GScluster: network-weighted gene-set clustering analysis.

ABSTRACT:

Background

Gene-set analysis (GSA) has been commonly used to identify significantly altered pathways or functions from omics data. However, GSA often yields a long list of gene-sets, necessitating efficient post-processing for improved interpretation. Existing methods cluster the gene-sets based on the extent of their overlap to summarize the GSA results without considering interactions between gene-sets.

Results

Here, we presented a novel network-weighted gene-set clustering that incorporates both the gene-set overlap and protein-protein interaction (PPI) networks. Three examples were demonstrated for microarray gene expression, GWAS summary, and RNA-sequencing data to which different GSA methods were applied. These examples as well as a global analysis show that the propos

SUBMITTER: Yoon S 

PROVIDER: S-EPMC6507172 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature