A benchmark of batch-effect correction methods for single-cell RNA sequencing data

Abstract Background Large-scale single-cell transcriptomic datasets generated using different technologies contain batch-specific systematic variations that present a challenge to batch-effect removal and data integration. With continued growth expected in scRNA-seq data, achieving effective batch i...

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Autori principali:	Hoa Thi Nhu Tran, Kok Siong Ang, Marion Chevrier, Xiaomeng Zhang, Nicole Yee Shin Lee, Michelle Goh, Jinmiao Chen
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	BMC 2020-01-01
Serie:	Genome Biology
Soggetti:	Single-cell RNA-seq Batch correction Batch effect Integration Differential gene expression
Accesso online:	https://doi.org/10.1186/s13059-019-1850-9
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