Additional file 8.

Supplementary Figure S7. SVM-based effect size estimation for the biomarkers found for the Rag2-/- versus T-bet-/-xRag2-/- comparison reported in Figure 3 of the manuscript. The LDA-based approach for assessing effect size (Figure 3) is closer to the biological follow-up experiments and is more visually consistent. The reason for LDA superiority over SVM approaches for effect size estimation is theoretically connected with the ability of LDA to find the axis with the highest variance, and the SVM effort on evaluating the combined feature predictive power rather than single feature relevance. It is worth specifying that the effect size estimation accuracy of an algorithm is not directly connected with its predictive ability (SVM approaches are usually considered more accurate than LDA for prediction).

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Segata et al. Genome Biology 2011 12:R60   doi:10.1186/gb-2011-12-6-r60