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  • 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.
Subject
  • Meta-analysis
  • Clinical research
  • Mathematical and quantitative methods (economics)
  • Medical statistics
  • Pharmaceutical industry
  • Spam filtering
  • Statistical hypothesis testing
  • Educational psychology research methods
  • Effect size
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