.,  4.],\n",
       "       [51., 66., 94., ..., 41., 75., 58.],\n",
       "       ...,\n",
       "       [25.,  7., 60., ..., 79., 83., 74.],\n",
       "       [40., 82., 49., ..., 82., 70., 80.],\n",
       "       [81., 14., 43., ...,  6., 34., 18.]], dtype=float32)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = adata.X\n",
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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_type</th>\n",
       "      <th>condition</th>\n",
       "      <th>replicate</th>\n",
       "      <th>time_point</th>\n",
       "      <th>time_unit</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>observations</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>obs-ctrl-1-0h</th>\n",
       "      <td>utricle</td>\n",
       "      <td>control</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>hour</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>obs-ctrl-2-0h</th>\n",
       "      <td>utricle</td>\n",
       "      <td>control</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>hour</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>obs-ctrl-3-0h</th>\n",
       "      <td>utricle</td>\n",
       "      <td>control</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>hour</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>obs-trt-1-0h</th>\n",
       "      <td>utricle</td>\n",
       "      <td>treated</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>hour</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>obs-trt-2-0h</th>\n",
       "      <td>utricle</td>\n",
       "      <td>treated</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>hour</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              cell_type condition  replicate  time_point time_unit\n",
       "observations                                                      \n",
       "obs-ctrl-1-0h   utricle   control          1           0      hour\n",
       "obs-ctrl-2-0h   utricle   control          2           0      hour\n",
       "obs-ctrl-3-0h   utricle   control          3           0      hour\n",
       "obs-trt-1-0h    utricle   treated          1           0      hour\n",
       "obs-trt-2-0h    utricle   treated          2           0      hour"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obs = adata.obs\n",
    "obs.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 'replicate' column index = 2. Use this if not hardcoding the index\n",
    "# obs.columns.get_loc('replicate')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Get replicate column into np.array\n",
    "# replicates = obs.iloc[:, 2]\n",
    "\n",
    "#DO THIS INSTEAD of the above 2 lines:\n",
    "replicates = obs.loc[:, 'replicate']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3, 3, 3, 3, 3, 3]\n"
     ]
    }
   ],
   "source": [
    "# Build list of total number of replicates for each group\n",
    "replicate_count = list()\n",
    "prior_rep = None\n",
    "for r in replicates:\n",
    "    if prior_rep is None or r > prior_rep:\n",
    "        prior_rep = r\n",
    "    else:\n",
    "        replicate_count.append(prior_rep)\n",
    "        prior_rep = None\n",
    "\n",
    "replicate_count.append(prior_rep)\n",
    "    \n",
    "print(replicate_count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 72.  92.  51.  93.   1.  46.   0.  33.  46.  75.  56.  28.  90. 100.\n",
      "   7.  25.  40.  81.]\n",
      "(18, 100)\n"
     ]
    }
   ],
   "source": [
    "replicate_vals = X[:,0] #TODO: iterate over all rows\n",
    "print(replicate_vals)\n",
    "print(X.shape)\n",
    "col_count, row_count = X.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "#\n",
    "# THIS ALL WORKS. THE 'In' BELOW IS TRYING TO IMPROVE THE double counter of the inner-most loop (3-20-18)\n",
    "#\n",
    "# import numpy as np\n",
    "\n",
    "# average_list = list()\n",
    "# std_list = list()                         #TODO TODO Could add this here!\n",
    "# for x in range(row_count):\n",
    "#     replicate_vals = X[:,x]\n",
    "#     averages = list()\n",
    "#     std_devs = list()                     #TODO TODO Could add this here!\n",
    "#     start = 0\n",
    "#     end = 0\n",
    "#     for total_rep in replicate_count:\n",
    "#     #     end += total_rep\n",
    "#     #     print(replicate_vals[start:end])\n",
    "#     #     start += total_rep\n",
    "#     #     print(\"total_rep: \", total_rep, \"start: \", total_rep, \"end: \", end)\n",
    "#         end += total_rep\n",
    "\n",
    "#         values = replicate_vals[start:end]\n",
    "#         rep_avg = round( (np.nanmean(values)), 4)\n",
    "#         rep_std = np.nanstd(values)       #TODO TODO Could add this here!\n",
    "#         for x in range(total_rep):\n",
    "#             averages.append(rep_avg)\n",
    "#             std_devs.append(rep_std)\n",
    "#             x += 1\n",
    "\n",
    "#         start += total_rep\n",
    "\n",
    "#     average_list.append(averages)\n",
    "#     std_list.append(std_devs)           #TODO TODO Could add this here!\n",
    "#     x += 1\n",
    "\n",
    "# #Transpose back to match the original .X\n",
    "# Xmean = np.array(average_list).T\n",
    "# print(Xmean)\n",
    "# print(Xmean[:,0])\n",
    "# print(type(Xmean))\n",
    "# print(Xmean.shape)\n",
    "\n",
    "# Xstd = np.array(std_list).T              #TODO TODO Could add this here!\n",
    "# print(Xstd)                              #TODO TODO Could add this here!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "replicate_count list:  [3, 3, 3, 3, 3, 3]\n",
      "[71.6667, 71.6667, 71.6667, 46.6667, 46.6667, 46.6667, 26.3333, 26.3333, 26.3333, 53.0, 53.0, 53.0, 65.6667, 65.6667, 65.6667, 48.6667, 48.6667, 48.6667]\n",
      "[16.7398, 16.7398, 16.7398, 37.5618, 37.5618, 37.5618, 19.362, 19.362, 19.362, 19.3046, 19.3046, 19.3046, 41.684, 41.684, 41.684, 23.669, 23.669, 23.669]\n",
      "[11.8369, 11.8369, 11.8369, 26.5602, 26.5602, 26.5602, 13.691, 13.691, 13.691, 13.6504, 13.6504, 13.6504, 29.475, 29.475, 29.475, 16.7365, 16.7365, 16.7365]\n",
      "[53.3333, 53.3333, 53.3333, 77.0, 77.0, 77.0, 42.0, 42.0, 42.0, 42.3333, 42.3333, 42.3333, 61.3333, 61.3333, 61.3333, 34.3333, 34.3333, 34.3333]\n",
      "[27.6204, 27.6204, 27.6204, 2.9439, 2.9439, 2.9439, 22.8619, 22.8619, 22.8619, 24.2808, 24.2808, 24.2808, 12.6579, 12.6579, 12.6579, 33.8264, 33.8264, 33.8264]\n",
      "[19.5306, 19.5306, 19.5306, 2.0817, 2.0817, 2.0817, 16.1658, 16.1658, 16.1658, 17.1691, 17.1691, 17.1691, 8.9505, 8.9505, 8.9505, 23.9188, 23.9188, 23.9188]\n",
      "[49.6667, 49.6667, 49.6667, 54.6667, 54.6667, 54.6667, 66.3333, 66.3333, 66.3333, 22.6667, 22.6667, 22.6667, 36.6667, 36.6667, 36.6667, 50.6667, 50.6667, 50.6667]\n",
      "[32.968, 32.968, 32.968, 14.8399, 14.8399, 14.8399, 15.4344, 15.4344, 15.4344, 15.9234, 15.9234, 15.9234, 26.234, 26.234, 26.234, 7.0396, 7.0396, 7.0396]\n",
      "[23.3119, 23.3119, 23.3119, 10.4934, 10.4934, 10.4934, 10.9138, 10.9138, 10.9138, 11.2596, 11.2596, 11.2596, 18.5502, 18.5502, 18.5502, 4.9777, 4.9777, 4.9777]\n",
      "[67.0, 67.0, 67.0, 32.3333, 32.3333, 32.3333, 40.0, 40.0, 40.0, 32.0, 32.0, 32.0, 66.3333, 66.3333, 66.3333, 51.3333, 51.3333, 51.3333]\n",
      "[3.7417, 3.7417, 3.7417, 40.7949, 40.7949, 40.7949, 34.2442, 34.2442, 34.2442, 10.4243, 10.4243, 10.4243, 8.0554, 8.0554, 8.0554, 31.6895, 31.6895, 31.6895]\n",
      "[2.6458, 2.6458, 2.6458, 28.8463, 28.8463, 28.8463, 24.2143, 24.2143, 24.2143, 7.3711, 7.3711, 7.3711, 5.696, 5.696, 5.696, 22.4078, 22.4078, 22.4078]\n",
      "[63.3333, 63.3333, 63.3333, 55.6667, 55.6667, 55.6667, 34.0, 34.0, 34.0, 44.0, 44.0, 44.0, 43.3333, 43.3333, 43.3333, 34.3333, 34.3333, 34.3333]\n",
      "[42.7577, 42.7577, 42.7577, 32.1075, 32.1075, 32.1075, 18.3848, 18.3848, 18.3848, 19.2007, 19.2007, 19.2007, 6.8475, 6.8475, 6.8475, 18.6607, 18.6607, 18.6607]\n",
      "[30.2343, 30.2343, 30.2343, 22.7034, 22.7034, 22.7034, 13.0, 13.0, 13.0, 13.5769, 13.5769, 13.5769, 4.8419, 4.8419, 4.8419, 13.1951, 13.1951, 13.1951]\n",
      "[10.3333, 10.3333, 10.3333, 23.6667, 23.6667, 23.6667, 44.3333, 44.3333, 44.3333, 45.0, 45.0, 45.0, 57.0, 57.0, 57.0, 40.6667, 40.6667, 40.6667]\n",
      "[6.3421, 6.3421, 6.3421, 13.5974, 13.5974, 13.5974, 31.5841, 31.5841, 31.5841, 19.2007, 19.2007, 19.2007, 37.8506, 37.8506, 37.8506, 27.8248, 27.8248, 27.8248]\n",
      "[4.4845, 4.4845, 4.4845, 9.6148, 9.6148, 9.6148, 22.3333, 22.3333, 22.3333, 13.5769, 13.5769, 13.5769, 26.7644, 26.7644, 26.7644, 19.6751, 19.6751, 19.6751]\n",
      "[26.3333, 26.3333, 26.3333, 42.6667, 42.6667, 42.6667, 48.6667, 48.6667, 48.6667, 37.0, 37.0, 37.0, 63.6667, 63.6667, 63.6667, 46.3333, 46.3333, 46.3333]\n",
      "[16.5798, 16.5798, 16.5798, 17.5182, 17.5182, 17.5182, 25.3158, 25.3158, 25.3158, 26.9444, 26.9444, 26.9444, 21.4528, 21.4528, 21.4528, 19.9053, 19.9053, 19.9053]\n",
      "[11.7237, 11.7237, 11.7237, 12.3873, 12.3873, 12.3873, 17.901, 17.901, 17.901, 19.0526, 19.0526, 19.0526, 15.1694, 15.1694, 15.1694, 14.0752, 14.0752, 14.0752]\n",
      "[55.0, 55.0, 55.0, 45.6667, 45.6667, 45.6667, 46.6667, 46.6667, 46.6667, 44.3333, 44.3333, 44.3333, 46.6667, 46.6667, 46.6667, 69.0, 69.0, 69.0]\n",
      "[37.8506, 37.8506, 37.8506, 34.7211, 34.7211, 34.7211, 25.5908, 25.5908, 25.5908, 8.34, 8.34, 8.34, 16.8193, 16.8193, 16.8193, 6.532, 6.532, 6.532]\n",
      "[26.7644, 26.7644, 26.7644, 24.5515, 24.5515, 24.5515, 18.0954, 18.0954, 18.0954, 5.8973, 5.8973, 5.8973, 11.893, 11.893, 11.893, 4.6188, 4.6188, 4.6188]\n",
      "[49.0, 49.0, 49.0, 16.0, 16.0, 16.0, 50.0, 50.0, 50.0, 43.6667, 43.6667, 43.6667, 26.3333, 26.3333, 26.3333, 54.6667, 54.6667, 54.6667]\n",
      "[36.6697, 36.6697, 36.6697, 9.6264, 9.6264, 9.6264, 17.72, 17.72, 17.72, 22.3656, 22.3656, 22.3656, 29.5334, 29.5334, 29.5334, 35.5184, 35.5184, 35.5184]\n",
      "[25.9294, 25.9294, 25.9294, 6.8069, 6.8069, 6.8069, 12.53, 12.53, 12.53, 15.8149, 15.8149, 15.8149, 20.8833, 20.8833, 20.8833, 25.1153, 25.1153, 25.1153]\n",
