Fig. 1
OMICfpp method. a) Workflow used by OMICfpp paired data analysis. The 68 paired RNA-Seq data from TCGA and PRJNA218851 BioProject were analyzed by our proposed method OMICfpp and by conventional methods edgeR and DESEq2. In the OMICfpp approach, original and randomized p-values are obtained for each paired data, applying different randomization distributions. The p-values must be aggregated using the OWA to obtain a single value per gene. The user decides, by choosing an orness, the weights assigned to the genes. Finally, a marginal gene analysis is performed and a list of genes ordered by importance according to the assigned weights is obtained. These results are compared with those obtained using edgeR. b) IL11, c) HIST2H3C and d) AC012414.3 are examples of genes with area under the cumulative distribution function, respectively. Top-left, the kernel density estimator corresponding to the original p-values of the binomial test; top-right: the corresponding cumulative distribution function of these original p-values; bottom-left: the between-pair p-values corresponding to all the values of orness used in the study; bottom-right, the complete p-values corresponding to all orness. e) Optimal orness by comparing n0 extreme genes. f) Proportion of significant genes for different α values obtained using the complete distribution. g) Density function used in “Results” section to calculate the score of Eq. 3