GO-Figure

GO-Figure generates semantic-similarity-based visualizations of Gene Ontology (GO) term enrichments in Python to summarize redundancy-reduced GO term lists for functional genomics analyses.

Key Features:

• Semantic similarity scatterplots: Generates scatterplots that position GO terms in a two-dimensional semantic space using information content and semantic similarity metrics.
• Adjustable grouping thresholds: Provides adjustable grouping thresholds to control how GO terms are grouped based on semantic similarity.
• Redundancy reduction: Performs redundancy reduction by selecting representative GO terms to simplify and summarize enrichment results.
• Graphical customization: Enables customization of plotting attributes for visual summaries.
• Multiple dataset comparisons: Supports comparison of GO term enrichments across multiple datasets.

Scientific Applications:

• Functional enrichment interpretation: Identifies overrepresented annotated functions within subsets of genes from large-scale assays.
• Comparative functional analysis: Compares functional profiles across multiple datasets to reveal similarities or differences.
• Hypothesis formulation and testing: Supports formulation and testing of biological hypotheses based on patterns of enriched GO terms.
• Biological and evolutionary insight: Contributes to discoveries about the biology or evolution of study systems by summarizing functional enrichments.
• Bias mitigation in interpretation: Provides visual summaries that clarify results and help mitigate interpretation biases.

Methodology:

Computes semantic similarity using information content and semantic similarity metrics, performs redundancy reduction to select representative GO terms, and plots representative terms in a two-dimensional semantic space with adjustable grouping thresholds.