Figure 5

Pseudo code analysis of differentially distributed features. The pseudocode in the left panel illustrates the computation of the ANOVA test statistic a at the example of the continuous features in C. The design g specifies the mapping of patients to clusters. A permuted test is calculated by shuffling values in rows of the matrix C 100 times, computing their associated test statistics a’ and pushing their relative ranks and the relative ranks of a separately into arrays r’ and r, respectively. The backslash notation denotes the removal of an element, i.e. in a’ = a’\max(a’), the entry with the highest value is removed from a’. Analogously, the Fisher test statistic f is calculated for the discrete features in D (pseudo code in the right panel). Finally, FDRs are calculated by comparing the relative ranks from the true statistics r vs. the relative ranks from the permuted statistics r’ across discrete and continuous features (pseudocode in lower panel).