CSI-GEP: A GPU-based unsupervised machine learning approach for recovering gene expression programs in atlas-scale single-cell RNA-seq data

Summary: Exploratory analysis of single-cell RNA sequencing (scRNA-seq) typically relies on hard clustering over two-dimensional projections like uniform manifold approximation and projection (UMAP). However, such methods can severely distort the data and have many arbitrary parameter choices. Metho...

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Главные авторы:	Xueying Liu, Richard H. Chapple, Declan Bennett, William C. Wright, Ankita Sanjali, Erielle Culp, Yinwen Zhang, Min Pan, Paul Geeleher
Формат:	Artigo
Язык:	Inglês
Опубликовано:	Elsevier 2025-01-01
Серии:	Cell Genomics
Предметы:	single-cell RNA-seq unsupervised machine learning single-cell genomics
Online-ссылка:	http://www.sciencedirect.com/science/article/pii/S2666979X24003689
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