TI_PI_calculation_Code4.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d83fd15c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "import seaborn as sns\n",
    "\n",
    "import scipy.stats as sst\n",
    "\n",
    "from statannot import add_stat_annotation\n",
    "\n",
    "import functools\n",
    "\n",
    "import itertools"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "bb1a771f",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_statistics(path,col):\n",
    "    count_data=pd.read_csv(path,index_col=0)\n",
    "    count_data['Group']=count_data['sample'].str.endswith('surgery')*1\n",
    "    count_data_dict=count_data.groupby('sample').sum()['count'].to_dict()\n",
    "    count_data['percentage']=count_data.apply(lambda x:x['count']/count_data_dict[x[0]],axis=1)\n",
    "    count_data['group class']=count_data.apply(lambda x:'Biopsy' if x['Group']==0 else 'Surgery',axis=1)\n",
    "    cell_type_order=list(count_data[col].value_counts().index)\n",
    "    treatment=['Biopsy','Surgery']\n",
    "    box_pairs=get_pairs(cell_type_order,treatment)\n",
    "    return count_data,box_pairs,cell_type_order\n",
    "def get_pairs(order,treatment):\n",
    "    box_pairs=[]\n",
    "    for group in order:\n",
    "        box_pairs.append([(group,x) for x in treatment])\n",
    "    return box_pairs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c10a7020",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_ratio_df(T_cell_subtypes,colnames):\n",
    "    T_cell_subtypes_pre=[]\n",
    "    T_cell_subtypes_post=[]\n",
    "    for index,value in T_cell_subtypes.groupby(colnames):\n",
    "        key=','.join(index)\n",
    "        if 'biopsy' in key:\n",
    "            T_cell_subtypes_pre.append(key)\n",
    "        elif 'surgery' in key:\n",
    "            T_cell_subtypes_post.append(key)\n",
    "\n",
    "    patient_T_Cell_type={}\n",
    "    for index,value in T_cell_subtypes.groupby(colnames):\n",
    "        key=','.join(index)\n",
    "        patient_T_Cell_type[key]=value['percentage'].sum()\n",
    "\n",
    "    T_cell_type_ratio={}\n",
    "    tumor_change_IM={}\n",
    "    for key1,key2 in zip(T_cell_subtypes_pre,T_cell_subtypes_post):\n",
    "        pateint_val=key2.split(',')[0]\n",
    "        T_cell_type_ratio[key2]=patient_T_Cell_type[key2]/patient_T_Cell_type[key1]\n",
    "        tumor_change_IM[key2]=tumor_change[pateint_val]\n",
    "\n",
    "    T_cell_type_ratio_df=pd.DataFrame.from_dict(T_cell_type_ratio,orient='index')\n",
    "    T_cell_type_ratio_df.columns=['ratio']\n",
    "    tumor_changeIM_df=pd.DataFrame.from_dict(tumor_change_IM,orient='index')\n",
    "    tumor_changeIM_df.columns=['tumor change']\n",
    "\n",
    "\n",
    "    T_cell_type_ratio_df['tumor change'] = tumor_changeIM_df[['tumor change']]\n",
    "\n",
    "    T_cell_type_ratio_df['cell_types']=T_cell_type_ratio_df.index.str.split(',')\n",
    "\n",
    "    T_cell_type_ratio_df['cell_type']=T_cell_type_ratio_df.apply(lambda x:x['cell_types'][1],axis=1)\n",
    "\n",
    "    T_cell_type_ratio_df['log ratio'] =np.log10(T_cell_type_ratio_df['ratio'])\n",
    "    return T_cell_type_ratio_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ecdf7701",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_baseline_df(T_cell_subtypes,colnames):\n",
    "    T_cell_subtypes_pre=[]\n",
    "    T_cell_subtypes_post=[]\n",
    "    for index,value in T_cell_subtypes.groupby(colnames):\n",
    "        key=','.join(index)\n",
    "        if 'biopsy' in key:\n",
    "            T_cell_subtypes_pre.append(key)\n",
    "        elif 'surgery' in key:\n",
    "            T_cell_subtypes_post.append(key)\n",
    "\n",
    "    patient_T_Cell_type={}\n",
    "    for index,value in T_cell_subtypes.groupby(colnames):\n",
    "        key=','.join(index)\n",
    "        patient_T_Cell_type[key]=value['percentage'].sum()\n",
    "\n",
    "    T_cell_type_ratio={}\n",
    "    tumor_change_IM={}\n",
    "    for key1,key2 in zip(T_cell_subtypes_pre,T_cell_subtypes_post):\n",
    "        pateint_val=key2.split(',')[0]\n",
    "        T_cell_type_ratio[key2]=patient_T_Cell_type[key1]\n",
    "        tumor_change_IM[key2]=tumor_change[pateint_val]\n",
    "\n",
    "    T_cell_type_ratio_df=pd.DataFrame.from_dict(T_cell_type_ratio,orient='index')\n",
    "    T_cell_type_ratio_df.columns=['ratio']\n",
    "    tumor_changeIM_df=pd.DataFrame.from_dict(tumor_change_IM,orient='index')\n",
    "    tumor_changeIM_df.columns=['tumor change']\n",
    "\n",
    "\n",
    "    T_cell_type_ratio_df['tumor change'] = tumor_changeIM_df[['tumor change']]\n",
    "\n",
    "    T_cell_type_ratio_df['cell_types']=T_cell_type_ratio_df.index.str.split(',')\n",
    "\n",
    "    T_cell_type_ratio_df['cell_type']=T_cell_type_ratio_df.apply(lambda x:x['cell_types'][1],axis=1)\n",
    "\n",
    "    #T_cell_type_ratio_df['log ratio'] =np.log10(T_cell_type_ratio_df['ratio'])\n",
    "    return T_cell_type_ratio_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "e91365ad",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_subtypes,box_pairs_all,cell_type_orderall=get_statistics(\"statistics/celltype_counts.csv\",'cell_type')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "bc10a673",
   "metadata": {},
   "outputs": [],
   "source": [
    "tumor_change={'AA':-45.57,'AB':-31.26,'xx':-42.0,'cc':-20.52,'xx':-14.84,'dd':-65.63,'dd':-20.45,'dd':-31.7}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "89f4a66c",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-3-e277175031a7>:20: RuntimeWarning: invalid value encountered in double_scalars\n",
      "  T_cell_type_ratio[key2]=patient_T_Cell_type[key2]/patient_T_Cell_type[key1]\n",
      "<ipython-input-3-e277175031a7>:20: RuntimeWarning: divide by zero encountered in double_scalars\n",
      "  T_cell_type_ratio[key2]=patient_T_Cell_type[key2]/patient_T_Cell_type[key1]\n",
      "/OceanStor100D/home/sunyidi_lab/llwu/anaconda3/envs/py3.8/lib/python3.9/site-packages/pandas/core/arraylike.py:397: RuntimeWarning: divide by zero encountered in log10\n",
      "  result = getattr(ufunc, method)(*inputs, **kwargs)\n"
     ]
    }
   ],
   "source": [
    "all_tumor_change=get_ratio_df(all_subtypes,['sample','cell_type'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "60dc2b4f",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_tumor_baseline=get_baseline_df(all_subtypes,['sample','cell_type'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "05ca19c9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "0710037a",
   "metadata": {},
   "outputs": [],
   "source": [
    "def Ti_pi(slope,r_value):\n",
    "    ti=-slope/abs(slope)*r_value*r_value\n",
    "    return ti"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "23c3bf75",
   "metadata": {},
   "outputs": [],
   "source": [
    "comprehensive_cell_type={}\n",
    "for index,value in all_tumor_change.groupby('cell_type'):\n",
    "    value1=value.loc[~value['log ratio'].isin([np.inf,-np.inf,np.nan])].copy()\n",
    "    number=len(value1)\n",
    "    try:\n",
    "        slope, intercept, r_value, p_value, std_err=sst.linregress(value1['log ratio'],value1['tumor change'])\n",
    "    except ValueError:\n",
    "        print(index)\n",
    "        continue\n",
    "    ti_score=Ti_pi(slope,r_value)\n",
    "    comprehensive_cell_type[index]=[ti_score,slope,r_value,p_value,number]\n",
    "    #print(index,slope,intercept,r_value,p_value,sep=\"\\t\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "1e69cd06",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_pi(all_tumor_change,col):\n",
    "    comprehensive_cell_type={}\n",
    "    for index,value in all_tumor_change.groupby(col):\n",
    "        value1=value.loc[~value['ratio'].isin([np.inf,-np.inf,np.nan])].copy()\n",
    "        number=len(value1)\n",
    "        try:\n",
    "            slope, intercept, r_value, p_value, std_err=sst.linregress(value1['ratio'],value1['tumor change'])\n",
    "        except ValueError:\n",
    "            print(index)\n",
    "            continue\n",
    "        ti_score=Ti_pi(slope,r_value)\n",
    "        comprehensive_cell_type[index]=[ti_score,slope,r_value,p_value,number]\n",
    "    comprehensive_cell_type_ti=pd.DataFrame.from_dict(comprehensive_cell_type,orient='index')\n",
    "    comprehensive_cell_type_ti.columns=['Ti','slop','r value','p value','number']\n",
    "    comprehensive_cell_type_ti['log pvalue']=-np.log10(comprehensive_cell_type_ti['p value'])\n",
    "    return comprehensive_cell_type_ti"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "0dcc5236",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_type_base_line_ti=get_pi(all_tumor_baseline,'cell_type')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "4b304033",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_type_base_line_ti.to_csv(\"analysis_result/baseline_results/all_type_pi_update.txt\",sep=\"\\t\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "b8790702",
   "metadata": {},
   "outputs": [],
   "source": [
    "comprehensive_cell_type_ti=pd.DataFrame.from_dict(comprehensive_cell_type,orient='index')\n",
    "comprehensive_cell_type_ti.columns=['Ti','slop','r value','p value','number']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "11ce330b",
   "metadata": {},
   "outputs": [],
   "source": [
    "comprehensive_cell_type_ti['log pvalue']=-np.log10(comprehensive_cell_type_ti['p value'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "85281bde",
   "metadata": {},
   "outputs": [],
   "source": [
    "comprehensive_cell_type_ti.to_csv(\"analysis_result/comprehensive_cell_types_clinical/comprehensive_type_ti_update.txt\",sep=\"\\t\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "16936e72",
   "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>Ti</th>\n",
       "      <th>slop</th>\n",
       "      <th>r value</th>\n",
       "      <th>p value</th>\n",
       "      <th>number</th>\n",
       "      <th>log pvalue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>B cell</th>\n",
       "      <td>0.057213</td>\n",
       "      <td>-8.368844</td>\n",
       "      <td>-0.239192</td>\n",
       "      <td>0.568327</td>\n",
       "      <td>8</td>\n",
       "      <td>0.245401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Endothelial</th>\n",
       "      <td>0.086281</td>\n",
       "      <td>-7.229001</td>\n",
       "      <td>-0.293736</td>\n",
       "      <td>0.480104</td>\n",
       "      <td>8</td>\n",
       "      <td>0.318664</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Epithelial</th>\n",
       "      <td>0.106461</td>\n",
       "      <td>-6.316938</td>\n",
       "      <td>-0.326283</td>\n",
       "      <td>0.430253</td>\n",
       "      <td>8</td>\n",
       "      <td>0.366276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fibroblast</th>\n",
       "      <td>0.060174</td>\n",
       "      <td>-4.368570</td>\n",
       "      <td>-0.245305</td>\n",
       "      <td>0.558172</td>\n",
       "      <td>8</td>\n",
       "      <td>0.253232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Malignant cell</th>\n",
       "      <td>-0.172681</td>\n",
       "      <td>147.944645</td>\n",
       "      <td>0.415549</td>\n",
       "      <td>0.727179</td>\n",
       "      <td>3</td>\n",
       "      <td>0.138359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mast cell</th>\n",
       "      <td>-0.128577</td>\n",
       "      <td>13.541463</td>\n",
       "      <td>0.358577</td>\n",
       "      <td>0.429629</td>\n",
       "      <td>7</td>\n",
       "      <td>0.366906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Myeloid</th>\n",
       "      <td>0.011621</td>\n",
       "      <td>-5.540251</td>\n",
       "      <td>-0.107800</td>\n",
       "      <td>0.799436</td>\n",
       "      <td>8</td>\n",
       "      <td>0.097216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NK cell</th>\n",
       "      <td>0.056090</td>\n",
       "      <td>-10.910588</td>\n",
       "      <td>-0.236833</td>\n",
       "      <td>0.572263</td>\n",
       "      <td>8</td>\n",
       "      <td>0.242404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Neutrophil</th>\n",
       "      <td>-0.038316</td>\n",
       "      <td>3.436280</td>\n",
       "      <td>0.195744</td>\n",
       "      <td>0.642248</td>\n",
       "      <td>8</td>\n",
       "      <td>0.192297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Plasma</th>\n",
       "      <td>-0.042033</td>\n",
       "      <td>5.398257</td>\n",
       "      <td>0.205019</td>\n",
       "      <td>0.626226</td>\n",
       "      <td>8</td>\n",
       "      <td>0.203269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T cell</th>\n",
       "      <td>-0.253812</td>\n",
       "      <td>35.160358</td>\n",
       "      <td>0.503798</td>\n",
       "      <td>0.203046</td>\n",
       "      <td>8</td>\n",
       "      <td>0.692405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pDC</th>\n",
       "      <td>-0.022890</td>\n",
       "      <td>3.796806</td>\n",
       "      <td>0.151295</td>\n",
       "      <td>0.720621</td>\n",
       "      <td>8</td>\n",
       "      <td>0.142293</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Ti        slop   r value   p value  number  log pvalue\n",
       "B cell          0.057213   -8.368844 -0.239192  0.568327       8    0.245401\n",
       "Endothelial     0.086281   -7.229001 -0.293736  0.480104       8    0.318664\n",
       "Epithelial      0.106461   -6.316938 -0.326283  0.430253       8    0.366276\n",
       "Fibroblast      0.060174   -4.368570 -0.245305  0.558172       8    0.253232\n",
       "Malignant cell -0.172681  147.944645  0.415549  0.727179       3    0.138359\n",
