Evaluation of tools for highly variable gene discovery from single-cell RNA-seq data

Abstract Traditional RNA sequencing (RNA-seq) allows the detection of gene expression variations between two or more cell populations through differentially expressed gene (DEG) analysis. However, genes that contribute to cell-to-cell differences are not discoverable with RNA-seq because RNA-seq sam...

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Vydané v:	Briefings in bioinformatics Ročník 20; číslo 4; s. 1583 - 1589
Hlavní autori:	Yip, Shun H, Sham, Pak Chung, Wang, Junwen
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	England Oxford University Press 19.07.2019 Oxford Publishing Limited (England)
Predmet:	Animals Cluster Analysis Computational Biology Computer Simulation Databases, Nucleic Acid - statistics & numerical data Embryo cells Gene expression Gene Expression Profiling - statistics & numerical data Gene sequencing Genes Genetic diversity Genetic Variation Humans Quorum sensing Reproducibility of Results Ribonucleic acid RNA RNA-Seq - statistics & numerical data Single-Cell Analysis - statistics & numerical data Software Software packages Software Review Stem cells highly variable gene scRNA-seq single-cell RNA seq software DEG analysis
ISSN:	1467-5463, 1477-4054, 1477-4054
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