课前准备---空间通讯信号流COMMOT（封装版）

#! usr/python
####zhaoyunfei
####20240715
####https://commot.readthedocs.io/en/latest/index.html
####taskset -c 20 python
import argparse

parse=argparse.ArgumentParser(description='COMMOT')
parse.add_argument('--sp_input',help='the input file of matrix for spatial',type=str,required = True)
parse.add_argument('--sample',help='the sample name',type=str,required = True)
parse.add_argument('--species',help='the species',type=str,required = True,choices = ['mouse','human'])
parse.add_argument('--outdir',help='the outdir',type=str,required = True)

argv=parse.parse_args()
sp_input=args.sp_input
sample = args.sample
species = args.species
outdir = args.outdir


import os
import gc
import ot
import pickle
import anndata
import scanpy as sc
import pandas as pd
import numpy as np
from scipy import sparse
from scipy.stats import spearmanr, pearsonr
from scipy.spatial import distance_matrix
import matplotlib.pyplot as plt

import commot as ct


adata = sc.read_visium(sp_input,library_id = sample)

adata.var_names_make_unique()

sc.pp.normalize_total(adata, inplace=True)

sc.pp.log1p(adata)

adata_dis500 = adata.copy()

sc.pp.highly_variable_genes(adata, min_mean=0.0125, max_mean=3, min_disp=0.5)

adata = adata[:, adata.var.highly_variable]

sc.tl.pca(adata, svd_solver='arpack')

sc.pp.neighbors(adata, n_neighbors=10, n_pcs=20)

sc.tl.umap(adata)

sc.tl.leiden(adata, resolution=0.4)

df_cellchat = ct.pp.ligand_receptor_database(species=species, signaling_type='Secreted Signaling', database='CellChat')

df_cellchat_filtered = ct.pp.filter_lr_database(df_cellchat, adata_dis500, min_cell_pct=0.05)
###限速
ct.tl.spatial_communication(adata_dis500,database_name='cellchat', df_ligrec=df_cellchat_filtered, dis_thr=500, heteromeric=True, pathway_sum=True)

for pathway in list(set(df_cellchat_filtered.iloc[:,2])):

    ct.tl.communication_direction(adata_dis500, database_name='cellchat', pathway_name=pathway, k=5)

    ct.pl.plot_cell_communication(adata_dis500, database_name='cellchat', pathway_name=pathway, plot_method='grid', background_legend=True,scale=0.00001, ndsize=8, grid_density=0.4, summary='sender', background='image', clustering='leiden', cmap='Alphabet',normalize_v = True, normalize_v_quantile=0.995)

    plt.savefig(outdir + '/' + sample + 'signal.arrow.grid.spatial.png',bbox_inches = 'tight')

    ct.pl.plot_cell_communication(adata_dis500, database_name='cellchat', pathway_name=pathway, plot_method='stream', background_legend=True,scale=0.00001, ndsize=8, grid_density=0.4, summary='sender', background='image', clustering='leiden', cmap='Alphabet',normalize_v = True, normalize_v_quantile=0.995)

    plt.savefig(outdir + '/' + sample + 'signal.arrow.stream.spatial.png',bbox_inches = 'tight')