Triodenovo

Triodenovo detects de novo mutations (DNMs) in parent-proband trios—comprising two parents and one offspring—from next-generation sequencing data using a Bayesian framework that separates prior mutation rates from data likelihood.

Key Features:

• Bayesian Framework: Employs a Bayesian approach that separates prior mutation rates from likelihood evaluation, enabling post-hoc adjustment of priors at different genomic sites.
• Improved Sensitivity and Specificity: Demonstrates superior sensitivity and specificity compared to existing methods based on extensive simulations and real-data applications.
• Flexible Prior Adjustment: Allows site-specific prior adjustments to accommodate variation in mutation rates across different genomic contexts.
• Effective Filtering Mechanism: Incorporates filtering based on sequence alignment characteristics to minimize false positives arising from sequencing errors and alignment artifacts.

Scientific Applications:

• Complex disease genetics: Identifying genes or genomic regions associated with complex diseases by analyzing sporadic cases and discovering novel de novo contributors to disease etiology.

Methodology:

Analyzes next-generation sequencing of parent–proband trios with a Bayesian DNM-calling framework, applies site-specific prior adjustments, and filters candidate variants using sequence alignment characteristics.