Factors influencing the statistical power of complex data analysis protocols for molecular signature development from microarray data.

ABSTRACT:

Background

Critical to the development of molecular signatures from microarray and other high-throughput data is testing the statistical significance of the produced signature in order to ensure its statistical reproducibility. While current best practices emphasize sufficiently powered univariate tests of differential expression, little is known about the factors that affect the statistical power of complex multivariate analysis protocols for high-dimensional molecular signature development.

Methodology/principal findings

We show that choices of specific components of the analysis (i.e., error metric, classifier, error estimator and event balancing) have large and compounding effects on statistical power. The effects are demonstrated empirically by an analysis of 7 of the l

SUBMITTER: Aliferis CF 

PROVIDER: S-EPMC2654113 | biostudies-literature | 2009

REPOSITORIES: biostudies-literature