Article

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

2021-01-29

Abstract excerpt

<title>Abstract</title> <p>The advent of single-cell RNA sequencing (scRNA-seq) technologies has revolutionized transcriptomic studies. However, integrative analysis of scRNA-seq data remains a challenge largely due to batch effects. We present single-cell Embedded Topic Model (scETM), an unsupervised deep generative model that recapitulates known cell types by inferring the latent cell topic mixtures via a varia...

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Literature Corpus work: f31b04bd-323d-56a7-a812-3b64ccb03278
DOI: 10.21203/rs.3.rs-151085/v1

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