Article

Self-supervised contrastive learning for integrative single cell RNA-seq data analysis

2021-07-27

Abstract excerpt

Single-cell RNA-sequencing (scRNA-seq) has become a powerful tool to reveal the complex biological diversity and heterogeneity among cell populations. However, the technical noise and bias of the technology still have negative impacts on the downstream analysis. Here, we present a self-supervised Contrastive LEArning framework for scRNA-seq (CLEAR) profile representation and the downstream analysis. CLEAR overcome...

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Literature Corpus work: 13d59caa-9552-588e-8622-ee8392f296a3
DOI: 10.1101/2021.07.26.453730

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