       "Mast cell      -0.128577   13.541463  0.358577  0.429629       7    0.366906\n",
       "Myeloid         0.011621   -5.540251 -0.107800  0.799436       8    0.097216\n",
       "NK cell         0.056090  -10.910588 -0.236833  0.572263       8    0.242404\n",
       "Neutrophil     -0.038316    3.436280  0.195744  0.642248       8    0.192297\n",
       "Plasma         -0.042033    5.398257  0.205019  0.626226       8    0.203269\n",
       "T cell         -0.253812   35.160358  0.503798  0.203046       8    0.692405\n",
       "pDC            -0.022890    3.796806  0.151295  0.720621       8    0.142293"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "comprehensive_cell_type_ti"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0ec5c93c",
   "metadata": {},
   "outputs": [],
   "source": [
    "##T_cell types\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "id": "fe17c557",
   "metadata": {},
   "outputs": [],
   "source": [
    "T_cell_types,box_pairs,cell_type_order=get_statistics(\"statistics/T_cell_subtype.csv\",'T_cell_subtype')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "id": "8b08bf83",
   "metadata": {},
   "outputs": [],
   "source": [
    "T_type_tumor_change=get_ratio_df(T_cell_types,['sample','T_cell_subtype'])\n",
    "T_type_base=get_baseline_df(T_cell_types,['sample','T_cell_subtype'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "9c6f173e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_ti_pi(all_tumor_change,col):\n",
    "    comprehensive_cell_type={}\n",
    "    for index,value in all_tumor_change.groupby(col):\n",
    "        value1=value.loc[~value['log ratio'].isin([np.inf,-np.inf,np.nan])].copy()\n",
    "        number=len(value1)\n",
    "        try:\n",
    "            slope, intercept, r_value, p_value, std_err=sst.linregress(value1['log ratio'],value1['tumor change'])\n",
    "        except ValueError:\n",
    "            print(index)\n",
    "            continue\n",
    "        ti_score=Ti_pi(slope,r_value)\n",
    "        comprehensive_cell_type[index]=[ti_score,slope,r_value,p_value,number]\n",
    "    comprehensive_cell_type_ti=pd.DataFrame.from_dict(comprehensive_cell_type,orient='index')\n",
    "    comprehensive_cell_type_ti.columns=['Ti','slop','r value','p value','number']\n",
    "    comprehensive_cell_type_ti['log pvalue']=-np.log10(comprehensive_cell_type_ti['p value'])\n",
    "    return comprehensive_cell_type_ti"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "id": "7d663e1e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#T_cell_type_baseline=get_baseline_df(T_cell_types,['sample','T_cell_subtype'])\n",
    "T_cell_type_baseline_line_pi=get_pi(T_cell_type_baseline,'cell_type')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "id": "82f866df",
   "metadata": {},
   "outputs": [],
   "source": [
    "T_cell_type_ti=get_ti_pi(T_type_tumor_change,'cell_type')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "id": "d05f538c",
   "metadata": {},
   "outputs": [],
   "source": [
    "T_cell_type_ti.to_csv(\"analysis_result/T_cell_type_ti.txt\",sep=\"\\t\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "id": "42dbe46d",
   "metadata": {},
   "outputs": [],
   "source": [
    "T_cell_type_baseline_line_pi.to_csv(\"analysis_result/baseline_results/T_cell_type_baseline_pi.txt\",sep=\"\\t\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ec18a4ed",
   "metadata": {},
   "outputs": [],
   "source": [
    "T_cell_subtypes,box_pairs,cell_type_order_subtypes=get_statistics(\"statistics/T_further_subtypes_counts.csv\",'T_cell_further_subtype')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "5eb0378f",
   "metadata": {},
   "outputs": [],
   "source": [
    "T_subtype_baseline=get_baseline_df(T_cell_subtypes,['sample','T_cell_further_subtype'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8145a89d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-4-e277175031a7>:20: RuntimeWarning: divide by zero encountered in double_scalars\n",
      "  T_cell_type_ratio[key2]=patient_T_Cell_type[key2]/patient_T_Cell_type[key1]\n"
     ]
    }
   ],
   "source": [
    "T_subtype_tumor_ratio=get_ratio_df(T_cell_subtypes,['sample','T_cell_further_subtype'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "efacfb1c",
   "metadata": {},
   "outputs": [],
   "source": [
    "T_subtype_pi=get_pi(T_subtype_baseline,'cell_type')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "d16cb8cc",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ti</th>\n",
       "      <th>slop</th>\n",
       "      <th>r value</th>\n",
       "      <th>p value</th>\n",
       "      <th>number</th>\n",
       "      <th>log pvalue</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CD4 SOCS3</th>\n",
       "      <td>-0.147614</td>\n",
       "      <td>134.946607</td>\n",
       "      <td>0.384206</td>\n",
       "      <td>0.347367</td>\n",
       "      <td>8</td>\n",
       "      <td>0.459211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD4 Treg_1</th>\n",
       "      <td>0.151142</td>\n",
       "      <td>-84.458359</td>\n",
       "      <td>-0.388770</td>\n",
       "      <td>0.341175</td>\n",
       "      <td>8</td>\n",
       "      <td>0.467023</td>\n",
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       "    <tr>\n",
       "      <th>CD4 Treg_2</th>\n",
       "      <td>0.508055</td>\n",
       "      <td>-1311.317722</td>\n",
       "      <td>-0.712780</td>\n",
       "      <td>0.047209</td>\n",
       "      <td>8</td>\n",
       "      <td>1.325979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD4 naive</th>\n",
       "      <td>-0.001793</td>\n",
       "      <td>8.773146</td>\n",
       "      <td>0.042339</td>\n",
       "      <td>0.920710</td>\n",
       "      <td>8</td>\n",
       "      <td>0.035877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD8 GZMB</th>\n",
       "      <td>0.646105</td>\n",
       "      <td>-84.502446</td>\n",
       "      <td>-0.803807</td>\n",
       "      <td>0.016211</td>\n",
       "      <td>8</td>\n",
       "      <td>1.790201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD8 GZMK_1</th>\n",
       "      <td>0.009062</td>\n",
       "      <td>-11.495496</td>\n",
       "      <td>-0.095195</td>\n",
       "      <td>0.822585</td>\n",
       "      <td>8</td>\n",
       "      <td>0.084819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD8 GZMK_2</th>\n",
       "      <td>-0.406283</td>\n",
       "      <td>132.929800</td>\n",
       "      <td>0.637404</td>\n",
       "      <td>0.089121</td>\n",
       "      <td>8</td>\n",
       "      <td>1.050019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD8 KLRB1</th>\n",
       "      <td>-0.190221</td>\n",
       "      <td>155.151694</td>\n",
       "      <td>0.436143</td>\n",
       "      <td>0.280018</td>\n",
