Robust Microarray Meta-Analysis Identifies Differentially Expressed Genes for Clinical Prediction

Figure 3

Rating meta-analysis methods by prediction performance when combining all available datasets. Each meta-analysis method (rank average, rank products, Wang, mDEDS, Choi, and naive) is rated relative to its peers. We assess performance rating across three factors: (1) clinical application (breast cancer: BC, renal cancer: RC, and pancreatic cancer: PC), (2) data platform heterogeneity (homogeneous: orange, heterogeneous: blue), and (3) classifier (logistic regression: LR, diagonal LDA: DLDA and linear SVM). For each combination of factors, the rating of each meta-analysis method is represented by an additive bar. Methods with higher absolute prediction performance receive higher ratings (and longer bars). When considering absolute prediction performance, rank average, with a mean overall rating of 4.56, performs consistently well compared to its peers.