      "[26.0, 26.0, 26.0, 60.0, 60.0, 60.0, 80.3333, 80.3333, 80.3333, 61.6667, 61.6667, 61.6667, 44.6667, 44.6667, 44.6667, 30.3333, 30.3333, 30.3333]\n",
      "[22.5536, 22.5536, 22.5536, 31.6333, 31.6333, 31.6333, 3.8586, 3.8586, 3.8586, 41.9947, 41.9947, 41.9947, 26.837, 26.837, 26.837, 22.3656, 22.3656, 22.3656]\n",
      "[15.9478, 15.9478, 15.9478, 22.3681, 22.3681, 22.3681, 2.7285, 2.7285, 2.7285, 29.6947, 29.6947, 29.6947, 18.9766, 18.9766, 18.9766, 15.8149, 15.8149, 15.8149]\n",
      "[53.3333, 53.3333, 53.3333, 15.3333, 15.3333, 15.3333, 57.3333, 57.3333, 57.3333, 74.0, 74.0, 74.0, 27.0, 27.0, 27.0, 46.3333, 46.3333, 46.3333]\n",
      "[39.6849, 39.6849, 39.6849, 8.1786, 8.1786, 8.1786, 31.2552, 31.2552, 31.2552, 16.3095, 16.3095, 16.3095, 18.8326, 18.8326, 18.8326, 36.1509, 36.1509, 36.1509]\n",
      "[28.0614, 28.0614, 28.0614, 5.7831, 5.7831, 5.7831, 22.1008, 22.1008, 22.1008, 11.5326, 11.5326, 11.5326, 13.3167, 13.3167, 13.3167, 25.5626, 25.5626, 25.5626]\n",
      "[36.0, 36.0, 36.0, 55.3333, 55.3333, 55.3333, 76.0, 76.0, 76.0, 49.0, 49.0, 49.0, 64.0, 64.0, 64.0, 46.6667, 46.6667, 46.6667]\n",
      "[26.3186, 26.3186, 26.3186, 24.0878, 24.0878, 24.0878, 12.083, 12.083, 12.083, 28.3901, 28.3901, 28.3901, 5.099, 5.099, 5.099, 32.9983, 32.9983, 32.9983]\n",
      "[18.61, 18.61, 18.61, 17.0326, 17.0326, 17.0326, 8.544, 8.544, 8.544, 20.0749, 20.0749, 20.0749, 3.6056, 3.6056, 3.6056, 23.3333, 23.3333, 23.3333]\n",
      "[71.3333, 71.3333, 71.3333, 68.0, 68.0, 68.0, 28.0, 28.0, 28.0, 29.3333, 29.3333, 29.3333, 57.3333, 57.3333, 57.3333, 56.0, 56.0, 56.0]\n",
      "[12.3918, 12.3918, 12.3918, 28.6007, 28.6007, 28.6007, 13.4907, 13.4907, 13.4907, 17.4611, 17.4611, 17.4611, 39.8107, 39.8107, 39.8107, 20.8487, 20.8487, 20.8487]\n",
      "[8.7623, 8.7623, 8.7623, 20.2237, 20.2237, 20.2237, 9.5394, 9.5394, 9.5394, 12.3468, 12.3468, 12.3468, 28.1504, 28.1504, 28.1504, 14.7422, 14.7422, 14.7422]\n",
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      "[21.7128, 21.7128, 21.7128, 13.0512, 13.0512, 13.0512, 21.5019, 21.5019, 21.5019, 14.1931, 14.1931, 14.1931, 11.1704, 11.1704, 11.1704, 10.3976, 10.3976, 10.3976]\n",
      "[42.0, 42.0, 42.0, 49.0, 49.0, 49.0, 64.0, 64.0, 64.0, 48.6667, 48.6667, 48.6667, 39.0, 39.0, 39.0, 78.6667, 78.6667, 78.6667]\n",
      "[26.7706, 26.7706, 26.7706, 16.3299, 16.3299, 16.3299, 24.3858, 24.3858, 24.3858, 33.5592, 33.5592, 33.5592, 41.0203, 41.0203, 41.0203, 13.5728, 13.5728, 13.5728]\n",
      "[18.9297, 18.9297, 18.9297, 11.547, 11.547, 11.547, 17.2434, 17.2434, 17.2434, 23.73, 23.73, 23.73, 29.0057, 29.0057, 29.0057, 9.5975, 9.5975, 9.5975]\n",
      "[49.0, 49.0, 49.0, 66.6667, 66.6667, 66.6667, 47.6667, 47.6667, 47.6667, 65.3333, 65.3333, 65.3333, 26.0, 26.0, 26.0, 69.0, 69.0, 69.0]\n",
      "[27.1784, 27.1784, 27.1784, 18.4089, 18.4089, 18.4089, 18.0062, 18.0062, 18.0062, 27.8129, 27.8129, 27.8129, 1.4142, 1.4142, 1.4142, 23.3381, 23.3381, 23.3381]\n",
      "[19.218, 19.218, 19.218, 13.0171, 13.0171, 13.0171, 12.7323, 12.7323, 12.7323, 19.6667, 19.6667, 19.6667, 1.0, 1.0, 1.0, 16.5025, 16.5025, 16.5025]\n",
      "[37.3333, 37.3333, 37.3333, 38.3333, 38.3333, 38.3333, 27.3333, 27.3333, 27.3333, 42.3333, 42.3333, 42.3333, 53.6667, 53.6667, 53.6667, 43.0, 43.0, 43.0]\n",
      "[24.074, 24.074, 24.074, 34.6827, 34.6827, 34.6827, 10.3387, 10.3387, 10.3387, 28.5463, 28.5463, 28.5463, 26.0811, 26.0811, 26.0811, 14.3062, 14.3062, 14.3062]\n",
      "[17.0229, 17.0229, 17.0229, 24.5244, 24.5244, 24.5244, 7.3106, 7.3106, 7.3106, 20.1853, 20.1853, 20.1853, 18.4421, 18.4421, 18.4421, 10.116, 10.116, 10.116]\n",
      "[60.0, 60.0, 60.0, 41.6667, 41.6667, 41.6667, 53.6667, 53.6667, 53.6667, 53.6667, 53.6667, 53.6667, 37.0, 37.0, 37.0, 45.6667, 45.6667, 45.6667]\n",
      "[16.5731, 16.5731, 16.5731, 33.9051, 33.9051, 33.9051, 12.8149, 12.8149, 12.8149, 30.7282, 30.7282, 30.7282, 23.2809, 23.2809, 23.2809, 4.1096, 4.1096, 4.1096]\n",
      "[11.7189, 11.7189, 11.7189, 23.9745, 23.9745, 23.9745, 9.0615, 9.0615, 9.0615, 21.7281, 21.7281, 21.7281, 16.4621, 16.4621, 16.4621, 2.9059, 2.9059, 2.9059]\n",
      "[30.3333, 30.3333, 30.3333, 60.0, 60.0, 60.0, 57.3333, 57.3333, 57.3333, 63.3333, 63.3333, 63.3333, 35.6667, 35.6667, 35.6667, 63.3333, 63.3333, 63.3333]\n",
      "[15.7973, 15.7973, 15.7973, 24.3858, 24.3858, 24.3858, 28.5463, 28.5463, 28.5463, 19.9388, 19.9388, 19.9388, 9.5685, 9.5685, 9.5685, 14.9741, 14.9741, 14.9741]\n",
      "[11.1704, 11.1704, 11.1704, 17.2434, 17.2434, 17.2434, 20.1853, 20.1853, 20.1853, 14.0989, 14.0989, 14.0989, 6.7659, 6.7659, 6.7659, 10.5883, 10.5883, 10.5883]\n",
      "[63.3333, 63.3333, 63.3333, 40.3333, 40.3333, 40.3333, 49.0, 49.0, 49.0, 29.0, 29.0, 29.0, 68.6667, 68.6667, 68.6667, 47.0, 47.0, 47.0]\n",
      "[15.3695, 15.3695, 15.3695, 19.6016, 19.6016, 19.6016, 15.7692, 15.7692, 15.7692, 18.4932, 18.4932, 18.4932, 27.1825, 27.1825, 27.1825, 31.1234, 31.1234, 31.1234]\n",
      "[10.8679, 10.8679, 10.8679, 13.8604, 13.8604, 13.8604, 11.1505, 11.1505, 11.1505, 13.0767, 13.0767, 13.0767, 19.2209, 19.2209, 19.2209, 22.0076, 22.0076, 22.0076]\n",
      "[83.3333, 83.3333, 83.3333, 52.6667, 52.6667, 52.6667, 15.6667, 15.6667, 15.6667, 41.6667, 41.6667, 41.6667, 45.0, 45.0, 45.0, 48.6667, 48.6667, 48.6667]\n",
      "[1.6997, 1.6997, 1.6997, 37.2499, 37.2499, 37.2499, 10.274, 10.274, 10.274, 39.5418, 39.5418, 39.5418, 19.8158, 19.8158, 19.8158, 30.1367, 30.1367, 30.1367]\n",
      "[1.2019, 1.2019, 1.2019, 26.3397, 26.3397, 26.3397, 7.2648, 7.2648, 7.2648, 27.9603, 27.9603, 27.9603, 14.0119, 14.0119, 14.0119, 21.3099, 21.3099, 21.3099]\n",
      "[53.0, 53.0, 53.0, 52.0, 52.0, 52.0, 39.6667, 39.6667, 39.6667, 41.0, 41.0, 41.0, 81.3333, 81.3333, 81.3333, 83.0, 83.0, 83.0]\n",
      "[31.9687, 31.9687, 31.9687, 31.0161, 31.0161, 31.0161, 39.8525, 39.8525, 39.8525, 13.9284, 13.9284, 13.9284, 13.0214, 13.0214, 13.0214, 24.0416, 24.0416, 24.0416]\n",
      "[22.6053, 22.6053, 22.6053, 21.9317, 21.9317, 21.9317, 28.18, 28.18, 28.18, 9.8489, 9.8489, 9.8489, 9.2075, 9.2075, 9.2075, 17.0, 17.0, 17.0]\n",
      "[69.0, 69.0, 69.0, 57.0, 57.0, 57.0, 45.6667, 45.6667, 45.6667, 52.6667, 52.6667, 52.6667, 64.0, 64.0, 64.0, 67.3333, 67.3333, 67.3333]\n",
      "[17.1464, 17.1464, 17.1464, 15.7692, 15.7692, 15.7692, 30.9121, 30.9121, 30.9121, 24.2808, 24.2808, 24.2808, 37.0945, 37.0945, 37.0945, 8.2597, 8.2597, 8.2597]\n",
      "[12.1244, 12.1244, 12.1244, 11.1505, 11.1505, 11.1505, 21.8581, 21.8581, 21.8581, 17.1691, 17.1691, 17.1691, 26.2298, 26.2298, 26.2298, 5.8405, 5.8405, 5.8405]\n",
      "[80.0, 80.0, 80.0, 54.3333, 54.3333, 54.3333, 50.3333, 50.3333, 50.3333, 59.6667, 59.6667, 59.6667, 75.3333, 75.3333, 75.3333, 34.3333, 34.3333, 34.3333]\n",
      "[12.1929, 12.1929, 12.1929, 25.3289, 25.3289, 25.3289, 33.1696, 33.1696, 33.1696, 33.4896, 33.4896, 33.4896, 17.1335, 17.1335, 17.1335, 4.9216, 4.9216, 4.9216]\n",
      "[8.6217, 8.6217, 8.6217, 17.9103, 17.9103, 17.9103, 23.4544, 23.4544, 23.4544, 23.6807, 23.6807, 23.6807, 12.1152, 12.1152, 12.1152, 3.4801, 3.4801, 3.4801]\n",
      "[75.6667, 75.6667, 75.6667, 42.6667, 42.6667, 42.6667, 63.3333, 63.3333, 63.3333, 71.6667, 71.6667, 71.6667, 37.0, 37.0, 37.0, 48.3333, 48.3333, 48.3333]\n",
      "[14.6135, 14.6135, 14.6135, 37.5085, 37.5085, 37.5085, 37.8535, 37.8535, 37.8535, 28.3118, 28.3118, 28.3118, 19.9499, 19.9499, 19.9499, 21.6692, 21.6692, 21.6692]\n",
      "[10.3333, 10.3333, 10.3333, 26.5225, 26.5225, 26.5225, 26.7665, 26.7665, 26.7665, 20.0194, 20.0194, 20.0194, 14.1067, 14.1067, 14.1067, 15.3225, 15.3225, 15.3225]\n",
      "[35.0, 35.0, 35.0, 71.3333, 71.3333, 71.3333, 31.0, 31.0, 31.0, 41.6667, 41.6667, 41.6667, 60.6667, 60.6667, 60.6667, 68.3333, 68.3333, 68.3333]\n",
      "[21.276, 21.276, 21.276, 26.0811, 26.0811, 26.0811, 20.7043, 20.7043, 20.7043, 31.3829, 31.3829, 31.3829, 32.2628, 32.2628, 32.2628, 8.0554, 8.0554, 8.0554]\n",
      "[15.0444, 15.0444, 15.0444, 18.4421, 18.4421, 18.4421, 14.6401, 14.6401, 14.6401, 22.1911, 22.1911, 22.1911, 22.8133, 22.8133, 22.8133, 5.696, 5.696, 5.696]\n",
      "[59.6667, 59.6667, 59.6667, 22.3333, 22.3333, 22.3333, 69.6667, 69.6667, 69.6667, 54.0, 54.0, 54.0, 30.3333, 30.3333, 30.3333, 36.3333, 36.3333, 36.3333]\n",
      "[29.3295, 29.3295, 29.3295, 16.1314, 16.1314, 16.1314, 24.8507, 24.8507, 24.8507, 15.7692, 15.7692, 15.7692, 21.7613, 21.7613, 21.7613, 30.0924, 30.0924, 30.0924]\n",
      "[20.7391, 20.7391, 20.7391, 11.4066, 11.4066, 11.4066, 17.5721, 17.5721, 17.5721, 11.1505, 11.1505, 11.1505, 15.3876, 15.3876, 15.3876, 21.2786, 21.2786, 21.2786]\n",
      "[46.6667, 46.6667, 46.6667, 34.3333, 34.3333, 34.3333, 72.6667, 72.6667, 72.6667, 60.6667, 60.6667, 60.6667, 62.6667, 62.6667, 62.6667, 57.6667, 57.6667, 57.6667]\n",
      "[28.0159, 28.0159, 28.0159, 23.0988, 23.0988, 23.0988, 26.2467, 26.2467, 26.2467, 22.529, 22.529, 22.529, 39.5081, 39.5081, 39.5081, 20.9815, 20.9815, 20.9815]\n",
      "[19.8102, 19.8102, 19.8102, 16.3333, 16.3333, 16.3333, 18.5592, 18.5592, 18.5592, 15.9304, 15.9304, 15.9304, 27.9364, 27.9364, 27.9364, 14.8361, 14.8361, 14.8361]\n",
      "[75.3333, 75.3333, 75.3333, 41.3333, 41.3333, 41.3333, 69.6667, 69.6667, 69.6667, 49.3333, 49.3333, 49.3333, 37.0, 37.0, 37.0, 33.6667, 33.6667, 33.6667]\n",
      "[16.2138, 16.2138, 16.2138, 27.1088, 27.1088, 27.1088, 29.937, 29.937, 29.937, 31.8991, 31.8991, 31.8991, 39.6316, 39.6316, 39.6316, 23.7954, 23.7954, 23.7954]\n",
      "[11.4649, 11.4649, 11.4649, 19.1688, 19.1688, 19.1688, 21.1686, 21.1686, 21.1686, 22.5561, 22.5561, 22.5561, 28.0238, 28.0238, 28.0238, 16.8259, 16.8259, 16.8259]\n",
      "[69.3333, 69.3333, 69.3333, 42.6667, 42.6667, 42.6667, 57.6667, 57.6667, 57.6667, 74.6667, 74.6667, 74.6667, 66.6667, 66.6667, 66.6667, 72.3333, 72.3333, 72.3333]\n",
      "[19.6016, 19.6016, 19.6016, 37.2767, 37.2767, 37.2767, 28.5229, 28.5229, 28.5229, 6.5997, 6.5997, 6.5997, 12.7628, 12.7628, 12.7628, 21.3125, 21.3125, 21.3125]\n",
      "[13.8604, 13.8604, 13.8604, 26.3586, 26.3586, 26.3586, 20.1687, 20.1687, 20.1687, 4.6667, 4.6667, 4.6667, 9.0247, 9.0247, 9.0247, 15.0702, 15.0702, 15.0702]\n",
      "[68.3333, 68.3333, 68.3333, 69.3333, 69.3333, 69.3333, 55.0, 55.0, 55.0, 68.6667, 68.6667, 68.6667, 51.0, 51.0, 51.0, 43.6667, 43.6667, 43.6667]\n",
      "[18.732, 18.732, 18.732, 18.625, 18.625, 18.625, 20.8327, 20.8327, 20.8327, 31.4784, 31.4784, 31.4784, 35.8143, 35.8143, 35.8143, 11.1455, 11.1455, 11.1455]\n",
      "[13.2455, 13.2455, 13.2455, 13.1698, 13.1698, 13.1698, 14.7309, 14.7309, 14.7309, 22.2586, 22.2586, 22.2586, 25.3246, 25.3246, 25.3246, 7.8811, 7.8811, 7.8811]\n",
      "[29.3333, 29.3333, 29.3333, 46.0, 46.0, 46.0, 47.6667, 47.6667, 47.6667, 59.0, 59.0, 59.0, 64.3333, 64.3333, 64.3333, 63.6667, 63.6667, 63.6667]\n",
      "[9.9778, 9.9778, 9.9778, 26.9196, 26.9196, 26.9196, 13.1993, 13.1993, 13.1993, 28.3901, 28.3901, 28.3901, 23.7954, 23.7954, 23.7954, 28.7557, 28.7557, 28.7557]\n",
      "[7.0553, 7.0553, 7.0553, 19.0351, 19.0351, 19.0351, 9.3333, 9.3333, 9.3333, 20.0749, 20.0749, 20.0749, 16.8259, 16.8259, 16.8259, 20.3333, 20.3333, 20.3333]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[62.0, 62.0, 62.0, 28.3333, 28.3333, 28.3333, 73.0, 73.0, 73.0, 88.6667, 88.6667, 88.6667, 39.3333, 39.3333, 39.3333, 36.6667, 36.6667, 36.6667]\n",
      "[36.4783, 36.4783, 36.4783, 13.1993, 13.1993, 13.1993, 27.7248, 27.7248, 27.7248, 5.4365, 5.4365, 5.4365, 36.5726, 36.5726, 36.5726, 16.1107, 16.1107, 16.1107]\n",
      "[25.7941, 25.7941, 25.7941, 9.3333, 9.3333, 9.3333, 19.6044, 19.6044, 19.6044, 3.8442, 3.8442, 3.8442, 25.8607, 25.8607, 25.8607, 11.392, 11.392, 11.392]\n",
      "[72.3333, 72.3333, 72.3333, 35.3333, 35.3333, 35.3333, 38.3333, 38.3333, 38.3333, 30.0, 30.0, 30.0, 61.6667, 61.6667, 61.6667, 46.6667, 46.6667, 46.6667]\n",
      "[24.1431, 24.1431, 24.1431, 15.195, 15.195, 15.195, 21.2968, 21.2968, 21.2968, 22.5536, 22.5536, 22.5536, 5.2493, 5.2493, 5.2493, 30.2141, 30.2141, 30.2141]\n",
      "[17.0717, 17.0717, 17.0717, 10.7445, 10.7445, 10.7445, 15.0591, 15.0591, 15.0591, 15.9478, 15.9478, 15.9478, 3.7118, 3.7118, 3.7118, 21.3646, 21.3646, 21.3646]\n",
      "[39.0, 39.0, 39.0, 52.3333, 52.3333, 52.3333, 83.3333, 83.3333, 83.3333, 49.6667, 49.6667, 49.6667, 50.6667, 50.6667, 50.6667, 73.6667, 73.6667, 73.6667]\n",
      "[21.6025, 21.6025, 21.6025, 33.6287, 33.6287, 33.6287, 10.873, 10.873, 10.873, 12.3648, 12.3648, 12.3648, 24.9978, 24.9978, 24.9978, 16.0485, 16.0485, 16.0485]\n",
      "[15.2753, 15.2753, 15.2753, 23.7791, 23.7791, 23.7791, 7.6884, 7.6884, 7.6884, 8.7433, 8.7433, 8.7433, 17.6761, 17.6761, 17.6761, 11.348, 11.348, 11.348]\n",
      "[51.0, 51.0, 51.0, 71.6667, 71.6667, 71.6667, 52.0, 52.0, 52.0, 48.0, 48.0, 48.0, 73.6667, 73.6667, 73.6667, 54.3333, 54.3333, 54.3333]\n",
      "[26.1916, 26.1916, 26.1916, 13.4743, 13.4743, 13.4743, 12.3558, 12.3558, 12.3558, 38.6092, 38.6092, 38.6092, 8.3799, 8.3799, 8.3799, 27.378, 27.378, 27.378]\n",
      "[18.5203, 18.5203, 18.5203, 9.5277, 9.5277, 9.5277, 8.7369, 8.7369, 8.7369, 27.3008, 27.3008, 27.3008, 5.9255, 5.9255, 5.9255, 19.3592, 19.3592, 19.3592]\n",
      "[68.0, 68.0, 68.0, 41.0, 41.0, 41.0, 51.6667, 51.6667, 51.6667, 24.6667, 24.6667, 24.6667, 39.3333, 39.3333, 39.3333, 60.3333, 60.3333, 60.3333]\n",
      "[36.9143, 36.9143, 36.9143, 35.3648, 35.3648, 35.3648, 9.7411, 9.7411, 9.7411, 32.7855, 32.7855, 32.7855, 21.0608, 21.0608, 21.0608, 17.5563, 17.5563, 17.5563]\n",
      "[26.1024, 26.1024, 26.1024, 25.0067, 25.0067, 25.0067, 6.888, 6.888, 6.888, 23.1828, 23.1828, 23.1828, 14.8922, 14.8922, 14.8922, 12.4141, 12.4141, 12.4141]\n",
      "[67.3333, 67.3333, 67.3333, 61.6667, 61.6667, 61.6667, 27.3333, 27.3333, 27.3333, 41.6667, 41.6667, 41.6667, 28.6667, 28.6667, 28.6667, 52.3333, 52.3333, 52.3333]\n",
      "[31.1698, 31.1698, 31.1698, 25.3026, 25.3026, 25.3026, 33.0387, 33.0387, 33.0387, 40.8357, 40.8357, 40.8357, 10.1434, 10.1434, 10.1434, 13.7679, 13.7679, 13.7679]\n",
      "[22.0404, 22.0404, 22.0404, 17.8916, 17.8916, 17.8916, 23.3619, 23.3619, 23.3619, 28.8752, 28.8752, 28.8752, 7.1725, 7.1725, 7.1725, 9.7354, 9.7354, 9.7354]\n",
      "[71.6667, 71.6667, 71.6667, 32.0, 32.0, 32.0, 53.0, 53.0, 53.0, 25.0, 25.0, 25.0, 80.3333, 80.3333, 80.3333, 67.0, 67.0, 67.0]\n",
      "[22.4846, 22.4846, 22.4846, 42.4264, 42.4264, 42.4264, 19.4422, 19.4422, 19.4422, 17.4547, 17.4547, 17.4547, 16.3367, 16.3367, 16.3367, 23.2809, 23.2809, 23.2809]\n",
      "[15.899, 15.899, 15.899, 30.0, 30.0, 30.0, 13.7477, 13.7477, 13.7477, 12.3423, 12.3423, 12.3423, 11.5518, 11.5518, 11.5518, 16.4621, 16.4621, 16.4621]\n",
      "[69.6667, 69.6667, 69.6667, 36.6667, 36.6667, 36.6667, 35.6667, 35.6667, 35.6667, 40.6667, 40.6667, 40.6667, 41.6667, 41.6667, 41.6667, 55.6667, 55.6667, 55.6667]\n",
      "[20.4179, 20.4179, 20.4179, 6.1283, 6.1283, 6.1283, 16.4181, 16.4181, 16.4181, 41.2661, 41.2661, 41.2661, 9.3927, 9.3927, 9.3927, 35.141, 35.141, 35.141]\n",
      "[14.4376, 14.4376, 14.4376, 4.3333, 4.3333, 4.3333, 11.6094, 11.6094, 11.6094, 29.1795, 29.1795, 29.1795, 6.6416, 6.6416, 6.6416, 24.8484, 24.8484, 24.8484]\n",
      "[45.3333, 45.3333, 45.3333, 45.3333, 45.3333, 45.3333, 57.6667, 57.6667, 57.6667, 60.0, 60.0, 60.0, 43.3333, 43.3333, 43.3333, 62.3333, 62.3333, 62.3333]\n",
      "[26.3354, 26.3354, 26.3354, 26.4491, 26.4491, 26.4491, 32.7143, 32.7143, 32.7143, 22.5536, 22.5536, 22.5536, 38.3087, 38.3087, 38.3087, 20.7257, 20.7257, 20.7257]\n",
      "[18.622, 18.622, 18.622, 18.7023, 18.7023, 18.7023, 23.1325, 23.1325, 23.1325, 15.9478, 15.9478, 15.9478, 27.0883, 27.0883, 27.0883, 14.6553, 14.6553, 14.6553]\n",
      "[48.6667, 48.6667, 48.6667, 55.0, 55.0, 55.0, 71.3333, 71.3333, 71.3333, 45.3333, 45.3333, 45.3333, 51.0, 51.0, 51.0, 57.3333, 57.3333, 57.3333]\n",
      "[33.32, 33.32, 33.32, 27.5318, 27.5318, 27.5318, 23.0988, 23.0988, 23.0988, 8.34, 8.34, 8.34, 36.6879, 36.6879, 36.6879, 27.9205, 27.9205, 27.9205]\n",
      "[23.5608, 23.5608, 23.5608, 19.4679, 19.4679, 19.4679, 16.3333, 16.3333, 16.3333, 5.8973, 5.8973, 5.8973, 25.9422, 25.9422, 25.9422, 19.7428, 19.7428, 19.7428]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import scipy.stats as stats\n",
    "\n",
    "\n",
    "average_list = list()\n",
    "std_list = list()\n",
    "sem_list = list()\n",
    "\n",
    "replicate_col = 'replicate'\n",
    "\n",
    "obs = adata.obs\n",
    "X = adata.X\n",
    "col_count, row_count = X.shape\n",
    "\n",
    "# Get replicate column\n",
    "replicates = obs.loc[:, replicate_col]\n",
    "\n",
    "# Build list of total number of replicates for each group\n",
    "replicate_count = list()\n",
    "prior_rep = None\n",
    "for r in replicates:\n",
    "    if prior_rep is None or r > prior_rep:\n",
    "        prior_rep = r\n",
    "    else:\n",
    "        replicate_count.append(prior_rep)\n",
    "        prior_rep = None\n",
    "\n",
    "#Gets last replicate count\n",
    "replicate_count.append(prior_rep)\n",
    "print('replicate_count list: ', replicate_count)\n",
    "\n",
    "#Override replicate list to test variable replicate numbers \n",
    "# replicate_count = [3, 3, 3, 3, 3, 3]\n",
    "## replicate_count = [3, 2, 1, 4, 4, 4]\n",
    "## print('New replicate_count list: ', replicate_count)\n",
    "\n",
    "for row in range(row_count):\n",
    "    replicate_vals = X[:,row]\n",
    "    \n",
    "    averages = list()\n",
    "    stds = list()\n",
    "    sems = list()\n",
    "    \n",
    "    start = 0\n",
    "    end = 0\n",
    "    for total_rep in replicate_count:\n",
    "        end += total_rep\n",
    "\n",
    "        # Subsample the replicates from 1 condition\n",
    "        values = replicate_vals[start:end]\n",
    "        rep_avg = round( np.nanmean(values), 4 )\n",
    "        rep_std = round( np.nanstd(values), 4 )\n",
    "        rep_sem = round( stats.sem(values, nan_policy=\"omit\"), 4 )\n",
    "\n",
    "        # Add the average, std, and sem for each replicate\n",
    "        for r in range(total_rep):\n",
    "            averages.append(rep_avg)\n",
    "            stds.append(rep_std)\n",
    "            sems.append(rep_sem)\n",
    "            r += 1\n",
    "\n",
    "#         start += total_rep\n",
    "#         print('start: ', start, ' end: ', end, ' values: ', values)\n",
    "        start = end\n",
    "\n",
    "    average_list.append(averages)\n",
    "    std_list.append(stds)\n",
    "    sem_list.append(sems)\n",
    "    print(averages)\n",
    "    print(stds)\n",
    "    print(sems)\n",
    "    row += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "################## TEST datasetstats.py DatasetStats.get_replicate_averages() ####################################"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>gene_symbol</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>genes</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ENSMUSG00000000567</th>\n",
       "      <td>Gnai3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSMUSG00000000568</th>\n",
       "      <td>Pbsn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSMUSG00000000569</th>\n",
       "      <td>Cdc45l</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSMUSG00000000570</th>\n",
       "      <td>H19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSMUSG00000000571</th>\n",
       "      <td>Scml2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   gene_symbol\n",
       "genes                         \n",
       "ENSMUSG00000000567       Gnai3\n",
       "ENSMUSG00000000568        Pbsn\n",
       "ENSMUSG00000000569      Cdc45l\n",
       "ENSMUSG00000000570         H19\n",
       "ENSMUSG00000000571       Scml2"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import os, sys\n",
    "sys.path.append('/home/dolley/gear/lib')\n",
