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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...

תיאור מלא

שמור ב:
מידע ביבליוגרפי
הוצא לאור ב:Comput Struct Biotechnol J
Main Authors: Chen, Wenan, Zhang, Silu, Williams, Justin, Ju, Bensheng, Shaner, Bridget, Easton, John, Wu, Gang, Chen, Xiang
פורמט: Artigo
שפה:Inglês
יצא לאור: Research Network of Computational and Structural Biotechnology 2020
נושאים:
גישה מקוונת: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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