Expand description
Multiple testing correction methods for controlling false positives in differential expression analysis.
When testing thousands of genes simultaneously (as is common in single-cell RNA-seq analysis), the probability of false positives increases dramatically. These correction methods help control either the Family-Wise Error Rate (FWER) or False Discovery Rate (FDR).
§Available Methods
- Bonferroni: Conservative FWER control, multiplies p-values by number of tests
- Benjamini-Hochberg: FDR control, less conservative than Bonferroni
- Benjamini-Yekutieli: FDR control for dependent tests
- Holm-Bonferroni: Step-down FWER control, less conservative than Bonferroni
- Storey’s q-value: Improved FDR estimation
§Choosing a Method
- For single-cell DE analysis: Use Benjamini-Hochberg (most common)
- For very strict control: Use Bonferroni or Holm-Bonferroni
- For dependent tests: Use Benjamini-Yekutieli
- For large datasets: Consider Storey’s q-value
Functions§
- adaptive_
storey_ qvalues - Apply adaptive Storey’s q-value method with automatic lambda selection
- benjamini_
hochberg_ correction - Apply Benjamini-Hochberg (BH) procedure for controlling false discovery rate
- benjamini_
yekutieli_ correction - Apply Benjamini-Yekutieli (BY) procedure for controlling false discovery rate under dependence
- bonferroni_
correction - Apply Bonferroni correction to p-values
- hochberg_
correction - Apply Hochberg’s step-up method for controlling family-wise error rate
- holm_
bonferroni_ correction - Apply Holm-Bonferroni (step-down) method for controlling family-wise error rate
- storey_
qvalues - Apply Storey’s q-value method for controlling false discovery rate