       "      <td>8</td>\n",
       "      <td>0.552813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD8 Trm</th>\n",
       "      <td>-0.106345</td>\n",
       "      <td>316.723484</td>\n",
       "      <td>0.326106</td>\n",
       "      <td>0.430518</td>\n",
       "      <td>8</td>\n",
       "      <td>0.366009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD8 proliferating</th>\n",
       "      <td>0.880695</td>\n",
       "      <td>-675.477357</td>\n",
       "      <td>-0.938454</td>\n",
       "      <td>0.000556</td>\n",
       "      <td>8</td>\n",
       "      <td>3.254718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NK_1</th>\n",
       "      <td>-0.662576</td>\n",
       "      <td>140.521407</td>\n",
       "      <td>0.813988</td>\n",
       "      <td>0.013929</td>\n",
       "      <td>8</td>\n",
       "      <td>1.856077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NK_2</th>\n",
       "      <td>-0.229638</td>\n",
       "      <td>182.462908</td>\n",
       "      <td>0.479206</td>\n",
       "      <td>0.229567</td>\n",
       "      <td>8</td>\n",
       "      <td>0.639090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gdT</th>\n",
       "      <td>-0.049546</td>\n",
       "      <td>1976.292060</td>\n",
       "      <td>0.222590</td>\n",
       "      <td>0.596224</td>\n",
       "      <td>8</td>\n",
       "      <td>0.224590</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Ti         slop   r value   p value  number  \\\n",
       "CD4 SOCS3         -0.147614   134.946607  0.384206  0.347367       8   \n",
       "CD4 Treg_1         0.151142   -84.458359 -0.388770  0.341175       8   \n",
       "CD4 Treg_2         0.508055 -1311.317722 -0.712780  0.047209       8   \n",
       "CD4 naive         -0.001793     8.773146  0.042339  0.920710       8   \n",
       "CD8 GZMB           0.646105   -84.502446 -0.803807  0.016211       8   \n",
       "CD8 GZMK_1         0.009062   -11.495496 -0.095195  0.822585       8   \n",
       "CD8 GZMK_2        -0.406283   132.929800  0.637404  0.089121       8   \n",
       "CD8 KLRB1         -0.190221   155.151694  0.436143  0.280018       8   \n",
       "CD8 Trm           -0.106345   316.723484  0.326106  0.430518       8   \n",
       "CD8 proliferating  0.880695  -675.477357 -0.938454  0.000556       8   \n",
       "NK_1              -0.662576   140.521407  0.813988  0.013929       8   \n",
       "NK_2              -0.229638   182.462908  0.479206  0.229567       8   \n",
       "gdT               -0.049546  1976.292060  0.222590  0.596224       8   \n",
       "\n",
       "                   log pvalue  \n",
       "CD4 SOCS3            0.459211  \n",
       "CD4 Treg_1           0.467023  \n",
       "CD4 Treg_2           1.325979  \n",
       "CD4 naive            0.035877  \n",
       "CD8 GZMB             1.790201  \n",
       "CD8 GZMK_1           0.084819  \n",
       "CD8 GZMK_2           1.050019  \n",
       "CD8 KLRB1            0.552813  \n",
       "CD8 Trm              0.366009  \n",
       "CD8 proliferating    3.254718  \n",
       "NK_1                 1.856077  \n",
       "NK_2                 0.639090  \n",
       "gdT                  0.224590  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T_subtype_pi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "id": "15a94072",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ti</th>\n",
       "      <th>slop</th>\n",
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       "      <th>p value</th>\n",
       "      <th>number</th>\n",
       "      <th>log pvalue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CD4 SOCS3</th>\n",
       "      <td>-0.147614</td>\n",
       "      <td>134.946607</td>\n",
       "      <td>0.384206</td>\n",
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       "      <td>8</td>\n",
       "      <td>0.459211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD4 Treg_1</th>\n",
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       "      <td>-0.388770</td>\n",
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       "      <th>CD4 Treg_2</th>\n",
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       "      <td>-1311.317722</td>\n",
       "      <td>-0.712780</td>\n",
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       "      <td>8</td>\n",
       "      <td>1.325979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD4 naive</th>\n",
       "      <td>-0.001793</td>\n",
       "      <td>8.773146</td>\n",
       "      <td>0.042339</td>\n",
       "      <td>0.920710</td>\n",
       "      <td>8</td>\n",
       "      <td>0.035877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD8 GZMB</th>\n",
       "      <td>0.646105</td>\n",
       "      <td>-84.502446</td>\n",
       "      <td>-0.803807</td>\n",
       "      <td>0.016211</td>\n",
       "      <td>8</td>\n",
       "      <td>1.790201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD8 GZMK_12</th>\n",
       "      <td>-0.123196</td>\n",
       "      <td>54.317952</td>\n",
       "      <td>0.350993</td>\n",
       "      <td>0.393942</td>\n",
       "      <td>8</td>\n",
       "      <td>0.404568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD8 KLRB1</th>\n",
       "      <td>-0.190221</td>\n",
       "      <td>155.151694</td>\n",
       "      <td>0.436143</td>\n",
       "      <td>0.280018</td>\n",
       "      <td>8</td>\n",
       "      <td>0.552813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD8 Trm</th>\n",
       "      <td>-0.106345</td>\n",
       "      <td>316.723484</td>\n",
       "      <td>0.326106</td>\n",
       "      <td>0.430518</td>\n",
       "      <td>8</td>\n",
       "      <td>0.366009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD8 proliferating</th>\n",
       "      <td>0.880695</td>\n",
       "      <td>-675.477357</td>\n",
       "      <td>-0.938454</td>\n",
       "      <td>0.000556</td>\n",
       "      <td>8</td>\n",
       "      <td>3.254718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NK_1</th>\n",
       "      <td>-0.662576</td>\n",
       "      <td>140.521407</td>\n",
       "      <td>0.813988</td>\n",
       "      <td>0.013929</td>\n",
       "      <td>8</td>\n",
       "      <td>1.856077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NK_2</th>\n",
       "      <td>-0.229638</td>\n",
       "      <td>182.462908</td>\n",
       "      <td>0.479206</td>\n",
       "      <td>0.229567</td>\n",
       "      <td>8</td>\n",
       "      <td>0.639090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gdT</th>\n",
       "      <td>-0.049546</td>\n",
       "      <td>1976.292060</td>\n",
       "      <td>0.222590</td>\n",
       "      <td>0.596224</td>\n",
       "      <td>8</td>\n",
       "      <td>0.224590</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Ti         slop   r value   p value  number  \\\n",
