MultiWGCNA: an R package for deep mining gene co-expression networks in multi-trait expression data.

ABSTRACT:

Background

Gene co-expression networks represent modules of genes with shared biological function, and have been widely used to model biological pathways in gene expression data. Co-expression networks associated with a specific trait can be constructed and identified using weighted gene co-expression network analysis (WGCNA), which is especially useful for the study of transcriptional signatures in disease. WGCNA networks are typically constructed using both disease and wildtype samples, so molecular pathways associated with disease are identified. However, it would be advantageous to study such co-expression networks in their disease context across spatiotemporal conditions, but currently there is no comprehensive software implementation for this type of analysis.

Results

SUBMITTER: Tommasini D 

PROVIDER: S-EPMC10039544 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature