DynaVenn

DynaVenn identifies statistically significant overlaps between two or three ordered gene or protein lists by generating dynamic Venn diagrams and computing p-values to avoid arbitrary thresholds.

Key Features:

• Ordered-list comparison: Compares two or three ranked gene or protein lists to detect overlapping elements.
• Dynamic Venn diagrams: Generates dynamic Venn diagrams that represent overlaps among subsets of the input lists.
• Incremental subset generation: Incrementally generates all possible subsets from the input lists for exhaustive comparison.
• Statistical scoring: Calculates a p-value for each potential overlap to quantify statistical significance.
• Backtracking algorithm: Uses backtracking algorithms to explore subset combinations and identify optimal overlaps.
• Avoids fixed-threshold bias: Eliminates reliance on fixed thresholds used by static Venn or Euler diagrams to reduce bias from varying cohort sizes or analytical differences.
• Animated progression: Provides animations that illustrate the progression toward identified optimal overlaps.

Scientific Applications:

• Genomics: Comparing ranked gene lists to identify statistically significant intersections.
• Proteomics: Comparing ranked protein lists to identify statistically significant intersections.
• Comparative studies across cohorts: Assessing overlaps across datasets with varying cohort sizes or analytical techniques where fixed thresholds are problematic.
• Alzheimer's Disease biomarker analysis: Applied to Alzheimer's Disease biomarker sets with reported improved detection of significant overlaps versus arbitrary cutoff methods.

Methodology:

Incrementally generates all possible subsets from the input lists, computes a p-value for each potential overlap, and uses a backtracking algorithm to dynamically generate Venn diagrams and identify the most statistically significant intersections.