A comparison of methods accounting for batch effects in differential expression analysis of UMI count based single cell RNA sequencing

Accounting for batch effects, especially latent batch effects, in differential expression (DE) analysis is critical for identifying true biological effects. Single-cell RNA sequencing (scRNA-seq) is a powerful tool for quantifying cell-to-cell variation in transcript abundance and characterizing cel...

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Enregistré dans:
Détails bibliographiques
Publié dans:Comput Struct Biotechnol J
Auteurs principaux: Chen, Wenan, Zhang, Silu, Williams, Justin, Ju, Bensheng, Shaner, Bridget, Easton, John, Wu, Gang, Chen, Xiang
Format: Artigo
Langue:Inglês
Publié: Research Network of Computational and Structural Biotechnology 2020
Sujets:
Research Article
Accès en ligne:https://ncbi.nlm.nih.gov/pmc/articles/PMC7163294/
https://ncbi.nlm.nih.gov/pubmed/32322368
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.csbj.2020.03.026
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