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Table 2 Comparison of methods.

From: Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data

Evaluation Cuffdiff DESeq edgeR limmaVoom PoissonSeq baySeq
Normalization and clustering All methods performed equally well
DE detection accuracy measured by AUC at increasing qRT-PCR cutoff Decreasing Consistent Consistent Decreasing Increases up to log expression change ≤ 2.0 Consistent
Null model type I error High number of FPs Low number of FPs Low number of FPs Low Number of FPs Low number of FPs Low number of FPs
Signal-to-noise vs P value correlation for genes detected in one condition Poor Poor Poor Good Moderate Good
Support for multi-factored experiments No Yes Yes Yes No No
Support DE detection without replicated samples Yes Yes Yes No Yes No
Detection of differential isoforms Yes No No No No No
Runtime for experiments with three to five replicates on a 12 dual-core 3.33 GHz, 100 G RAM server Hours Minutes Minutes Minutes Seconds Hours
  1. AUC, area under curve; DE, differential expression; FP, false positive.