    "import gear.datasetuploader as datasetuploader\n",
    "\n",
    "#Read in xlsx file and convert it to AnnData object\n",
    "#Automatically appends AnnData object to DatasetUploader object as .adata\n",
    "#  access adata via .adata.var, .adata.obs, adata.X\n",
    "test_file = '/home/dolley/gear/tests/base_template.xlsx'\n",
    "dataset = datasetuploader.DatasetUploader.upload_dataset('excel')\n",
    "dataset._read_file(test_file)\n",
    "dataset.adata.var.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[71.6667, 53.3333, 49.6667, ..., 69.6667, 45.3333, 48.6667],\n",
       "       [71.6667, 53.3333, 49.6667, ..., 69.6667, 45.3333, 48.6667],\n",
       "       [71.6667, 53.3333, 49.6667, ..., 69.6667, 45.3333, 48.6667],\n",
       "       ...,\n",
       "       [48.6667, 34.3333, 50.6667, ..., 55.6667, 62.3333, 57.3333],\n",
       "       [48.6667, 34.3333, 50.6667, ..., 55.6667, 62.3333, 57.3333],\n",
       "       [48.6667, 34.3333, 50.6667, ..., 55.6667, 62.3333, 57.3333]],\n",
       "      dtype=float32)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from gear.datasetstats import DatasetStats\n",
    "\n",
    "Xmean = DatasetStats.get_replicate_averages(dataset.adata)\n",
    "Xmean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# dataset.adata.Xmean = Xmean\n",
    "# dataset.adata.Xmean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[71.6667, 53.3333, 49.6667, ..., 69.6667, 45.3333, 48.6667],\n",
       "       [71.6667, 53.3333, 49.6667, ..., 69.6667, 45.3333, 48.6667],\n",
       "       [71.6667, 53.3333, 49.6667, ..., 69.6667, 45.3333, 48.6667],\n",
       "       ...,\n",
       "       [48.6667, 34.3333, 50.6667, ..., 55.6667, 62.3333, 57.3333],\n",
       "       [48.6667, 34.3333, 50.6667, ..., 55.6667, 62.3333, 57.3333],\n",
       "       [48.6667, 34.3333, 50.6667, ..., 55.6667, 62.3333, 57.3333]],\n",
       "      dtype=float32)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset._add_calculated_values(dataset.adata)\n",
    "dataset.adata.Xmean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[16.7398 16.7398 16.7398 37.5618 37.5618 37.5618 19.362  19.362  19.362\n",
      " 19.3046 19.3046 19.3046 41.684  41.684  41.684  23.669  23.669  23.669 ]\n"
     ]
    }
   ],
   "source": [
    "############################  TEST DatasetStats.get_replicate_std() ###############################################\n",
    "Xstd = DatasetStats.get_replicate_std(dataset.adata)\n",
    "Xstd\n",
    "print(Xstd[:,0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[11.8369 11.8369 11.8369 26.5602 26.5602 26.5602 13.691  13.691  13.691\n",
      " 13.6504 13.6504 13.6504 29.475  29.475  29.475  16.7365 16.7365 16.7365]\n"
     ]
    }
   ],
   "source": [
    "############################  TEST DatasetStats.get_replicate_sem() ###############################################\n",
    "Xsem = DatasetStats.get_replicate_sem(dataset.adata)\n",
    "Xsem\n",
    "print(Xsem[:,0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_replicate_counts(obs=None):\n",
    "\n",
    "    # Get replicate counts by grouping them with pandas built-ins\n",
    "    if 'time_point' in obs.columns:\n",
    "        groups = obs.groupby(['cell_type', 'condition', 'time_point']).count().reset_index()\n",
    "    else:\n",
    "        groups = obs.groupby(['cell_type', 'condition']).count().reset_index()\n",
    "\n",
    "    #pandas series containing number of replicates for each condition\n",
    "    replicate_count = groups.loc[:, 'replicate']\n",
    "\n",
    "    return replicate_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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_type</th>\n",
       "      <th>condition</th>\n",
       "      <th>replicate</th>\n",
       "      <th>time_point</th>\n",
       "      <th>time_unit</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>observations</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>obs-ctrl-1-0h</th>\n",
       "      <td>utricle</td>\n",
       "      <td>control</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>hour</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>obs-ctrl-2-0h</th>\n",
       "      <td>utricle</td>\n",
       "      <td>control</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>hour</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>obs-ctrl-3-0h</th>\n",
       "      <td>utricle</td>\n",
       "      <td>control</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>hour</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>obs-trt-1-0h</th>\n",
       "      <td>utricle</td>\n",
       "      <td>treated</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>hour</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>obs-trt-2-0h</th>\n",
       "      <td>utricle</td>\n",
       "      <td>treated</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>hour</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>obs-trt-3-0h</th>\n",
       "      <td>utricle</td>\n",
       "      <td>treated</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>hour</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>obs-ctrl-1-24h</th>\n",
       "      <td>utricle</td>\n",
       "      <td>control</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>hour</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>obs-ctrl-2-24h</th>\n",
       "      <td>utricle</td>\n",
       "      <td>control</td>\n",
       "      <td>2</td>\n",
       "      <td>24</td>\n",
       "      <td>hour</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>obs-ctrl-3-24h</th>\n",
       "      <td>utricle</td>\n",
       "      <td>control</td>\n",
       "      <td>3</td>\n",
       "      <td>24</td>\n",
       "      <td>hour</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>obs-trt-1-24h</th>\n",
       "      <td>utricle</td>\n",
       "      <td>treated</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>hour</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>obs-trt-2-24h</th>\n",
       "      <td>utricle</td>\n",
       "      <td>treated</td>\n",
       "      <td>2</td>\n",
       "      <td>24</td>\n",
       "      <td>hour</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>obs-trt-3-24h</th>\n",
       "      <td>utricle</td>\n",
       "      <td>treated</td>\n",
       "      <td>3</td>\n",
       "      <td>24</td>\n",
       "      <td>hour</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>obs-ctrl-1-48h</th>\n",
       "      <td>utricle</td>\n",
       "      <td>control</td>\n",
       "      <td>1</td>\n",
       "      <td>48</td>\n",
       "      <td>hour</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>obs-ctrl-2-48h</th>\n",
       "      <td>utricle</td>\n",
       "      <td>control</td>\n",
       "      <td>2</td>\n",
       "      <td>48</td>\n",
       "      <td>hour</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>obs-ctrl-3-48h</th>\n",
       "      <td>utricle</td>\n",
       "      <td>control</td>\n",
       "      <td>3</td>\n",
       "      <td>48</td>\n",
       "      <td>hour</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>obs-trt-1-48h</th>\n",
       "      <td>utricle</td>\n",
       "      <td>treated</td>\n",
       "      <td>1</td>\n",
       "      <td>48</td>\n",
       "      <td>hour</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>obs-trt-2-48h</th>\n",
       "      <td>utricle</td>\n",
       "      <td>treated</td>\n",
       "      <td>2</td>\n",
       "      <td>48</td>\n",
       "      <td>hour</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>obs-trt-3-48h</th>\n",
       "      <td>utricle</td>\n",
       "      <td>treated</td>\n",
       "      <td>3</td>\n",
       "      <td>48</td>\n",
       "      <td>hour</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               cell_type condition  replicate  time_point time_unit\n",
       "observations                                                       \n",
       "obs-ctrl-1-0h    utricle   control          1           0      hour\n",
       "obs-ctrl-2-0h    utricle   control          2           0      hour\n",
       "obs-ctrl-3-0h    utricle   control          3           0      hour\n",
       "obs-trt-1-0h     utricle   treated          1           0      hour\n",
       "obs-trt-2-0h     utricle   treated          2           0      hour\n",
       "obs-trt-3-0h     utricle   treated          3           0      hour\n",
       "obs-ctrl-1-24h   utricle   control          1          24      hour\n",
       "obs-ctrl-2-24h   utricle   control          2          24      hour\n",
       "obs-ctrl-3-24h   utricle   control          3          24      hour\n",
       "obs-trt-1-24h    utricle   treated          1          24      hour\n",
       "obs-trt-2-24h    utricle   treated          2          24      hour\n",
       "obs-trt-3-24h    utricle   treated          3          24      hour\n",
       "obs-ctrl-1-48h   utricle   control          1          48      hour\n",
       "obs-ctrl-2-48h   utricle   control          2          48      hour\n",
       "obs-ctrl-3-48h   utricle   control          3          48      hour\n",
       "obs-trt-1-48h    utricle   treated          1          48      hour\n",
       "obs-trt-2-48h    utricle   treated          2          48      hour\n",
       "obs-trt-3-48h    utricle   treated          3          48      hour"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "###################################### Calculate p-values #########################################################\n",
    "# https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.pearsonr.html#scipy.stats.pearsonr\n",
    "# pearson_coefficient, pvalue = stats.pearsonr(control_array, treated_array)\n",
    "import  scipy.stats as stats\n",
    "X = adata.X\n",
    "obs = adata.obs\n",
    "obs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    3\n",
       "1    3\n",
       "2    3\n",
