title: Gene co-expression analysis for functional classification and gene-disease predictions.
abstract: Gene co-expression networks can be used to associate genes of unknown function with biological processes, to prioritize candidate disease genes or to discern transcriptional regulatory programmes. With recent advances in transcriptomics and next-generation sequencing, co-expression networks constructed from RNA sequencing data also enable the inference of functions and disease associations for non-coding genes and splice variants. Although gene co-expression networks typically do not provide information about causality, emerging methods for differential co-expression analysis are enabling the identification of regulatory genes underlying various phenotypes. Here, we introduce and guide researchers through a (differential) co-expression analysis. We provide an overview of methods and tools used to create and analyse co-expression networks constructed from gene expression data, and we explain how these can be used to identify genes with a regulatory role in disease. Furthermore, we discuss the integration of other data types with co-expression networks and offer future perspectives of co-expression analysis.
authors.affiliation: Department of Genetics, UMCG HPC CB50, RB Groningen, Netherlands.
authors.forename: Sipko
authors.initials: S
authors.lastname: van Dam
authors.affiliation: Department of Genetics, UMCG HPC CB50, RB Groningen, Netherlands.
authors.forename: Urmo
authors.initials: U
authors.lastname: Võsa
authors.affiliation: Department of Genetics, UMCG HPC CB50, RB Groningen, Netherlands.
authors.forename: Adriaan
authors.initials: A
authors.lastname: van der Graaf
authors.affiliation: Department of Genetics, UMCG HPC CB50, RB Groningen, Netherlands.
authors.forename: Lude
authors.initials: L
authors.lastname: Franke
authors.affiliation: Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool, UK.
authors.forename: João Pedro
authors.initials: JP
authors.lastname: de Magalhães
mesh_terms: D019295:Computational Biology / Q000379:methods*; D004194:Disease / Q000145:classification* / Q000235:genetics*; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D005796:Genes; D006801:Humans; D010641:Phenotype