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Fig. 2 | BMC Bioinformatics

Fig. 2

From: Evaluation of linear models and missing value imputation for the analysis of peptide-centric proteomics

Fig. 2

ROC curves of the UPS1 dataset comparing our pipeline with a FDR corrected t-test. a and b show ROC curves of comparisons with a fold change of 2 (LFC of 1), where (a) shows comparison between 100 fmol and 50 fmol, and (b) shows comparison between 50 fmol and 25 fmol. c shows a comparison with a fold change of 4 (LFC of 2) comparing 100 fmol with 25 fmol. Both, LFC, and P-val indicates which parameters were varied (p-value and LFC at the same time, LFC only, and p-value only, respectively) when creating the ROC curves. LFC was changed from zero to two and p-value from 0.05 to 0.001, simultaneously or separately. When only LFC was changed the p-value was fixed to 0.05, and when the p-value was changed LFC was fixed to zero. Lower LFC cut-off was set to –infinity as there was no TP with a decreasing fold change. “Limma” indicates that our pipeline utilizing limma was used with 100 imputations while t-test implies that a FDR corrected t-test was used on a single imputed dataset. Y-axis show TPR and x-axis show FPR expressed as a percentage (TPR*100, FPR*100, respectively)

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