Fig. 2
From: Comparison of RNA-seq and microarray-based models for clinical endpoint prediction
Performances of RNA-seq- and microarray-based models to predict clinical endpoints in the validation cohorts. a Schematic overview of gene expression profiles generated by RNA-seq (n = 9 per sample) and microarray (n = 1 per sample). CL, Cufflinks; MAV, Magic-AceView; TAV, TopHat-AceView; TUC, TopHat-UCSC. b Distribution of MCC values of all models for each endpoint according to the technical platform (MA, microarray). Boxes indicate the 25 % and 75 % percentiles, and whiskers indicate the 5 % and 95 % percentiles; (*), P <0.05; two-sided T-test was performed for statistical testing. c, d Model performance of internal validation compared with external validation based on (c) microarray and (d) RNA-seq expression data in terms of MCC