Article

Explainable deep neural networks for predicting sample phenotypes from single-cell transcriptomics

2024-12-06

Abstract excerpt

Recent advances in single-cell RNA-Seq (scRNA-Seq) technologies have revolutionized our ability to gather molecular insights into different phenotypes, such as diseases, at the level of individual cells. The analysis of the resulting data poses significant challenges due to their sparsity and large volume, and proper statistical methods are required to analyze and extract information from scRNA-Seq datasets. Sampl...

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Literature Corpus work: c61360d9-2a31-5851-afcf-8948a12f3ca2
DOI: 10.1101/2024.12.03.626549

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