       "CD4 SOCS3         -0.147614   134.946607  0.384206  0.347367       8   \n",
       "CD4 Treg_1         0.151142   -84.458359 -0.388770  0.341175       8   \n",
       "CD4 Treg_2         0.508055 -1311.317722 -0.712780  0.047209       8   \n",
       "CD4 naive         -0.001793     8.773146  0.042339  0.920710       8   \n",
       "CD8 GZMB           0.646105   -84.502446 -0.803807  0.016211       8   \n",
       "CD8 GZMK_12       -0.123196    54.317952  0.350993  0.393942       8   \n",
       "CD8 KLRB1         -0.190221   155.151694  0.436143  0.280018       8   \n",
       "CD8 Trm           -0.106345   316.723484  0.326106  0.430518       8   \n",
       "CD8 proliferating  0.880695  -675.477357 -0.938454  0.000556       8   \n",
       "NK_1              -0.662576   140.521407  0.813988  0.013929       8   \n",
       "NK_2              -0.229638   182.462908  0.479206  0.229567       8   \n",
       "gdT               -0.049546  1976.292060  0.222590  0.596224       8   \n",
       "\n",
       "                   log pvalue  \n",
       "CD4 SOCS3            0.459211  \n",
       "CD4 Treg_1           0.467023  \n",
       "CD4 Treg_2           1.325979  \n",
       "CD4 naive            0.035877  \n",
       "CD8 GZMB             1.790201  \n",
       "CD8 GZMK_12          0.404568  \n",
       "CD8 KLRB1            0.552813  \n",
       "CD8 Trm              0.366009  \n",
       "CD8 proliferating    3.254718  \n",
       "NK_1                 1.856077  \n",
       "NK_2                 0.639090  \n",
       "gdT                  0.224590  "
      ]
     },
     "execution_count": 195,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T_subtype_pi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "id": "f48f6726",
   "metadata": {},
   "outputs": [],
   "source": [
    "T_subtype_pi.to_csv(\"analysis_result/T_cell_class/T_sub_type_pi.txt\",sep=\"\\t\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "2ff9bb76",
   "metadata": {},
   "outputs": [],
   "source": [
    "T_subtype_pi.to_csv(\"analysis_result/T_cell_class/T_sub_type_pi_12.txt\",sep=\"\\t\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "8f972308",
   "metadata": {},
   "outputs": [],
   "source": [
    "T_cell_subtype_ti=get_ti_pi(T_subtype_tumor_ratio,'cell_type')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "6f8d2d70",
   "metadata": {},
   "outputs": [],
   "source": [
    "T_cell_subtype_ti.to_csv(\"analysis_result/T_cell_class/T_sub_type_ti_12.txt\",sep=\"\\t\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "id": "980e6cfa",
   "metadata": {},
   "outputs": [],
   "source": [
    "#T_subtype_tumor_change=get_ratio_df(T_cell_subtypes,['sample','T_cell_further_subtype'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "id": "c74f5e4d",
   "metadata": {},
   "outputs": [],
   "source": [
    "T_cell_subtype_ti=get_ti_pi(T_subtype_tumor_ratio,'cell_type')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "id": "a97a641f",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>Ti</th>\n",
       "      <th>slop</th>\n",
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       "      <th>p value</th>\n",
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       "      <th>CD4 SOCS3</th>\n",
       "      <td>-0.044357</td>\n",
       "      <td>5.446307</td>\n",
       "      <td>0.210611</td>\n",
       "      <td>0.616627</td>\n",
       "      <td>8</td>\n",
       "      <td>0.209977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD4 Treg_1</th>\n",
       "      <td>-0.557242</td>\n",
       "      <td>30.012838</td>\n",
       "      <td>0.746487</td>\n",
       "      <td>0.033381</td>\n",
       "      <td>8</td>\n",
       "      <td>1.476506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD4 Treg_2</th>\n",
       "      <td>-0.195149</td>\n",
       "      <td>15.965329</td>\n",
       "      <td>0.441757</td>\n",
       "      <td>0.273157</td>\n",
       "      <td>8</td>\n",
       "      <td>0.563587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD4 naive</th>\n",
       "      <td>-0.268446</td>\n",
       "      <td>52.400290</td>\n",
       "      <td>0.518118</td>\n",
       "      <td>0.188386</td>\n",
       "      <td>8</td>\n",
       "      <td>0.724952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD8 GZMB</th>\n",
       "      <td>-0.224253</td>\n",
       "      <td>15.629703</td>\n",
       "      <td>0.473554</td>\n",
       "      <td>0.235901</td>\n",
       "      <td>8</td>\n",
       "      <td>0.627270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD8 GZMK_12</th>\n",
       "      <td>0.855544</td>\n",
       "      <td>-81.327724</td>\n",
       "      <td>-0.924956</td>\n",
       "      <td>0.000998</td>\n",
       "      <td>8</td>\n",
       "      <td>3.000889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD8 KLRB1</th>\n",
       "      <td>0.136929</td>\n",
       "      <td>-13.341045</td>\n",
       "      <td>-0.370039</td>\n",
       "      <td>0.366911</td>\n",
       "      <td>8</td>\n",
       "      <td>0.435439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD8 Trm</th>\n",
       "      <td>-0.281619</td>\n",
       "      <td>21.225059</td>\n",
       "      <td>0.530677</td>\n",
       "      <td>0.278708</td>\n",
       "      <td>6</td>\n",
       "      <td>0.554850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD8 proliferating</th>\n",
       "      <td>-0.550123</td>\n",
       "      <td>16.306954</td>\n",
       "      <td>0.741702</td>\n",
       "      <td>0.035168</td>\n",
       "      <td>8</td>\n",
       "      <td>1.453858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NK_1</th>\n",
       "      <td>0.003120</td>\n",
       "      <td>-2.549611</td>\n",
       "      <td>-0.055853</td>\n",
       "      <td>0.895494</td>\n",
       "      <td>8</td>\n",
       "      <td>0.047937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NK_2</th>\n",
       "      <td>-0.037778</td>\n",
       "      <td>5.690107</td>\n",
       "      <td>0.194365</td>\n",
       "      <td>0.644639</td>\n",
       "      <td>8</td>\n",
       "      <td>0.190683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gdT</th>\n",
       "      <td>0.146683</td>\n",
       "      <td>-10.791099</td>\n",
       "      <td>-0.382992</td>\n",
       "      <td>0.349023</td>\n",
       "      <td>8</td>\n",
       "      <td>0.457145</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Ti       slop   r value   p value  number  log pvalue\n",
       "CD4 SOCS3         -0.044357   5.446307  0.210611  0.616627       8    0.209977\n",
       "CD4 Treg_1        -0.557242  30.012838  0.746487  0.033381       8    1.476506\n",
       "CD4 Treg_2        -0.195149  15.965329  0.441757  0.273157       8    0.563587\n",
       "CD4 naive         -0.268446  52.400290  0.518118  0.188386       8    0.724952\n",
