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Cell-cell communications inference for spatial transcriptomics data via optimal transport.

Project description


Screening cell-cell communication in spatial transcriptomics via collective optimal transport



Install from PyPI by pip install commot or install from source by cd to this directory and pip install .

[Optional] Install tradeSeq in R to analyze the CCC differentially expressed genes.
Currently, tradeSeq version 1.0.1 with R version 3.6.3 has been tested to work.
In order for the R-python interface to work properly, rpy2==3.4.2 and anndata2ri==1.0.6 should be installed. To use this feature, install from PyPI by pip install commot[tradeSeq] or from source by pip install .[tradeSeq].


Basic usage

Import packages

import commot as ct
import scanpy as sc
import pandas as pd
import numpy as np

Load a spatial dataset
(e.g., a Visium dataset)

adata = sc.datasets.visium_sge(sample_id='V1_Mouse_Brain_Sagittal_Posterior')

Basic processing

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

Specify ligand-receptor pairs

LR=np.array([['Tgfb1', 'Tgfbr1_Tgfbr2', 'Tgfb_pathway'],['Tgfb2', 'Tgfbr1_Tgfbr2', 'Tgfb_pathway'],['Tgfb3', 'Tgfbr1_Tgfbr2', 'Tgfb_pathway']],dtype=str)
df_ligrec = pd.DataFrame(data=LR)

(or use pairs from a ligand-receptor database df_ligrec=ct.pp.ligand_receptor_database(database='CellChat', species='mouse').)

Construct CCC networks
Use collective optimal transport to construct CCC networks for the ligand-receptor pairs with a spatial distance constraint of 200 (coupling between cells with distance greater than 200 is prohibited). For example, the spot-by-spot matrix for the pair Tgfb1 (ligand) and Tgfbr1_Tgfbr2 (receptor)is stored in adata.obsp['commot-user_database-Tgfb1-Tgfbr1_Tgfbr2']. The total sent or received signal for each pair is stored in adata.obsm['commot-user_database-sum-sender'] and adata.obsm['commot-user_database-sum-receiver'].,
    database_name='user_database', df_ligrec=df_ligrec, dis_thr=200, heteromeric=True)


See the documentation at for all the APIs to perform visualization and analyses such as visualizing spatial signaling direction and identifying CCC differentially expressed genes.


Cang, Zixuan, Yanxiang Zhao, Axel A. Almet, Adam Stabell, Raul Ramos, Maksim Plikus, Scott X. Atwood, and Qing Nie. "Screening cell-cell communication in spatial transcriptomics via collective optimal transport." bioRxiv (2022): 505185

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