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Figure 2 | BMC Bioinformatics

Figure 2

From: GSVA: gene set variation analysis for microarray and RNA-Seq data

Figure 2

Comparison of statistical power and type-I error rate between GSVA, PLAGE, single sample GSEA (ssGSEA) and combined z-score (zscore). The averaged results of 1,000 simulations are depicted as function of the sample size on the x-axis, for each of the GSE methods. On the y-axis either the statistical power (A, C, E, G) or the empirical type-I error rate (B, D, F, H) is shown. Data were simulated from a linear additive model with sample and probe effects (see Methods) for p=1,000 genes. GSE scores were calculated with each method with respect to two gene sets, one of them differentially expressed (DE) and the other one not. Statistical power and empirical type-I error rates were estimated by performing a t-test on the DE and non-DE gene sets, respectively, at a significance level of α=0.05. These simulations were carried out under the following four different scenarios for the DE gene set: (A,B) weak signal-to-noise ratio, 50% of DE genes in the DE gene set; (C,D) strong signal-to-noise ratio, 50% of DE genes in the DE gene set; (E, F) weak signal-to-noise ratio, 80% of DE genes in the DE gene set; (G, H) strong signal-to-noise ratio, 80% of DE genes in the DE gene set.

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