GeneSetCluster

GeneSetCluster clusters gene-sets by shared gene content to simplify interpretation of gene-set analysis (GSA) results across experiments and analytical tools.

Key Features:

• Clustering Based on Shared Genes: Clusters gene-sets from one or multiple experiments or tools by computing similarity based on overlapping gene content.
• Integration Across Multiple Data Types: Operates on gene-centric data from RNA sequencing and microarrays and supports interval-based analyses derived from DNA methylation and ChIP/ATAC-seq, and can aggregate gene-sets from tools such as Ingenuity and GSEA.
• Facilitation of Biological Insights: Reduces redundancy among gene-sets and highlights groups with similar definitions to focus interpretation on biologically relevant clusters.

Scientific Applications:

• Pathway and process identification: Identifies clusters of gene-sets that represent shared biological pathways and processes associated with traits or conditions.
• Cross-platform GSA synthesis: Facilitates integration and interpretation of GSA results from RNA-seq, microarray, DNA methylation, and ChIP/ATAC-seq studies.

Methodology:

Calculates a distance score quantifying overlap in gene content between gene-sets and uses that score to cluster gene-sets into groups with similar gene compositions.