orsum

orsum filters enrichment analysis results by removing redundant annotation terms and selecting representative, more significant terms that cover the same gene sets to produce concise, interpretable annotation lists.

Key Features:

• Redundancy Reduction: Reduces redundancy in enrichment analysis results by filtering annotation terms to produce concise sets.
• Collective Filtering: Performs collective filtering across multiple enrichment result sets to identify common and dataset-specific annotation terms.
• Significance-Based Selection: Discards a term when a more significant term annotates at least the same genes and uses the more significant term as the representative.
• Tailored Outputs: Selects representative terms from original enrichment results to generate outputs tailored to the study context.

Scientific Applications:

• Neurodegenerative disease gene lists: Applied to enrichment analyses of gene lists associated with neurodegenerative diseases to produce comprehensible filtered results.

Methodology:

Filters terms by comparing annotation overlap and significance, discarding terms when another term with higher significance annotates at least the same genes and retaining the more significant term as the representative.