CellSIUS provides sensitive and specific detection of rare cell populations from complex single-cell RNA-seq data

Autor:	Rebekka Wegmann, Marilisa Neri, Sven Schuierer, Bilada Bilican, Huyen Hartkopf, Florian Nigsch, Felipa Mapa, Annick Waldt, Rachel Cuttat, Max R. Salick, Joe Raymond, Ajamete Kaykas, Guglielmo Roma, Caroline Gubser Keller
Jazyk:	angličtina
Rok vydání:	2019
Předmět:	Single-cell RNA sequencing Data analysis Rare cell types Clustering Software Benchmarking Biology (General) QH301-705.5 Genetics QH426-470
Zdroj:	Genome Biology, Vol 20, Iss 1, Pp 1-21 (2019)
Druh dokumentu:	article
ISSN:	1474-760X
DOI:	10.1186/s13059-019-1739-7
Popis:	Abstract We develop CellSIUS (Cell Subtype Identification from Upregulated gene Sets) to fill a methodology gap for rare cell population identification for scRNA-seq data. CellSIUS outperforms existing algorithms for specificity and selectivity for rare cell types and their transcriptomic signature identification in synthetic and complex biological data. Characterization of a human pluripotent cell differentiation protocol recapitulating deep-layer corticogenesis using CellSIUS reveals unrecognized complexity in human stem cell-derived cellular populations. CellSIUS enables identification of novel rare cell populations and their signature genes providing the means to study those populations in vitro in light of their role in health and disease.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/39c1e83d8d7d43228770031c5358d8f1 Zobrazit plný text záznamu Full text from SpringerLink View record in DOAJ