An empirical assessment of validation practices for molecular classifiers.

ABSTRACT: Proposed molecular classifiers may be overfit to idiosyncrasies of noisy genomic and proteomic data. Cross-validation methods are often used to obtain estimates of classification accuracy, but both simulations and case studies suggest that, when inappropriate methods are used, bias may ensue. Bias can be bypassed and generalizability can be tested by external (independent) validation. We evaluated 35 studies that have reported on external validation of a molecular classifier. We extracted information on study design and methodological features, and compared the performance of molecular classifiers in internal cross-validation versus external validation for 28 studies where both had been performed. We demonstrate that the majority of studies pursued cross-validation practices that are likel

SUBMITTER: Castaldi PJ 

PROVIDER: S-EPMC3088312 | biostudies-literature | 2011 May

REPOSITORIES: biostudies-literature