GOMCL

GOMCL clusters Gene Ontology (GO) terms derived from omics enrichment analyses to reduce redundancy and summarize functional themes based on overlapping gene membership.

Key Features:

• Redundancy Reduction: Reduces redundancy in GO term lists by clustering terms that share overlapping gene members to produce non-overlapping functional themes.
• Clustering Methodology: Applies the Markov Clustering (MCL) algorithm to identify clusters of GO terms based on gene-member overlap.
• Sub-Cluster Analysis: Provides GOMCL-sub to divide GO clusters into non-overlapping sub-clusters for additional refinement.
• Visualization Capabilities: Generates heatmaps, networks based on gene-member overlap or hierarchical relationships among GO terms, and tables detailing term depth and cluster information, with outputs importable into Cytoscape.
• Batch Processing: Processes multiple GO enrichment datasets in batch to summarize and cluster results across datasets.

Scientific Applications:

• Functional enrichment interpretation: Summarizes enriched GO terms into coherent clusters to aid interpretation of gene and pathway enrichment results.
• Omics data analysis: Clarifies main functional attributes within large gene sets in omics studies by reducing GO-term redundancy and highlighting distinct functional themes.

Methodology:

Uses the Markov Clustering (MCL) algorithm to cluster GO terms based on overlap of gene members; optionally applies GOMCL-sub to partition clusters into non-overlapping sub-clusters; produces heatmaps, overlap- or hierarchy-based networks, and tables of term depth and cluster assignments exportable to Cytoscape.