Figure 7

Rank of test statistics in Golden Spike data, by fold change. (a-e) With RMA preprocessing in the full 3 × 3 comparison of the Golden Spike spike-in data, the overall ranks of test statistics from five methods are compared to the spiked-in fold changes. (The known fold change of 1 corresponds to non-spiked-in genes.) Both PLLM and PUMA show an overall drop in ranks for higher fold changes, while RMANOVA, NFM, and PLW show an overall increase in ranks for higher fold changes. There is a clear overall drop in NFM and PLW ranks for spiked-in genes with fold changes 1.5 and 1.7. (f) With RMA preprocessing in the same Golden Spike comparison, the distributions of estimated log fold changes are compared to the known spiked-in fold changes. There is a clear drop in estimated log fold changes for spiked-in genes with known fold changes 1.5 and 1.7. This contributes to the poorer performance of the fold-change-based methods at these fold change levels.