Proportion statistics to detect differentially expressed genes: a comparison with log-ratio statistics

BMC Bioinformatics

Table 1 Simulation comparing test statistics for , , , limma/EBA, edgeR, and DESeq with a sample size of n = 20 under four distributional assumptions.

	Exponential		Poisson		Binomial		Normal
	fc = 1	fc = 3	fc = 1	fc = 3	fc = 1	fc = 3	fc = 1	fc = 3
	0.051	0.742	0.004	0.116	0.047	1.000	0.050	1.000
+ 0.05	0.051	0.742	0.038	0.757	0.047	1.000	0.050	1.000
+ 0.5	0.051	0.742	0.044	0.943	0.047	1.000	0.050	1.000
	0.975	1.000	0.045	1.000	0.048	1.000	0.003	1.000
	0.055	0.773	0.047	0.881	0.047	1.000	0.050	1.000
	0.975	1.000	0.045	1.000	0.048	1.000	0.003	1.000
EBA	0.051	0.781	0.048	1.000	0.047	1.000	0.052	1.000
edger	NA	NA	0.033	1.000	0.014	1.000	NA	NA
DESeq	NA	NA	0.042	1.000	0.047	1.000	NA	NA

The exponential distribution has rate parameter 1/4000, the Poisson has rate parameter 3, the binomial has size 10000; and the normal has mean 10 and standard deviation 2. Each entry is proportion of times the null hypothesis was rejected at α = 0.05, out of 1000 simulations. The null hypothesis of no differential expression is equivalent to a fold change of one (fc = 1). When the fold change is three, we are calculating the power to detect differential expression (fc = 3). Tables for other distributional parameters may be found in Additional file 1. These tables also include a greater range of sample sizes and fold changes.

ISSN: 1471-2105