       "3    3\n",
       "4    3\n",
       "5    3\n",
       "Name: replicate, dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "replicate_counts = get_replicate_counts(obs)\n",
    "replicate_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "18 rows x  5 cols\n"
     ]
    }
   ],
   "source": [
    "rows, cols = obs.shape\n",
    "print(rows, 'rows x ', cols, 'cols')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "### USE THIS TO GENERATE REPLICATE COUNTS IN DatasetStats.get_replicate_counts()\n",
    "# groups = obs.groupby(['cell_type', 'condition', 'time_point']).count().reset_index()\n",
    "# if 'time_point' in obs.columns:\n",
    "#     print('time_point column found')\n",
    "#     groups = obs.groupby(['cell_type', 'condition', 'time_point']).count().reset_index()\n",
    "# else:\n",
    "#     print('No time_point column found')\n",
    "#     groups = obs.groupby(['cell_type', 'condition']).count().reset_index()\n",
    "# print(groups)\n",
    "# replicates = groups.loc[:, 'replicate']\n",
    "## for i, r in replicates.iteritems():\n",
    "##     print(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                replicate  time_unit\n",
      "cell_type condition time_point                      \n",
      "utricle   control   0                   3          3\n",
      "                    24                  3          3\n",
      "                    48                  3          3\n",
      "          treated   0                   3          3\n",
      "                    24                  3          3\n"
     ]
    }
   ],
   "source": [
    "groupby_attrs = ['cell_type', 'condition', 'time_point']\n",
    "# grouped = obs.groupby(['cell_type', 'condition', 'time_point']).count()\n",
    "grouped = obs.groupby([groupby_attrs[0], groupby_attrs[1], groupby_attrs[2]]).count()\n",
    "print(grouped.head())\n",
    "# grouped.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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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></th>\n",
       "      <th></th>\n",
       "      <th>replicate</th>\n",
       "      <th>time_unit</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell_type</th>\n",
       "      <th>condition</th>\n",
       "      <th>time_point</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">utricle</th>\n",
       "      <th rowspan=\"3\" valign=\"top\">control</th>\n",
       "      <th>0</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">treated</th>\n",
       "      <th>0</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                replicate  time_unit\n",
       "cell_type condition time_point                      \n",
       "utricle   control   0                   3          3\n",
       "                    24                  3          3\n",
       "                    48                  3          3\n",
       "          treated   0                   3          3\n",
       "                    24                  3          3\n",
       "                    48                  3          3"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped.reset_index().T\n",
    "grouped\n",
    "# grouped.loc['control']\n",
    "# grouped[['cell_type','']]\n",
    "# grouped.index.get_level_values(0)\n",
    "# grouped.iloc[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# http://pandas.pydata.org/pandas-docs/stable/advanced.html#advanced-indexing-with-hierarchical-index\n",
    "grouped.loc['utricle','control', 0]['replicate']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2\n",
      "utricle 3\n",
      "utricle 3\n",
      "utricle 3\n",
      "utricle 3\n",
      "utricle 3\n",
      "utricle 3\n",
      "MultiIndex(levels=[['utricle'], ['control', 'treated'], [0, 24, 48]],\n",
      "           labels=[[0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1], [0, 1, 2, 0, 1, 2]],\n",
      "           names=['cell_type', 'condition', 'time_point'])\n"
     ]
    }
   ],
   "source": [
    "level_1_len = len(grouped.index[0])\n",
    "# print(level_1_len, grouped.index[0])\n",
    "print(grouped.index.levels[1].size)\n",
    "for row in grouped.itertuples():\n",
    "    print(grouped.index[0][0], row[1])\n",
    "print(grouped.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[72. 79. 40. ... 87. 11. 84.]\n",
      " [92. 15. 15. ... 81. 50.  4.]\n",
      " [51. 66. 94. ... 41. 75. 58.]\n",
      " ...\n",
      " [25.  7. 60. ... 79. 83. 74.]\n",
      " [40. 82. 49. ... 82. 70. 80.]\n",
      " [81. 14. 43. ...  6. 34. 18.]]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(18, 100)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(X)\n",
    "X.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "p_values:  [None, None, None, 0.6836206, 0.6836206, 0.6836206, None, None, None, 0.5876048, 0.5876048, 0.5876048, None, None, None, 0.4909728, 0.4909728, 0.4909728]\n",
      "p_values:  [None, None, None, 0.9686701, 0.9686701, 0.9686701, None, None, None, 0.55428, 0.55428, 0.55428, None, None, None, 0.0692434, 0.0692434, 0.0692434]\n",
      "p_values:  [None, None, None, 0.9736786, 0.9736786, 0.9736786, None, None, None, 0.2822105, 0.2822105, 0.2822105, None, None, None, 0.6407919, 0.6407919, 0.6407919]\n",
      "p_values:  [None, None, None, 0.4734865, 0.4734865, 0.4734865, None, None, None, 0.6760904, 0.6760904, 0.6760904, None, None, None, 0.6263417, 0.6263417, 0.6263417]\n",
      "p_values:  [None, None, None, 0.5705433, 0.5705433, 0.5705433, None, None, None, 0.6414396, 0.6414396, 0.6414396, None, None, None, 0.6674344, 0.6674344, 0.6674344]\n",
      "p_values:  [None, None, None, 0.986875, 0.986875, 0.986875, None, None, None, 0.4330716, 0.4330716, 0.4330716, None, None, None, 0.8511378, 0.8511378, 0.8511378]\n",
      "p_values:  [None, None, None, 0.6700413, 0.6700413, 0.6700413, None, None, None, 0.9371955, 0.9371955, 0.9371955, None, None, None, 0.8476596, 0.8476596, 0.8476596]\n",
      "p_values:  [None, None, None, 0.0396467, 0.0396467, 0.0396467, None, None, None, 0.0586882, 0.0586882, 0.0586882, None, None, None, 0.8474834, 0.8474834, 0.8474834]\n",
      "p_values:  [None, None, None, 0.2276456, 0.2276456, 0.2276456, None, None, None, 0.1940557, 0.1940557, 0.1940557, None, None, None, 0.3426206, 0.3426206, 0.3426206]\n",
      "p_values:  [None, None, None, 0.0355653, 0.0355653, 0.0355653, None, None, None, 0.7184663, 0.7184663, 0.7184663, None, None, None, 0.9566355, 0.9566355, 0.9566355]\n",
      "p_values:  [None, None, None, 0.2469827, 0.2469827, 0.2469827, None, None, None, 0.8473977, 0.8473977, 0.8473977, None, None, None, 0.5273821, 0.5273821, 0.5273821]\n",
      "p_values:  [None, None, None, 0.1667498, 0.1667498, 0.1667498, None, None, None, 0.343558, 0.343558, 0.343558, None, None, None, 0.4938537, 0.4938537, 0.4938537]\n",
      "p_values:  [None, None, None, 0.0134819, 0.0134819, 0.0134819, None, None, None, 0.8729697, 0.8729697, 0.8729697, None, None, None, 0.0332109, 0.0332109, 0.0332109]\n",
      "p_values:  [None, None, None, 0.0003108, 0.0003108, 0.0003108, None, None, None, 0.2989513, 0.2989513, 0.2989513, None, None, None, 0.3711598, 0.3711598, 0.3711598]\n",
      "p_values:  [None, None, None, 0.1660151, 0.1660151, 0.1660151, None, None, None, 0.8546708, 0.8546708, 0.8546708, None, None, None, 0.5899775, 0.5899775, 0.5899775]\n",
      "p_values:  [None, None, None, 0.904192, 0.904192, 0.904192, None, None, None, 0.6561911, 0.6561911, 0.6561911, None, None, None, 0.448411, 0.448411, 0.448411]\n",
      "p_values:  [None, None, None, 0.2344975, 0.2344975, 0.2344975, None, None, None, 0.802229, 0.802229, 0.802229, None, None, None, 0.5980179, 0.5980179, 0.5980179]\n",
      "p_values:  [None, None, None, 0.3681195, 0.3681195, 0.3681195, None, None, None, 0.5699048, 0.5699048, 0.5699048, None, None, None, 0.3562955, 0.3562955, 0.3562955]\n",
      "p_values:  [None, None, None, 0.8398775, 0.8398775, 0.8398775, None, None, None, 0.3482946, 0.3482946, 0.3482946, None, None, None, 0.157034, 0.157034, 0.157034]\n",
      "p_values:  [None, None, None, 0.5711026, 0.5711026, 0.5711026, None, None, None, 0.0961562, 0.0961562, 0.0961562, None, None, None, 0.4456892, 0.4456892, 0.4456892]\n",
      "p_values:  [None, None, None, 0.6459458, 0.6459458, 0.6459458, None, None, None, 0.1324466, 0.1324466, 0.1324466, None, None, None, 0.0461951, 0.0461951, 0.0461951]\n",
      "p_values:  [None, None, None, 0.7052856, 0.7052856, 0.7052856, None, None, None, 0.6280478, 0.6280478, 0.6280478, None, None, None, 0.1208816, 0.1208816, 0.1208816]\n",
      "p_values:  [None, None, None, 0.3344101, 0.3344101, 0.3344101, None, None, None, 0.8512222, 0.8512222, 0.8512222, None, None, None, 0.4026058, 0.4026058, 0.4026058]\n",
      "p_values:  [None, None, None, 0.0272276, 0.0272276, 0.0272276, None, None, None, 0.5192776, 0.5192776, 0.5192776, None, None, None, 0.8490212, 0.8490212, 0.8490212]\n",
      "p_values:  [None, None, None, 0.4145679, 0.4145679, 0.4145679, None, None, None, 0.6686699, 0.6686699, 0.6686699, None, None, None, 0.342513, 0.342513, 0.342513]\n",
      "p_values:  [None, None, None, 0.9129899, 0.9129899, 0.9129899, None, None, None, 0.5480234, 0.5480234, 0.5480234, None, None, None, 0.0391553, 0.0391553, 0.0391553]\n",
      "p_values:  [None, None, None, 0.1249703, 0.1249703, 0.1249703, None, None, None, 0.8514396, 0.8514396, 0.8514396, None, None, None, 0.9652139, 0.9652139, 0.9652139]\n",
      "p_values:  [None, None, None, 0.1746771, 0.1746771, 0.1746771, None, None, None, 0.5317087, 0.5317087, 0.5317087, None, None, None, 0.1806279, 0.1806279, 0.1806279]\n",
      "p_values:  [None, None, None, 0.9040097, 0.9040097, 0.9040097, None, None, None, 0.0340701, 0.0340701, 0.0340701, None, None, None, 0.3667167, 0.3667167, 0.3667167]\n",
      "p_values:  [None, None, None, 0.6945913, 0.6945913, 0.6945913, None, None, None, 0.1087874, 0.1087874, 0.1087874, None, None, None, 0.5900174, 0.5900174, 0.5900174]\n",
