varlociraptor

varlociraptor implements a unifying statistical framework for sensitive and false discovery rate (FDR)-controlled discovery of somatic insertions and deletions (indels) from cancer genome sequencing data.

Key Features:

• Uncertainty-aware statistical model: Quantifies uncertainties arising from gap and alignment ambiguities, twilight zone indels, cancer heterogeneity, sample purity, sampling bias, and strand bias to enable principled variant assessment.
• Parameter-free FDR filtration: Applies a parameter-free filtration mechanism to control and minimize the false discovery rate (FDR) without fixed ad hoc thresholds.
• Post-processing integration: Functions as a post-processing step compatible with large-scale cancer genome sequencing workflows to refine candidate somatic indel calls.
• Improved discovery performance: Increases true discovery rates while suppressing false positives, as demonstrated on simulated and real sequencing data.

Scientific Applications:

• Population-scale cancer genome sequencing: Enables FDR-controlled somatic indel discovery across large cohorts to support cataloging of recurrent and rare variants.
• Cancer genomics and biomarker discovery: Supports accurate identification of somatic indels for studies of tumor biology and the development of targeted therapies.

Methodology:

Uses a unifying statistical model that explicitly quantifies alignment/gap uncertainties, twilight zone indels, heterogeneity, purity, sampling bias, and strand bias, combined with a parameter-free filtration strategy to control the false discovery rate; can be applied as a post-processing step in sequencing analysis pipelines.