OncodriveFM

OncodriveFM identifies candidate cancer driver genes and pathways by detecting biases toward functionally impactful somatic mutations within genes or gene modules across tumor cohorts.

Key Features:

• Functional Mutation (FM) Bias Detection: OncodriveFM evaluates the accumulation of functionally impactful variants within genes or groups of genes to detect FM bias indicative of positive selection.
• Independence from Recurrence-Based Methods: The method prioritizes genes by functional impact rather than mutation recurrence, avoiding reliance on background mutation rate estimation and enabling detection of lowly recurrent drivers.

Scientific Applications:

• Identification of Cancer Driver Genes: It identifies both highly recurrent and lowly recurrent candidate cancer drivers by assessing the functional impact of somatic mutations instead of their frequency.
• Pathway Analysis: By detecting gene modules with significant FM bias, it highlights pathways that may be critical for tumorigenesis.

Methodology:

OncodriveFM is based on the hypothesis that a bias toward functionally impactful mutations within genes or gene groups indicates positive selection; it quantifies this FM bias as a metric and applies the measurement to datasets of tumor somatic variants to identify genes and modules with significant FM bias.