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

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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Bibliographic Details
Main Authors: Hoa Thi Nhu Tran, Kok Siong Ang, Marion Chevrier, Xiaomeng Zhang, Nicole Yee Shin Lee, Michelle Goh, Jinmiao Chen
Format: Article
Language:English
Published: BMC 2020-01-01
Series:Genome Biology
Subjects:
Single-cell RNA-seq
Batch correction
Batch effect
Integration
Differential gene expression
Online Access:https://doi.org/10.1186/s13059-019-1850-9

Internet

https://doi.org/10.1186/s13059-019-1850-9

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