Article

scMoE: single-cell mixture of experts for learning hierarchical, cell-type-specific, and interpretable representations from heterogeneous scRNA-seq data

2024-10-25

Abstract excerpt

Advancements in single-cell transcriptomics methods have resulted in a wealth of single-cell RNA sequencing (scRNA-seq) data. Methods to learn cell representation from atlas-level scRNA-seq data across diverse tissues can shed light into cell functions implicated in diseases such as cancer. However, integrating large-scale and heterogeneous scRNA-seq data is challenging due to the disparity of cell-types and batch...

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Literature Corpus work: 35559b8c-8d8e-5e60-a487-506c6a46a21a
DOI: 10.1101/2024.10.24.620111

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