Fig. 4
From: Comparison of RNA-seq and microarray-based models for clinical endpoint prediction
a Contribution of different factors to the variability of prediction results as assessed by variance component analysis. (*), P <0.05; (**), P <0.01. The factors platform, RNA-seq pipeline, feature level, analysis team, classification method, and model size were analyzed both independently of the endpoint (white box), and taking a potential endpoint-dependence into account (gray box). b Best linear unbiased predictor (BLUP) estimates for the log10(model size) as the single factor contributing significantly to the prediction variability independent of the endpoint. Note that BLUPs are centered around zero and effectively average over all other effects. BLUPs for Log10(Model Size) indicate that models with 100 to 1,000 features perform better than those with fewer or more features