Integration and transfer learning of single-cell transcriptomes via cFIT

Large, comprehensive collections of single-cell RNA sequencing (scRNA-seq) datasets have been generated that allow for the full transcriptional characterization of cell types across a wide variety of biological and clinical conditions. As new methods arise to measure distinct cellular modalities, a...

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Vydané v:	Proceedings of the National Academy of Sciences - PNAS Ročník 118; číslo 10
Hlavní autori:	Peng, Minshi, Li, Yue, Wamsley, Brie, Wei, Yuting, Roeder, Kathryn
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States 09.03.2021
Predmet:	Animals Exome Sequencing Humans Machine Learning Mice RNA-Seq Single-Cell Analysis Software Transcriptome transfer learning single-cell RNA-seq brain cells data integration
ISSN:	1091-6490, 1091-6490
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