multiSNV

multiSNV performs joint somatic single-nucleotide variant (SNV) calling from next-generation sequencing (NGS) data of matched normal and multiple tumor samples to improve detection of somatic mutations and characterize intratumor heterogeneity.

Key Features:

• Multisample analysis: Supports joint analysis of multiple same-patient tumor samples alongside a matched normal to capture mutations across regions or time points.
• Bayesian framework: Integrates data from all samples using a Bayesian statistical model to increase accuracy in calling shared SNVs.
• Increased sensitivity (down to 3% VAF): Leverages information across samples to detect low-frequency somatic variants with variant allele frequencies as low as 3%.

Scientific Applications:

• Intratumor heterogeneity analysis: Identifies region-specific somatic mutations across multiple tumor samples to study spatial heterogeneity.
• Low-frequency variant detection: Enhances discovery of rare somatic SNVs that may be missed in single-sample analyses.
• Germline versus somatic discrimination: Distinguishes germline polymorphisms from somatic mutations using matched normal and tumor data.
• Cancer evolution and targeted therapy profiling: Provides comprehensive mutational profiles to inform studies of cancer evolution, progression, and targeted therapy development.

Methodology:

Processes NGS data from matched normal and multiple tumor samples and applies a Bayesian statistical framework to jointly analyze these datasets and call somatic SNVs, enabling detection of shared and low-frequency variants.