miRWoods: Enhanced precursor detection and stacked random forests for the sensitive detection of microRNAs
Fig 3
Evaluation of miRWoods performance.
a Euler diagrams comparing predictions from miRWoods and miRDeep with annotations from miRBase for human MCF-7 cytoplasmic extract b A scatterplot comparing the miRWoods decision value to the log fold change in Dicer knockdown cells compared to wild-type cells. c Scatter-boxplot comparing the log fold change for Dicer knockout to wild type for unprocessed read regions, miRBase annotations, and predictions from miRWoods, miRDeep, and miReap for MCF-7 (cytoplasmic fraction). Black dots indicate predictions that are unique to this method. d Precision-recall (PR) Curve and AUPRC of miRWoods predictions for human including MCF-7 (total cell content), MCF-7 (cytoplasmic fraction), cell lines, and liver. e Euler Diagrams comparing predictions from miRWoods and miRDeep with annotations from miRBase for human liver. f Precision Recall Curve and AUPRC of miRWoods predictions for mouse tissues including brain, embryo, newborn, testes, and ovaries sets. g Euler Diagrams comparing predictions from miRWoods and miRDeep2 with annotations from miRBase for mouse ovary.