       "CD8 GZMB          -0.224253  15.629703  0.473554  0.235901       8    0.627270\n",
       "CD8 GZMK_12        0.855544 -81.327724 -0.924956  0.000998       8    3.000889\n",
       "CD8 KLRB1          0.136929 -13.341045 -0.370039  0.366911       8    0.435439\n",
       "CD8 Trm           -0.281619  21.225059  0.530677  0.278708       6    0.554850\n",
       "CD8 proliferating -0.550123  16.306954  0.741702  0.035168       8    1.453858\n",
       "NK_1               0.003120  -2.549611 -0.055853  0.895494       8    0.047937\n",
       "NK_2              -0.037778   5.690107  0.194365  0.644639       8    0.190683\n",
       "gdT                0.146683 -10.791099 -0.382992  0.349023       8    0.457145"
      ]
     },
     "execution_count": 199,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T_cell_subtype_ti"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "id": "76b37650",
   "metadata": {},
   "outputs": [],
   "source": [
    "T_cell_subtype_ti.to_csv(\"analysis_result/T_cell_sub_class/T_cell_subtype_ti.txt\",sep=\"\\t\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "a50d1994",
   "metadata": {},
   "outputs": [],
   "source": [
    "#T_cell_subtypes12,box_pairs,cell_type_order_subtypes=get_statistics(\"statistics/T_further_subtypes_counts_GZMK12.csv\",'T_cell_further_subtype')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "16fd81c0",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-51-e277175031a7>:20: RuntimeWarning: divide by zero encountered in double_scalars\n",
      "  T_cell_type_ratio[key2]=patient_T_Cell_type[key2]/patient_T_Cell_type[key1]\n"
     ]
    }
   ],
   "source": [
    "#T_subtype_tumor_changeGZMK12=get_ratio_df(T_cell_subtypes12,['sample','T_cell_further_subtype'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "88de889e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#T_cell_subtype12_ti=get_ti_pi(T_subtype_tumor_changeGZMK12,'cell_type')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "f996bdb1",
   "metadata": {},
   "outputs": [],
   "source": [
    "#T_cell_subtype12_ti.to_csv(\"analysis_result/T_cell_sub_class_Treg_GZMK12/T_cellsubtype12ti.txt\",sep=\"\\t\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "60694b0f",
   "metadata": {},
   "outputs": [],
   "source": [
    "myeloid_subtypes_counts,box_pairs,cell_type_order_subtypes=get_statistics(\"statistics/myeloid_subtypes_counts.csv\",'myeloid_type')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "id": "8ccc08bb",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-51-e277175031a7>:20: RuntimeWarning: divide by zero encountered in double_scalars\n",
      "  T_cell_type_ratio[key2]=patient_T_Cell_type[key2]/patient_T_Cell_type[key1]\n",
      "<ipython-input-51-e277175031a7>:20: RuntimeWarning: invalid value encountered in double_scalars\n",
      "  T_cell_type_ratio[key2]=patient_T_Cell_type[key2]/patient_T_Cell_type[key1]\n",
      "/OceanStor100D/home/sunyidi_lab/llwu/anaconda3/envs/py3.8/lib/python3.9/site-packages/pandas/core/arraylike.py:358: RuntimeWarning: divide by zero encountered in log10\n",
      "  result = getattr(ufunc, method)(*inputs, **kwargs)\n"
     ]
    }
   ],
   "source": [
    "myeloid_tumor_change=get_ratio_df(myeloid_subtypes_counts,['sample','myeloid_type'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "id": "4fcf2536",
   "metadata": {},
   "outputs": [],
   "source": [
    "myeloid_baseline=get_baseline_df(myeloid_subtypes_counts,['sample','myeloid_type'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "id": "53729a82",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Macro MRC1\n"
     ]
    }
   ],
   "source": [
    "myeloid_ti=get_ti_pi(myeloid_tumor_change,'cell_type')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "id": "e92fc479",
   "metadata": {},
   "outputs": [],
   "source": [
    "myeloid_pi=get_pi(myeloid_baseline,'cell_type')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "id": "b660fcaf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ti</th>\n",
       "      <th>slop</th>\n",
       "      <th>r value</th>\n",
       "      <th>p value</th>\n",
       "      <th>number</th>\n",
       "      <th>log pvalue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>DC CD1C</th>\n",
       "      <td>-0.442155</td>\n",
       "      <td>108.770208</td>\n",
       "      <td>0.664948</td>\n",
       "      <td>0.071987</td>\n",
       "      <td>8</td>\n",
       "      <td>1.142749</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DC IDO1</th>\n",
       "      <td>0.078703</td>\n",
       "      <td>-214.036495</td>\n",
       "      <td>-0.280540</td>\n",
       "      <td>0.500935</td>\n",
       "      <td>8</td>\n",
       "      <td>0.300219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DC TYMS</th>\n",
       "      <td>-0.026732</td>\n",
       "      <td>95.325142</td>\n",
       "      <td>0.163500</td>\n",
       "      <td>0.698857</td>\n",
       "      <td>8</td>\n",
       "      <td>0.155612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Macro CD3</th>\n",
       "      <td>0.132131</td>\n",
       "      <td>-61.047789</td>\n",
       "      <td>-0.363498</td>\n",
       "      <td>0.376098</td>\n",
       "      <td>8</td>\n",
       "      <td>0.424699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Macro CD5L</th>\n",
       "      <td>-0.511981</td>\n",
       "      <td>266.930462</td>\n",
       "      <td>0.715528</td>\n",
       "      <td>0.045971</td>\n",
       "      <td>8</td>\n",
       "      <td>1.337513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Macro FBP1</th>\n",
       "      <td>0.000146</td>\n",
       "      <td>-9.614122</td>\n",
       "      <td>-0.012096</td>\n",
       "      <td>0.977323</td>\n",
       "      <td>8</td>\n",
       "      <td>0.009962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Macro GPNMB</th>\n",
       "      <td>0.004073</td>\n",
       "      <td>-7.988316</td>\n",
       "      <td>-0.063823</td>\n",
       "      <td>0.880657</td>\n",
       "      <td>8</td>\n",
       "      <td>0.055193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Macro IGLC2</th>\n",
       "      <td>0.611129</td>\n",
       "      <td>-256.225583</td>\n",
       "      <td>-0.781748</td>\n",
       "      <td>0.021922</td>\n",
       "      <td>8</td>\n",
       "      <td>1.659121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Macro MRC1</th>\n",
       "      <td>-0.004403</td>\n",
       "      <td>4315.457143</td>\n",
       "      <td>0.066352</td>\n",
       "      <td>0.875954</td>\n",
       "      <td>8</td>\n",
       "      <td>0.057519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Macro SPINK1</th>\n",
       "      <td>-0.195222</td>\n",
       "      <td>389.335377</td>\n",
       "      <td>0.441839</td>\n",
       "      <td>0.273058</td>\n",
