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Integrating multiple single-cell multi-omics samples with Smmit.
Wan, Changxin; Ji, Zhicheng.
Afiliação
  • Wan C; Program of Computational Biology and Bioinformatics, Duke University School of Medicine, Durham, 27705, NC, USA.
  • Ji Z; Program of Computational Biology and Bioinformatics, Duke University School of Medicine, Durham, 27705, NC, USA.
bioRxiv ; 2023 Apr 06.
Article em En | MEDLINE | ID: mdl-37066420
ABSTRACT
Multi-sample single-cell multi-omics datasets, which simultaneously measure multiple data modalities in the same cells and in multiple samples, facilitate the study of gene expression and gene regulatory activities on a population scale. Existing integration methods can integrate either multiple samples or multiple modalities, but not both simultaneously. To address this limitation, we developed Smmit, a computational pipeline that leverages existing integration methods to simultaneously integrate both samples and modalities and produces a unified representation of reduced dimensions. We demonstrate Smmit's capability to integrate information across samples and modalities while preserving cell type differences in two real datasets. Smmit is an R software package that is freely available at Github https//github.com/zji90/Smmit.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article