      "p_values:  [None, None, None, 0.5966239, 0.5966239, 0.5966239, None, None, None, 0.1724458, 0.1724458, 0.1724458, None, None, None, 0.1870376, 0.1870376, 0.1870376]\n",
      "p_values:  [None, None, None, 0.5821887, 0.5821887, 0.5821887, None, None, None, 0.1535879, 0.1535879, 0.1535879, None, None, None, 0.6457144, 0.6457144, 0.6457144]\n",
      "p_values:  [None, None, None, 0.9752645, 0.9752645, 0.9752645, None, None, None, 0.7627037, 0.7627037, 0.7627037, None, None, None, 0.5208935, 0.5208935, 0.5208935]\n",
      "p_values:  [None, None, None, 0.6083397, 0.6083397, 0.6083397, None, None, None, 0.6992145, 0.6992145, 0.6992145, None, None, None, 0.8764285, 0.8764285, 0.8764285]\n",
      "p_values:  [None, None, None, 0.5097566, 0.5097566, 0.5097566, None, None, None, 0.0033262, 0.0033262, 0.0033262, None, None, None, 0.9844247, 0.9844247, 0.9844247]\n",
      "p_values:  [None, None, None, 0.6425835, 0.6425835, 0.6425835, None, None, None, 0.4567582, 0.4567582, 0.4567582, None, None, None, 0.8414838, 0.8414838, 0.8414838]\n",
      "p_values:  [None, None, None, 0.9175125, 0.9175125, 0.9175125, None, None, None, 0.60185, 0.60185, 0.60185, None, None, None, 0.9381157, 0.9381157, 0.9381157]\n",
      "p_values:  [None, None, None, 0.0473387, 0.0473387, 0.0473387, None, None, None, 0.0676167, 0.0676167, 0.0676167, None, None, None, 0.6282332, 0.6282332, 0.6282332]\n",
      "p_values:  [None, None, None, 0.7697832, 0.7697832, 0.7697832, None, None, None, 0.9139935, 0.9139935, 0.9139935, None, None, None, 0.528258, 0.528258, 0.528258]\n",
      "p_values:  [None, None, None, 0.5723643, 0.5723643, 0.5723643, None, None, None, 0.5705182, 0.5705182, 0.5705182, None, None, None, 0.8370318, 0.8370318, 0.8370318]\n",
      "p_values:  [None, None, None, 0.7690732, 0.7690732, 0.7690732, None, None, None, 0.4980133, 0.4980133, 0.4980133, None, None, None, 0.4101798, 0.4101798, 0.4101798]\n",
      "p_values:  [None, None, None, 0.6927691, 0.6927691, 0.6927691, None, None, None, 0.8570348, 0.8570348, 0.8570348, None, None, None, 0.6612045, 0.6612045, 0.6612045]\n",
      "p_values:  [None, None, None, 0.0262212, 0.0262212, 0.0262212, None, None, None, 0.2262946, 0.2262946, 0.2262946, None, None, None, 0.8330572, 0.8330572, 0.8330572]\n",
      "p_values:  [None, None, None, 0.9371955, 0.9371955, 0.9371955, None, None, None, 0.1590973, 0.1590973, 0.1590973, None, None, None, 0.6973821, 0.6973821, 0.6973821]\n",
      "p_values:  [None, None, None, 0.1608618, 0.1608618, 0.1608618, None, None, None, 0.2438084, 0.2438084, 0.2438084, None, None, None, 0.0018521, 0.0018521, 0.0018521]\n",
      "p_values:  [None, None, None, 0.7806919, 0.7806919, 0.7806919, None, None, None, 0.6041223, 0.6041223, 0.6041223, None, None, None, 0.9158222, 0.9158222, 0.9158222]\n",
      "p_values:  [None, None, None, 0.4172919, 0.4172919, 0.4172919, None, None, None, 0.9242853, 0.9242853, 0.9242853, None, None, None, 0.4955191, 0.4955191, 0.4955191]\n",
      "p_values:  [None, None, None, 0.1164434, 0.1164434, 0.1164434, None, None, None, 0.6100798, 0.6100798, 0.6100798, None, None, None, 0.6685711, 0.6685711, 0.6685711]\n",
      "p_values:  [None, None, None, 0.9453091, 0.9453091, 0.9453091, None, None, None, 0.9813938, 0.9813938, 0.9813938, None, None, None, 0.6969043, 0.6969043, 0.6969043]\n",
      "p_values:  [None, None, None, 0.6666667, 0.6666667, 0.6666667, None, None, None, 0.7063831, 0.7063831, 0.7063831, None, None, None, 0.8642628, 0.8642628, 0.8642628]\n",
      "p_values:  [None, None, None, 0.7117083, 0.7117083, 0.7117083, None, None, None, 0.8750934, 0.8750934, 0.8750934, None, None, None, 0.2793275, 0.2793275, 0.2793275]\n",
      "p_values:  [None, None, None, 0.5486596, 0.5486596, 0.5486596, None, None, None, 0.6599638, 0.6599638, 0.6599638, None, None, None, 0.9887782, 0.9887782, 0.9887782]\n",
      "p_values:  [None, None, None, 0.4747417, 0.4747417, 0.4747417, None, None, None, 0.1078032, 0.1078032, 0.1078032, None, None, None, 0.9978876, 0.9978876, 0.9978876]\n",
      "p_values:  [None, None, None, 0.5019931, 0.5019931, 0.5019931, None, None, None, 0.5401869, 0.5401869, 0.5401869, None, None, None, 0.999155, 0.999155, 0.999155]\n",
      "p_values:  [None, None, None, 0.4267174, 0.4267174, 0.4267174, None, None, None, 0.8674775, 0.8674775, 0.8674775, None, None, None, 0.1428268, 0.1428268, 0.1428268]\n",
      "p_values:  [None, None, None, 0.1699257, 0.1699257, 0.1699257, None, None, None, 0.329274, 0.329274, 0.329274, None, None, None, 0.6729514, 0.6729514, 0.6729514]\n",
      "p_values:  [None, None, None, 0.6249896, 0.6249896, 0.6249896, None, None, None, 0.6260508, 0.6260508, 0.6260508, None, None, None, 0.1358324, 0.1358324, 0.1358324]\n",
      "p_values:  [None, None, None, 0.3721429, 0.3721429, 0.3721429, None, None, None, 0.6357283, 0.6357283, 0.6357283, None, None, None, 0.7243321, 0.7243321, 0.7243321]\n",
      "p_values:  [None, None, None, 0.0768113, 0.0768113, 0.0768113, None, None, None, 0.2788505, 0.2788505, 0.2788505, None, None, None, 0.6243685, 0.6243685, 0.6243685]\n",
      "p_values:  [None, None, None, 0.7625278, 0.7625278, 0.7625278, None, None, None, 0.9000995, 0.9000995, 0.9000995, None, None, None, 0.9055001, 0.9055001, 0.9055001]\n",
      "p_values:  [None, None, None, 0.3304047, 0.3304047, 0.3304047, None, None, None, 0.254932, 0.254932, 0.254932, None, None, None, 0.8374117, 0.8374117, 0.8374117]\n",
      "p_values:  [None, None, None, 0.4296261, 0.4296261, 0.4296261, None, None, None, 0.2535602, 0.2535602, 0.2535602, None, None, None, 0.2909861, 0.2909861, 0.2909861]\n",
      "p_values:  [None, None, None, 0.894274, 0.894274, 0.894274, None, None, None, 0.1057259, 0.1057259, 0.1057259, None, None, None, 0.6721252, 0.6721252, 0.6721252]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "p_values:  [None, None, None, 0.3857223, 0.3857223, 0.3857223, None, None, None, 0.4015123, 0.4015123, 0.4015123, None, None, None, 0.5070932, 0.5070932, 0.5070932]\n",
      "p_values:  [None, None, None, 0.3050156, 0.3050156, 0.3050156, None, None, None, 0.2615225, 0.2615225, 0.2615225, None, None, None, 0.4109908, 0.4109908, 0.4109908]\n",
      "p_values:  [None, None, None, 0.7392697, 0.7392697, 0.7392697, None, None, None, 0.0171663, 0.0171663, 0.0171663, None, None, None, 0.2568976, 0.2568976, 0.2568976]\n",
      "p_values:  [None, None, None, 0.5652898, 0.5652898, 0.5652898, None, None, None, 0.7029289, 0.7029289, 0.7029289, None, None, None, 0.5603632, 0.5603632, 0.5603632]\n",
      "p_values:  [None, None, None, 0.6426419, 0.6426419, 0.6426419, None, None, None, 0.8251274, 0.8251274, 0.8251274, None, None, None, 0.015178, 0.015178, 0.015178]\n",
      "p_values:  [None, None, None, 0.6669177, 0.6669177, 0.6669177, None, None, None, 0.626886, 0.626886, 0.626886, None, None, None, 0.929373, 0.929373, 0.929373]\n",
      "p_values:  [None, None, None, 0.8057759, 0.8057759, 0.8057759, None, None, None, 0.1044424, 0.1044424, 0.1044424, None, None, None, 0.5335133, 0.5335133, 0.5335133]\n",
      "p_values:  [None, None, None, 0.6542199, 0.6542199, 0.6542199, None, None, None, 0.6219449, 0.6219449, 0.6219449, None, None, None, 0.3085272, 0.3085272, 0.3085272]\n",
      "p_values:  [None, None, None, 0.8422559, 0.8422559, 0.8422559, None, None, None, 0.0244561, 0.0244561, 0.0244561, None, None, None, 0.715012, 0.715012, 0.715012]\n",
      "p_values:  [None, None, None, 0.5823434, 0.5823434, 0.5823434, None, None, None, 0.4641647, 0.4641647, 0.4641647, None, None, None, 0.1619023, 0.1619023, 0.1619023]\n",
      "p_values:  [None, None, None, 0.4701069, 0.4701069, 0.4701069, None, None, None, 0.0959901, 0.0959901, 0.0959901, None, None, None, 0.0848535, 0.0848535, 0.0848535]\n",
      "p_values:  [None, None, None, 0.9650785, 0.9650785, 0.9650785, None, None, None, 0.6552561, 0.6552561, 0.6552561, None, None, None, 0.432316, 0.432316, 0.432316]\n",
      "p_values:  [None, None, None, 0.7537164, 0.7537164, 0.7537164, None, None, None, 0.3691881, 0.3691881, 0.3691881, None, None, None, 0.4842977, 0.4842977, 0.4842977]\n",
      "p_values:  [None, None, None, 0.7902028, 0.7902028, 0.7902028, None, None, None, 0.4921766, 0.4921766, 0.4921766, None, None, None, 0.8230987, 0.8230987, 0.8230987]\n",
      "p_values:  [None, None, None, 0.9197229, 0.9197229, 0.9197229, None, None, None, 0.9775975, 0.9775975, 0.9775975, None, None, None, 0.03408, 0.03408, 0.03408]\n",
      "p_values:  [None, None, None, 0.1683763, 0.1683763, 0.1683763, None, None, None, 0.6045878, 0.6045878, 0.6045878, None, None, None, 0.9779004, 0.9779004, 0.9779004]\n",
      "p_values:  [None, None, None, 0.7123001, 0.7123001, 0.7123001, None, None, None, 0.5596802, 0.5596802, 0.5596802, None, None, None, 0.9436015, 0.9436015, 0.9436015]\n",
      "p_values:  [None, None, None, 0.3568836, 0.3568836, 0.3568836, None, None, None, 0.1019623, 0.1019623, 0.1019623, None, None, None, 0.7894034, 0.7894034, 0.7894034]\n",
      "p_values:  [None, None, None, 0.8692156, 0.8692156, 0.8692156, None, None, None, 0.4583403, 0.4583403, 0.4583403, None, None, None, 0.1651803, 0.1651803, 0.1651803]\n",
      "p_values:  [None, None, None, 0.4622281, 0.4622281, 0.4622281, None, None, None, 0.4995146, 0.4995146, 0.4995146, None, None, None, 0.3679738, 0.3679738, 0.3679738]\n",
      "p_values:  [None, None, None, 0.1808217, 0.1808217, 0.1808217, None, None, None, 0.0536426, 0.0536426, 0.0536426, None, None, None, 0.9777082, 0.9777082, 0.9777082]\n",
      "p_values:  [None, None, None, 0.0417204, 0.0417204, 0.0417204, None, None, None, 0.9259628, 0.9259628, 0.9259628, None, None, None, 0.6082827, 0.6082827, 0.6082827]\n",
      "p_values:  [None, None, None, 0.9140432, 0.9140432, 0.9140432, None, None, None, 0.1313735, 0.1313735, 0.1313735, None, None, None, 0.6737534, 0.6737534, 0.6737534]\n",
