Iterative single-cell multi-omic integration using online learning

Integrating large single-cell gene expression, chromatin accessibility and DNA methylation datasets requires general and scalable computational approaches. Here we describe online integrative non-negative matrix factorization (iNMF), an algorithm for integrating large, diverse and continually arrivi...

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Veröffentlicht in:	Nature biotechnology Jg. 39; H. 8; S. 1000 - 1007
Hauptverfasser:	Gao, Chao, Liu, Jialin, Kriebel, April R., Preissl, Sebastian, Luo, Chongyuan, Castanon, Rosa, Sandoval, Justin, Rivkin, Angeline, Nery, Joseph R., Behrens, Margarita M., Ecker, Joseph R., Ren, Bing, Welch, Joshua D.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Nature Publishing Group US 01.08.2021 Nature Publishing Group
Schlagworte:	631/114/1305 631/114/2401 Agriculture Algorithms Analysis Animals Bioinformatics Biomedical and Life Sciences Biomedical Engineering/Biotechnology Biomedicine Biotechnology Chromatin Computational Biology - methods Computer applications Cortex (motor) Datasets Deoxyribonucleic acid DNA DNA methylation Gene expression Gene sequencing Integration Iterative methods Life Sciences Machine Learning Methods Methylation Mice Multivariate Analysis RNA sequencing Single-Cell Analysis - methods Streaming Transcriptome - genetics Transcriptomics United States
ISSN:	1087-0156, 1546-1696, 1546-1696
Online-Zugang:	Volltext
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