GWENA: gene co-expression networks analysis and extended modules characterization in a single Bioconductor package

Abstract Background Network-based analysis of gene expression through co-expression networks can be used to investigate modular relationships occurring between genes performing different biological functions. An extended description each the network modules is therefore a critical step understand underlying processes contributing disease or phenotype. Biological integration, topology study and conditions comparison (e.g. wild vs mutant) are main methods do so, but date no tool combines them all into single pipeline. Results Here we present GWENA, new R package that integrates construction whole characterization detected set enrichment, phenotypic association, hub detection, topological metric computation, differential co-expression. To demonstrate its performance, applied GWENA on two skeletal muscle datasets from young old patients GTEx study. Remarkably, prioritized whose involvement was unknown in development growth. Moreover, insights variations patterns were identified. The known phenomena connectivity loss associated with aging found coupled global reorganization leading related Conclusion an available Bioconductor ( https://bioconductor.org/packages/release/bioc/html/GWENA.html ) has been developed perform networks. Thanks information as well co-expression, helps dissect role diseases targeted phenotypes. goes beyond existing packages by including tools fully characterize modules, such additional enrichment databases, visualization.