      "p_values:  [None, None, None, 0.5307251, 0.5307251, 0.5307251, None, None, None, 0.4412087, 0.4412087, 0.4412087, None, None, None, 0.0578747, 0.0578747, 0.0578747]\n",
      "p_values:  [None, None, None, 0.3875141, 0.3875141, 0.3875141, None, None, None, 0.222319, 0.222319, 0.222319, None, None, None, 0.7212825, 0.7212825, 0.7212825]\n",
      "p_values:  [None, None, None, 0.9642976, 0.9642976, 0.9642976, None, None, None, 0.8608187, 0.8608187, 0.8608187, None, None, None, 0.0006217, 0.0006217, 0.0006217]\n",
      "p_values:  [None, None, None, 0.4157289, 0.4157289, 0.4157289, None, None, None, 0.200525, 0.200525, 0.200525, None, None, None, 0.8789623, 0.8789623, 0.8789623]\n",
      "p_values:  [None, None, None, 0.5829643, 0.5829643, 0.5829643, None, None, None, 0.1105216, 0.1105216, 0.1105216, None, None, None, 0.5729327, 0.5729327, 0.5729327]\n",
      "p_values:  [None, None, None, 0.0558442, 0.0558442, 0.0558442, None, None, None, 0.4815932, 0.4815932, 0.4815932, None, None, None, 0.1350397, 0.1350397, 0.1350397]\n",
      "p_values:  [None, None, None, 0.365479, 0.365479, 0.365479, None, None, None, 0.0367143, 0.0367143, 0.0367143, None, None, None, 0.9016741, 0.9016741, 0.9016741]\n",
      "p_values:  [None, None, None, 0.2785473, 0.2785473, 0.2785473, None, None, None, 0.7176066, 0.7176066, 0.7176066, None, None, None, 0.5730413, 0.5730413, 0.5730413]\n",
      "p_values:  [None, None, None, 0.3534933, 0.3534933, 0.3534933, None, None, None, 0.7468525, 0.7468525, 0.7468525, None, None, None, 0.9350542, 0.9350542, 0.9350542]\n",
      "p_values:  [None, None, None, 0.7693285, 0.7693285, 0.7693285, None, None, None, 0.7075069, 0.7075069, 0.7075069, None, None, None, 0.0417129, 0.0417129, 0.0417129]\n",
      "p_values:  [None, None, None, 0.7245413, 0.7245413, 0.7245413, None, None, None, 0.7590832, 0.7590832, 0.7590832, None, None, None, 0.2561198, 0.2561198, 0.2561198]\n",
      "p_values:  [None, None, None, 0.3854003, 0.3854003, 0.3854003, None, None, None, 0.0576611, 0.0576611, 0.0576611, None, None, None, 0.0987502, 0.0987502, 0.0987502]\n",
      "p_values:  [None, None, None, 0.2926852, 0.2926852, 0.2926852, None, None, None, 0.1021299, 0.1021299, 0.1021299, None, None, None, 0.2484567, 0.2484567, 0.2484567]\n",
      "p_values:  [None, None, None, 0.6714747, 0.6714747, 0.6714747, None, None, None, 0.9668941, 0.9668941, 0.9668941, None, None, None, 0.8171428, 0.8171428, 0.8171428]\n"
     ]
    }
   ],
   "source": [
    "obs = adata.obs\n",
    "X_cols, X_rows = X.shape\n",
    "obs_rows, obs_cols = obs.shape\n",
    "\n",
    "total_conditions = grouped.index.levels[0].size * grouped.index.levels[1].size * grouped.index.levels[2].size\n",
    "\n",
    "# print(grouped.index.levels[0].name, ': ', grouped.index.levels[0][0], ': ', grouped.index.levels[0].size)\n",
    "# print(grouped.index.levels[1].name, ': ', grouped.index.levels[1].values, ': ', grouped.index.levels[1].size)\n",
    "# print(grouped.index.levels[2].name, ': ', grouped.index.levels[2].values, ': ', grouped.index.levels[2].size)\n",
    "# print(\"number of conditions: {0}\".format(total_conditions))\n",
    "\n",
    "replicate_list = get_replicate_counts(adata.obs)\n",
    "# print(replicate_list)\n",
    "\n",
    "# for r in range(X_rows):\n",
    "\n",
    "control_string = ['control', 'wildtype', 'input']\n",
    "\n",
    "p_values_list = list()\n",
    "for g, gene in enumerate(X.T):\n",
    "#     print(gene)\n",
    "    \n",
    "#     p_values = list()\n",
    "    p_values = [None] * len(gene)\n",
    "    cell_type = None\n",
    "    time_point = None\n",
    "    control_list = list()\n",
    "    treated_list = list()\n",
    "    treated_indices = list()\n",
    "    count_replicates = 0\n",
    "    count_conditions = 1 # adds control group here\n",
    "    \n",
    "    #Go through each condition for each expression row\n",
    "    for col, replicate in obs.iterrows():\n",
    "        cell_type = replicate['cell_type']\n",
    "        condition = replicate['condition']\n",
    "        time_point = replicate['time_point']\n",
    "        \n",
    "        # Replicate is control group ('control', 'wildtype', 'input')\n",
    "        if any(condition.lower() in c for c in control_string):\n",
    "            # Add replicate to list\n",
    "            if len(control_list) < grouped.loc[cell_type, condition, time_point]['replicate']: \n",
    "                # Still adding replicates of current condition\n",
    "                control_list.append(gene[count_replicates])\n",
    "        \n",
    "        # Replicate is non-control\n",
    "        else:\n",
    "            # Do we already get all the replicates for this condition?\n",
    "            if len(treated_list) < grouped.loc[cell_type, replicate['condition'], time_point]['replicate']:\n",
    "                # Still adding replicates of current condition\n",
    "                treated_list.append(gene[count_replicates])\n",
    "                treated_indices.append(count_replicates)\n",
    "                \n",
    "        if len(control_list) == grouped.loc[cell_type, condition, time_point]['replicate'] and \\\n",
    "            len(treated_list) == grouped.loc[cell_type, replicate['condition'], time_point]['replicate']:        \n",
    "            \n",
    "            # Calculate pvalue\n",
    "            import scipy.stats as stats\n",
    "            p_coef, p_value = stats.pearsonr(control_list, treated_list)\n",
    "            p_value = round(p_value, 7)\n",
    "            #print('PEARSON COEFFICIENT: ', p_coef)\n",
    "            \n",
    "            #Controls are NaN, treated replicates ge the pvalue\n",
    "#             for c in range(len(control_list)):\n",
    "#                 p_values.append(None)\n",
    "            for t in range(len(treated_list)):\n",
    "                #p_values.append(p_value)\n",
    "                p_values[treated_indices[t]] = p_value\n",
    "                \n",
    "            # Reset\n",
    "            treated_list = list()\n",
    "            treated_indices = list()\n",
    "            if count_conditions == grouped.index.levels[1].size:\n",
    "                control_list = list()\n",
    "            \n",
    "        count_replicates += 1\n",
    "\n",
    "    p_values_list.append(p_values)\n",
    "    print('p_values: ', p_values)\n",
    "\n",
    "Xpval = np.array(p_values_list)\n",
    "\n",
    "adata.Xpval = Xpval.T\n",
    "\n",
    "#Return this:\n",
    "#Xpval.T\n",
    "# Xpval\n",
    "            \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "###################################### Calculate FDR ##########################################################\n",
    "# Yang: http://www.statsmodels.org/devel/generated/statsmodels.sandbox.stats.multicomp.multipletests.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[None None None ... 0.6836206 0.6836206 0.6836206]\n",
      " [None None None ... 0.20773019999999998 0.20773019999999998\n",
      "  0.20773019999999998]\n",
      " [None None None ... 0.96118785 0.96118785 0.96118785]\n",
      " ...\n",
      " [None None None ... 0.1481253 0.1481253 0.1481253]\n",
      " [None None None ... 0.2926852 0.2926852 0.2926852]\n",
      " [None None None ... 0.9668941 0.9668941 0.9668941]]\n"
     ]
    }
   ],
   "source": [
    "Xpval = adata.Xpval.T\n",
    "# print(Xpval)\n",
    "\n",
    "# from numpy import array, empty                                                                        \n",
    "# pvalues = array(pvalues) \n",
    "# n = float(pvalues.shape[0])                                                                           \n",
    "# new_pvalues = empty(n)\n",
    "\n",
    "replicates = get_replicate_counts(adata.obs)\n",
    "\n",
    "fdrs_list = list()\n",
    "for index, row in enumerate(Xpval):\n",
    "       \n",
    "    current_fdrs = [None] * len(row)    \n",
    "    start = 0\n",
    "    end = 0\n",
    "    pvalue_list = list()\n",
    "    pvalue_indices = list() # tuple of int values (index_of_first_replicate, number_of_replicates)\n",
    "    for i, rep_count in enumerate(replicates):\n",
    "        end += rep_count\n",
    "\n",
    "        # Take 1st replicate of group (skip None groups - controls)\n",
    "        if row[start:end][0] is not None:\n",
    "            pvalue_list.append(row[start:end][0])\n",
    "            pvalue_indices.append((start, rep_count))\n",
    "            \n",
    "            \n",
    "        start += rep_count\n",
    "        \n",
    "    n = len(pvalue_list)    \n",
    "    fdr_list = list()\n",
    "\n",
    "    pvalue_list = [ (pvalue, i) for i, pvalue in enumerate(pvalue_list) ]\n",
    "    pvalue_list.sort()\n",
    "    pvalue_list.reverse()\n",
    "    for i, vals in enumerate(pvalue_list):\n",
    "        rank = n - i\n",
    "        pvalue, index = vals\n",
    "        fdr_list.append((n/rank) * pvalue)\n",
    "    for i in range(0, int(n)-1):\n",
    "        if fdr_list[i] < fdr_list[i+1]:\n",
    "            fdr_list[i+1] = fdr_list[i]\n",
    "    for i, vals in enumerate(pvalue_list):\n",
    "        pvalue, index = vals\n",
    "        fdr_list[index] = fdr_list[i]\n",
    "    \n",
    "    \n",
    "    # Add the FDR to FDR_list for each replicate. Control replicates remain None\n",
    "    for (i, rep_count), fdr in zip(pvalue_indices, fdr_list):\n",
    "        for t in range(rep_count):\n",
    "            current_fdrs[i+t] = fdr\n",
    "    \n",
    "#     print('current_fdrs: ', current_fdrs)\n",
    "    fdrs_list.append(current_fdrs)\n",
    "        \n",
    "# print(fdrs_list)\n",
    "Xfdr = np.array(fdrs_list)\n",
    "\n",
    "print(Xfdr)\n",
    "\n",
    "#Return the transposed np.array\n",
    "#return Xfdr.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X.shape:  (18, 100)\n",
      "[ 72.  79.  40.  72.  90.   8.   3.   3.   8.  57. 100.  21.  74.  86.\n",
