Comparison of confound adjustment methods in the construction of gene co-expression networks

Abstract

Adjustment for confounding sources of expression variation is an important preprocessing step in large gene expression studies, but the effect of confound adjustment on co-expression network analysis has not been well-characterized. Here, we demonstrate that the choice of confound adjustment method can have a considerable effect on the architecture of the resulting co-expression network. We compare standard and alternative confound adjustment methods and provide recommendations for their use in the construction of gene co-expression networks from bulk tissue RNA-seq datasets.

Keywords: Batch effects; Co-expression; Complex traits; Confound; Covariate; Module discovery; Normalization; RNA-seq.