/SCOTCH

SCOTCH is a Single-Cell multi-modal integration method leveraging the Optimal Transport algorithm and a cell matCHing strategy

Primary LanguageJupyter NotebookGNU General Public License v3.0GPL-3.0

SCOTCH v1.0.0

Cross-modal matching and integration of single-cell multi-omics data

Penghui Yang, Kaiyu Jin, Lijun Jin, ..., Xiaohui Fan*

SCOTCH is a computational method that leverages the optimal transport algorithm and a cell matching strategy to integrate scRNA-seq and scATAC-seq data. SCOTCH takes into account the adverse effects of cell type abundance and cell number differences on data integration during the calculation process, and predicts cell pairing relationships to meet the needs of downstream in-depth analysis.

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Installation of SCOTCH

pot 0.8.2 numpy 1.22.4 pandas 1.4.3 scikit-learn 1.2.0 scipy 1.8.1 scanpy 1.9.1 anndata 0.7.5 igraph 0.10.8 louvain 0.7.1 matplotlib 3.5.2


pip install scotch-sc

Tutorials

We have applied SCOTCH on different tissues of multiple species, here we give step-by-step tutorials for application scenarios. And datasets in .h5ad fomat can be downloaded from Google Drive.

About

Should you have any questions, please feel free to contact the author of the manuscript, Mr. Penghui Yang (yangph@zju.edu.cn).

References