RCA2: a scalable supervised clustering algorithm that reduces batch effects in scRNA-seq data

Abstract The transcriptomic diversity of cell types in the human body can be analysed in unprecedented detail using single cell (SC) technologies. Unsupervised clustering of SC transcriptomes, which is the default technique for defining cell types, is prone to group cells by technical, rather than b...

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Vydáno v:	Nucleic acids research Ročník 49; číslo 15; s. 8505 - 8519
Hlavní autoři:	Schmidt, Florian, Ranjan, Bobby, Lin, Quy Xiao Xuan, Krishnan, Vaidehi, Joanito, Ignasius, Honardoost, Mohammad Amin, Nawaz, Zahid, Venkatesh, Prasanna Nori, Tan, Joanna, Rayan, Nirmala Arul, Ong, Sin Tiong, Prabhakar, Shyam
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	England Oxford University Press 07.09.2021
Témata:	Algorithms Animals Arthritis, Rheumatoid - genetics Bone Marrow Cells - metabolism Cluster Analysis Cohort Studies Computational Biology COVID-19 - blood COVID-19 - pathology Datasets as Topic Humans Leukocytes, Mononuclear - metabolism Leukocytes, Mononuclear - pathology Mice Organ Specificity Quality Control RNA, Small Cytoplasmic - genetics RNA-Seq - methods RNA-Seq - standards Single-Cell Analysis - methods Single-Cell Analysis - standards Transcriptome
ISSN:	0305-1048, 1362-4962, 1362-4962
On-line přístup:	Získat plný text
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