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

Alanna C. Cote, Hannah E. Young, Laura M. Huckins

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number44
JournalGenome Biology
Volume23
Issue number1
DOIs
StatePublished - Dec 2022

Keywords

  • Batch effects
  • Co-expression
  • Complex traits
  • Confound
  • Covariate
  • Module discovery
  • Normalization
  • RNA-seq

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