      "  25.  80.  16.  43.  96.  51.  28.  86.  92.  68.  98.  89.  77.  43.\n",
      "  25.   3.  59.  21.  69.  69.  59.  18.  98.  32.  97.  89.  96.  55.\n",
      "  97.  21.  54.  22.  67.  63.  24.  44.  99.  79.  97.   1.  50.   8.\n",
      "  54.  12.  95.   4.  16.  35.  18.  43.  50.  74.  94.  71.  89.  51.\n",
      "  55.   6.  72.  35.   4.  56.  42.  54.  85.  94.  93.  69.  55.  10.\n",
      "  69.  10.  53.  43.  79.  16.  98.  40.  49.  86.  98.  24.  40.  87.\n",
      "  11.  84.]\n",
      "df.shape:  (18, 103)\n",
      "0    72\n",
      "1    79\n",
      "2    40\n",
      "3    72\n",
      "4    90\n",
      "Name: 0, dtype: object\n",
      "df_mean.shape:  (6, 100)\n",
      "0    71.666664\n",
      "1    53.333332\n",
      "2    49.666668\n",
      "3    67.000000\n",
      "4    63.333332\n",
      "Name: (utricle, control, 0), dtype: float32\n",
      "Mean of 1st gene in dataset. Utricle, control, 0hrs:  71.666664\n"
     ]
    }
   ],
   "source": [
    "\n",
    "# Try grouping with scanpy https://github.com/theislab/scanpy/issues/106#issuecomment-378912055\n",
    "import pandas as pd\n",
    "df = pd.DataFrame(X)  # does not allocate new memory if X is an array, so this efficient\n",
    "df['cell_type'] = obs['cell_type'].values  # if not using assign, no copy is made\n",
    "df['condition'] = obs['condition'].values  # if not using assign, no copy is made\n",
    "df['time_point'] = obs['time_point'].values  # if not using assign, no copy is made\n",
    "df_grouped = df.groupby(['cell_type', 'condition', 'time_point'])\n",
    "df_mean = df_grouped.mean()\n",
    "df_std = df_grouped.std()\n",
    "\n",
    "# df_mean.head()\n",
    "\n",
    "# print(df_grouped.mean())\n",
    "# print(df_grouped.std())\n",
    "# print(df_grouped.sem())\n",
    "\n",
    "print('X.shape: ', X.shape)\n",
    "print(X[0,:])\n",
    "print('df.shape: ', df.shape)\n",
    "print(df.iloc[0,:].head())\n",
    "print('df_mean.shape: ', df_mean.shape)\n",
    "print(df_mean.iloc[0,:].head())\n",
    "print(\"Mean of 1st gene in dataset. Utricle, control, 0hrs: \", df_mean.loc['utricle', 'control', 0][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
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       "      <td>44.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>75.0</td>\n",
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       "      <td>74.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>...</td>\n",
       "      <td>58.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>utricle</td>\n",
       "      <td>treated</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>...</td>\n",
       "      <td>90.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>utricle</td>\n",
       "      <td>treated</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>46.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>...</td>\n",
       "      <td>67.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>utricle</td>\n",
       "      <td>treated</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>utricle</td>\n",
       "      <td>control</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>33.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>...</td>\n",
       "      <td>57.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>utricle</td>\n",
       "      <td>control</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>46.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>...</td>\n",
       "      <td>64.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>utricle</td>\n",
       "      <td>control</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>75.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>...</td>\n",
       "      <td>42.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>utricle</td>\n",
       "      <td>treated</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>56.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>98.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>utricle</td>\n",
       "      <td>treated</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>28.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>utricle</td>\n",
       "      <td>treated</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>90.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>...</td>\n",
       "      <td>65.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>utricle</td>\n",
       "      <td>control</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>100.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>...</td>\n",
       "      <td>85.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>utricle</td>\n",
       "      <td>control</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>7.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>...</td>\n",
       "      <td>71.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>utricle</td>\n",
       "      <td>control</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>25.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>...</td>\n",
       "      <td>87.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>utricle</td>\n",
       "      <td>treated</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>40.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>...</td>\n",
       "      <td>56.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>utricle</td>\n",
       "      <td>treated</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>81.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>...</td>\n",
       "      <td>20.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>utricle</td>\n",
       "      <td>treated</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>18 rows × 103 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        0     1     2     3      4     5     6     7     8     9     ...      \\\n",
       "0    72.0  79.0  40.0  72.0   90.0   8.0   3.0   3.0   8.0  57.0     ...       \n",
       "1    92.0  15.0  15.0  66.0   97.0   4.0  36.0  92.0  42.0  17.0     ...       \n",
       "2    51.0  66.0  94.0  63.0    3.0  19.0  40.0  70.0  97.0   4.0     ...       \n",
       "3    93.0  74.0  75.0   5.0  100.0   5.0  57.0  94.0   3.0  16.0     ...       \n",
       "4     1.0  76.0  40.0   2.0   42.0  37.0  18.0  14.0  19.0  75.0     ...       \n",
       "5    46.0  81.0  49.0  90.0   25.0  29.0  53.0  29.0  26.0  89.0     ...       \n",
       "6     0.0  74.0  81.0  85.0   56.0  22.0  36.0  12.0  75.0  75.0     ...       \n",
       "7    33.0  22.0  73.0  33.0   35.0  22.0  26.0  73.0  36.0  82.0     ...       \n",
       "8    46.0  30.0  45.0   2.0   11.0  89.0  84.0  55.0  39.0  84.0     ...       \n",
       "9    75.0   8.0   9.0  43.0   17.0  56.0  37.0  56.0  14.0  99.0     ...       \n",
       "10   56.0  59.0  14.0  18.0   55.0  18.0   4.0  37.0  49.0   3.0     ...       \n",
       "11   28.0  60.0  45.0  35.0   60.0  61.0  70.0  40.0  68.0  83.0     ...       \n",
       "12   90.0  46.0  67.0  71.0   39.0  72.0  48.0  49.0   8.0  36.0     ...       \n",
       "13  100.0  61.0   3.0  55.0   53.0  94.0  49.0  66.0   3.0  81.0     ...       \n",
       "14    7.0  77.0  40.0  73.0   38.0   5.0  94.0  25.0  68.0  17.0     ...       \n",
       "15   25.0   7.0  60.0  87.0    8.0  80.0  37.0  69.0  73.0  25.0     ...       \n",
       "16   40.0  82.0  49.0  10.0   46.0  20.0  74.0  77.0  86.0  60.0     ...       \n",
       "17   81.0  14.0  43.0  57.0   49.0  22.0  28.0  61.0   5.0   6.0     ...       \n",
       "\n",
       "      93    94    95     96    97    98    99  cell_type  condition  \\\n",
       "0   86.0  98.0  24.0   40.0  87.0  11.0  84.0    utricle    control   \n",
       "1   23.0  90.0  96.0   90.0  81.0  50.0   4.0    utricle    control   \n",
       "2   44.0  16.0  82.0   85.0  41.0  75.0  58.0    utricle    control   \n",
       "3   58.0  87.0  68.0    2.0  37.0   8.0  47.0    utricle    treated   \n",
       "4   90.0  35.0  28.0    2.0  44.0  66.0  26.0    utricle    treated   \n",
       "5   67.0   1.0  89.0   92.0  29.0  62.0  92.0    utricle    treated   \n",
       "6   35.0  65.0  74.0   35.0  19.0  99.0  76.0    utricle    control   \n",
       "7   57.0  48.0   6.0   44.0  58.0  19.0  97.0    utricle    control   \n",
       "8   64.0  42.0   2.0   80.0  30.0  55.0  41.0    utricle    control   \n",
       "9   42.0   0.0   7.0   18.0  10.0  29.0  38.0    utricle    treated   \n",
       "10  98.0  71.0  19.0   49.0  13.0  69.0  41.0    utricle    treated   \n",
       "11   4.0   3.0  99.0    8.0  99.0  82.0  57.0    utricle    treated   \n",
       "12  65.0  32.0  43.0   60.0  53.0   6.0  64.0    utricle    control   \n",
       "13  85.0  68.0  22.0  100.0  30.0  28.0  88.0    utricle    control   \n",
       "14  71.0  18.0  21.0   81.0  42.0  96.0   1.0    utricle    control   \n",
       "15  87.0  82.0  33.0   96.0  79.0  83.0  74.0    utricle    treated   \n",
       "16  56.0  39.0  64.0   39.0  82.0  70.0  80.0    utricle    treated   \n",
       "17  20.0  60.0  60.0   66.0   6.0  34.0  18.0    utricle    treated   \n",
       "\n",
       "    time_point  \n",
       "0            0  \n",
       "1            0  \n",
       "2            0  \n",
       "3            0  \n",
       "4            0  \n",
       "5            0  \n",
       "6           24  \n",
       "7           24  \n",
       "8           24  \n",
       "9           24  \n",
       "10          24  \n",
       "11          24  \n",
       "12          48  \n",
       "13          48  \n",
       "14          48  \n",
       "15          48  \n",
       "16          48  \n",
       "17          48  \n",
       "\n",
       "[18 rows x 103 columns]"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_grouped.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import scipy.stats as stats\n",
    "coef, pval = pearsonr()"
   ]
  }
 ],
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