       "      <td>8</td>\n",
       "      <td>0.563745</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mono CCL20</th>\n",
       "      <td>0.072048</td>\n",
       "      <td>-30.507130</td>\n",
       "      <td>-0.268418</td>\n",
       "      <td>0.520368</td>\n",
       "      <td>8</td>\n",
       "      <td>0.283690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mono CCL3</th>\n",
       "      <td>-0.105732</td>\n",
       "      <td>84.004343</td>\n",
       "      <td>0.325164</td>\n",
       "      <td>0.431930</td>\n",
       "      <td>8</td>\n",
       "      <td>0.364587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mono CXCL10</th>\n",
       "      <td>-0.042478</td>\n",
       "      <td>55.594699</td>\n",
       "      <td>0.206102</td>\n",
       "      <td>0.624363</td>\n",
       "      <td>8</td>\n",
       "      <td>0.204563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mono FCN1</th>\n",
       "      <td>0.041240</td>\n",
       "      <td>-41.883711</td>\n",
       "      <td>-0.203077</td>\n",
       "      <td>0.629570</td>\n",
       "      <td>8</td>\n",
       "      <td>0.200956</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Ti         slop   r value   p value  number  log pvalue\n",
       "DC CD1C      -0.442155   108.770208  0.664948  0.071987       8    1.142749\n",
       "DC IDO1       0.078703  -214.036495 -0.280540  0.500935       8    0.300219\n",
       "DC TYMS      -0.026732    95.325142  0.163500  0.698857       8    0.155612\n",
       "Macro CD3     0.132131   -61.047789 -0.363498  0.376098       8    0.424699\n",
       "Macro CD5L   -0.511981   266.930462  0.715528  0.045971       8    1.337513\n",
       "Macro FBP1    0.000146    -9.614122 -0.012096  0.977323       8    0.009962\n",
       "Macro GPNMB   0.004073    -7.988316 -0.063823  0.880657       8    0.055193\n",
       "Macro IGLC2   0.611129  -256.225583 -0.781748  0.021922       8    1.659121\n",
       "Macro MRC1   -0.004403  4315.457143  0.066352  0.875954       8    0.057519\n",
       "Macro SPINK1 -0.195222   389.335377  0.441839  0.273058       8    0.563745\n",
       "Mono CCL20    0.072048   -30.507130 -0.268418  0.520368       8    0.283690\n",
       "Mono CCL3    -0.105732    84.004343  0.325164  0.431930       8    0.364587\n",
       "Mono CXCL10  -0.042478    55.594699  0.206102  0.624363       8    0.204563\n",
       "Mono FCN1     0.041240   -41.883711 -0.203077  0.629570       8    0.200956"
      ]
     },
     "execution_count": 208,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "myeloid_pi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "id": "49abdd65",
   "metadata": {},
   "outputs": [],
   "source": [
    "myeloid_pi.to_csv(\"analysis_result/myeloid_sub_class/myeloid_pi.txt\",sep=\"\\t\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "id": "fd7792d0",
   "metadata": {},
   "outputs": [],
   "source": [
    "myeloid_ti.to_csv(\"analysis_result/myeloid_sub_class/myeloid_ti.txt\",sep=\"\\t\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "id": "c1c67e4e",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ti</th>\n",
       "      <th>slop</th>\n",
       "      <th>r value</th>\n",
       "      <th>p value</th>\n",
       "      <th>number</th>\n",
       "      <th>log pvalue</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>DC CD1C</th>\n",
       "      <td>0.158048</td>\n",
       "      <td>-12.197669</td>\n",
       "      <td>-0.397553</td>\n",
       "      <td>0.329405</td>\n",
       "      <td>8</td>\n",
       "      <td>0.482270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DC IDO1</th>\n",
       "      <td>-0.164120</td>\n",
       "      <td>21.894303</td>\n",
       "      <td>0.405117</td>\n",
       "      <td>0.319423</td>\n",
       "      <td>8</td>\n",
       "      <td>0.495634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DC TYMS</th>\n",
       "      <td>-0.019090</td>\n",
       "      <td>5.499051</td>\n",
       "      <td>0.138168</td>\n",
       "      <td>0.767672</td>\n",
       "      <td>7</td>\n",
       "      <td>0.114824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Macro CD3</th>\n",
       "      <td>-0.136988</td>\n",
       "      <td>15.170067</td>\n",
       "      <td>0.370118</td>\n",
       "      <td>0.366800</td>\n",
       "      <td>8</td>\n",
       "      <td>0.435570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Macro CD5L</th>\n",
       "      <td>0.558781</td>\n",
       "      <td>-24.100469</td>\n",
       "      <td>-0.747517</td>\n",
       "      <td>0.252483</td>\n",
       "      <td>4</td>\n",
       "      <td>0.597768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Macro FBP1</th>\n",
       "      <td>0.314984</td>\n",
       "      <td>-9.935398</td>\n",
       "      <td>-0.561235</td>\n",
       "      <td>0.246538</td>\n",
       "      <td>6</td>\n",
       "      <td>0.608116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Macro GPNMB</th>\n",
       "      <td>0.006413</td>\n",
       "      <td>-2.668763</td>\n",
       "      <td>-0.080081</td>\n",
       "      <td>0.850490</td>\n",
       "      <td>8</td>\n",
       "      <td>0.070331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Macro IGLC2</th>\n",
       "      <td>0.872990</td>\n",
       "      <td>-21.108786</td>\n",
       "      <td>-0.934340</td>\n",
       "      <td>0.065660</td>\n",
       "      <td>4</td>\n",
       "      <td>1.182696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Macro SPINK1</th>\n",
       "      <td>0.999710</td>\n",
       "      <td>-7.509431</td>\n",
       "      <td>-0.999855</td>\n",
       "      <td>0.010839</td>\n",
       "      <td>3</td>\n",
       "      <td>1.964995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mono CCL20</th>\n",
       "      <td>-0.001642</td>\n",
       "      <td>0.477479</td>\n",
       "      <td>0.040523</td>\n",
       "      <td>0.974196</td>\n",
       "      <td>3</td>\n",
       "      <td>0.011354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mono CCL3</th>\n",
       "      <td>0.125742</td>\n",
       "      <td>-17.766325</td>\n",
       "      <td>-0.354601</td>\n",
       "      <td>0.388756</td>\n",
       "      <td>8</td>\n",
       "      <td>0.410323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mono CXCL10</th>\n",
       "      <td>-0.007712</td>\n",
       "      <td>2.514556</td>\n",
       "      <td>0.087819</td>\n",
       "      <td>0.836184</td>\n",
       "      <td>8</td>\n",
       "      <td>0.077698</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mono FCN1</th>\n",
       "      <td>-0.061166</td>\n",
       "      <td>9.649511</td>\n",
       "      <td>0.247317</td>\n",
       "      <td>0.554843</td>\n",
       "      <td>8</td>\n",
       "      <td>0.255830</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Ti       slop   r value   p value  number  log pvalue\n",
