Integrating Multiple Single-cell Multi-omics Samples with Smmit

Overview

Journal bioRxiv

Date 2023 Apr 17

PMID 37066420

Authors

Changxin Wan

Zhicheng Ji

Affiliations

Soon will be listed here.

Abstract

Multi-sample single-cell multi-omics datasets, which simultaneously measure multiple data modalities in the same cells across multiple samples, facilitate the study of gene expression, gene regulatory activities, and protein abundances on a population scale. We developed Smmit, a computational method for integrating data both across samples and modalities. Compared to existing methods, Smmit more effectively removes batch effects while preserving relevant biological information, resulting in superior integration outcomes. Additionally, Smmit is more computationally efficient and builds upon existing computational pipelines, requiring minimal effort for implementation. Smmit is an R software package that is freely available on Github: https://github.com/zji90/Smmit.

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