Article

Learning interpretable cellular and gene signature embeddings from single-cell transcriptomic data

2021-01-15

Abstract excerpt

The advent of single-cell RNA sequencing (scRNA-seq) technologies has revolutionized transcriptomic studies. However, large-scale integrative analysis of scRNA-seq data remains a challenge largely due to unwanted batch effects and the limited transferabilty, interpretability, and scalability of the existing computational methods. We present single-cell Embedded Topic Model (scETM). Our key contribution is the util...

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Literature Corpus work: 01388340-f6ae-51a9-aacb-a63fbee44c62
DOI: 10.1101/2021.01.13.426593

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