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Stratified Test Alleviates Batch Effects in Single-Cell Data

  • Shaoheng Liang
  • Qingnan Liang
  • Rui Chen
  • Ken ChenEmail author
Conference paper
  • 48 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12099)

Abstract

Analyzing single-cell sequencing data across batches is challenging. We find that the Van Elteren test, a stratified version of Wilcoxon rank-sum test, elegantly mitigates the problem. We also modified the common language effect size to supplement this test, further improving its utility. On both simulated and real patient data we show the ability of Van Elteren test to control for false positives and false negatives. The effect size also estimates the differences between cell types more accurately.

Keywords

scRNA-seq analysis Differential expression analysis Batch effect Wilcoxon rank-sum test Van Elteren test 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Rice UniversityHoustonUSA
  2. 2.The University of Texas MD Anderson Cancer CenterHoustonUSA
  3. 3.Baylor College of MedicineHoustonUSA

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