       "DC CD1C       0.158048 -12.197669 -0.397553  0.329405       8    0.482270\n",
       "DC IDO1      -0.164120  21.894303  0.405117  0.319423       8    0.495634\n",
       "DC TYMS      -0.019090   5.499051  0.138168  0.767672       7    0.114824\n",
       "Macro CD3    -0.136988  15.170067  0.370118  0.366800       8    0.435570\n",
       "Macro CD5L    0.558781 -24.100469 -0.747517  0.252483       4    0.597768\n",
       "Macro FBP1    0.314984  -9.935398 -0.561235  0.246538       6    0.608116\n",
       "Macro GPNMB   0.006413  -2.668763 -0.080081  0.850490       8    0.070331\n",
       "Macro IGLC2   0.872990 -21.108786 -0.934340  0.065660       4    1.182696\n",
       "Macro SPINK1  0.999710  -7.509431 -0.999855  0.010839       3    1.964995\n",
       "Mono CCL20   -0.001642   0.477479  0.040523  0.974196       3    0.011354\n",
       "Mono CCL3     0.125742 -17.766325 -0.354601  0.388756       8    0.410323\n",
       "Mono CXCL10  -0.007712   2.514556  0.087819  0.836184       8    0.077698\n",
       "Mono FCN1    -0.061166   9.649511  0.247317  0.554843       8    0.255830"
      ]
     },
     "execution_count": 213,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "myeloid_ti"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "e7680260",
   "metadata": {},
   "outputs": [],
   "source": [
    "T_subtype_tumor_myeloid_ti.to_csv(\"statistics/myloid_ti.txt\",sep=\"\\t\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "ae2021bd",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ti</th>\n",
       "      <th>slop</th>\n",
       "      <th>r value</th>\n",
       "      <th>p value</th>\n",
       "      <th>number</th>\n",
       "      <th>log pvalue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>DC CD1C</th>\n",
       "      <td>0.158048</td>\n",
       "      <td>-12.197669</td>\n",
       "      <td>-0.397553</td>\n",
       "      <td>0.329405</td>\n",
       "      <td>8</td>\n",
       "      <td>0.482270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DC IDO1</th>\n",
       "      <td>-0.164120</td>\n",
       "      <td>21.894303</td>\n",
       "      <td>0.405117</td>\n",
       "      <td>0.319423</td>\n",
       "      <td>8</td>\n",
       "      <td>0.495634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DC TYMS</th>\n",
       "      <td>-0.019090</td>\n",
       "      <td>5.499051</td>\n",
       "      <td>0.138168</td>\n",
       "      <td>0.767672</td>\n",
       "      <td>7</td>\n",
       "      <td>0.114824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Macro CD3</th>\n",
       "      <td>-0.136988</td>\n",
       "      <td>15.170067</td>\n",
       "      <td>0.370118</td>\n",
       "      <td>0.366800</td>\n",
       "      <td>8</td>\n",
       "      <td>0.435570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Macro CD5L</th>\n",
       "      <td>0.558781</td>\n",
       "      <td>-24.100469</td>\n",
       "      <td>-0.747517</td>\n",
       "      <td>0.252483</td>\n",
       "      <td>4</td>\n",
       "      <td>0.597768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Macro FBP1</th>\n",
       "      <td>0.314984</td>\n",
       "      <td>-9.935398</td>\n",
       "      <td>-0.561235</td>\n",
       "      <td>0.246538</td>\n",
       "      <td>6</td>\n",
       "      <td>0.608116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Macro GPNMB</th>\n",
       "      <td>0.006413</td>\n",
       "      <td>-2.668763</td>\n",
       "      <td>-0.080081</td>\n",
       "      <td>0.850490</td>\n",
       "      <td>8</td>\n",
       "      <td>0.070331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Macro IGLC2</th>\n",
       "      <td>0.872990</td>\n",
       "      <td>-21.108786</td>\n",
       "      <td>-0.934340</td>\n",
       "      <td>0.065660</td>\n",
       "      <td>4</td>\n",
       "      <td>1.182696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Macro SPINK1</th>\n",
       "      <td>0.999710</td>\n",
       "      <td>-7.509431</td>\n",
       "      <td>-0.999855</td>\n",
       "      <td>0.010839</td>\n",
       "      <td>3</td>\n",
       "      <td>1.964995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mono CCL20</th>\n",
       "      <td>-0.001642</td>\n",
       "      <td>0.477479</td>\n",
       "      <td>0.040523</td>\n",
       "      <td>0.974196</td>\n",
       "      <td>3</td>\n",
       "      <td>0.011354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mono CCL3</th>\n",
       "      <td>0.125742</td>\n",
       "      <td>-17.766325</td>\n",
       "      <td>-0.354601</td>\n",
       "      <td>0.388756</td>\n",
       "      <td>8</td>\n",
       "      <td>0.410323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mono CXCL10</th>\n",
       "      <td>-0.007712</td>\n",
       "      <td>2.514556</td>\n",
       "      <td>0.087819</td>\n",
       "      <td>0.836184</td>\n",
       "      <td>8</td>\n",
       "      <td>0.077698</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mono FCN1</th>\n",
       "      <td>-0.061166</td>\n",
       "      <td>9.649511</td>\n",
       "      <td>0.247317</td>\n",
       "      <td>0.554843</td>\n",
       "      <td>8</td>\n",
       "      <td>0.255830</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Ti       slop   r value   p value  number  log pvalue\n",
       "DC CD1C       0.158048 -12.197669 -0.397553  0.329405       8    0.482270\n",
       "DC IDO1      -0.164120  21.894303  0.405117  0.319423       8    0.495634\n",
       "DC TYMS      -0.019090   5.499051  0.138168  0.767672       7    0.114824\n",
       "Macro CD3    -0.136988  15.170067  0.370118  0.366800       8    0.435570\n",
       "Macro CD5L    0.558781 -24.100469 -0.747517  0.252483       4    0.597768\n",
       "Macro FBP1    0.314984  -9.935398 -0.561235  0.246538       6    0.608116\n",
       "Macro GPNMB   0.006413  -2.668763 -0.080081  0.850490       8    0.070331\n",
       "Macro IGLC2   0.872990 -21.108786 -0.934340  0.065660       4    1.182696\n",
       "Macro SPINK1  0.999710  -7.509431 -0.999855  0.010839       3    1.964995\n",
       "Mono CCL20   -0.001642   0.477479  0.040523  0.974196       3    0.011354\n",
       "Mono CCL3     0.125742 -17.766325 -0.354601  0.388756       8    0.410323\n",
       "Mono CXCL10  -0.007712   2.514556  0.087819  0.836184       8    0.077698\n",
       "Mono FCN1    -0.061166   9.649511  0.247317  0.554843       8    0.255830"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T_subtype_tumor_myeloid_ti"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "aa9ae6d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_tumor_change_nona=all_tumor_change.loc[~all_tumor_change['ratio'].isin([np.inf,-np.inf,np.nan,0])].copy()"
   ]
  }
 ],
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