AmpliSolve

AmpliSolve detects single nucleotide variants (SNVs) in amplicon-based deep sequencing data by modeling position-, strand-, and nucleotide-specific sequencing noise and applying a Poisson statistical framework to enable accurate detection of low variant allele frequencies (VAFs), including around 1%, particularly for Ion AmpliSeq / Ion Torrent data.

Key Features:

• Position-Specific Error Estimation: Models position-specific, strand-specific, and nucleotide-specific background artifacts using a set of normal samples to separate true variants from sequencing errors.
• Poisson Model-Based Framework: Uses a Poisson statistical framework as the core approach for SNV detection.
• Low VAF Detection: Achieves sensitivity and precision sufficient to detect SNVs at variant allele frequencies as low as ~1% in deep sequencing data.
• Validation with Digital Droplet PCR: Performance has been validated on 96 circulating tumor DNA samples at clinically relevant genomic positions with comparisons to digital droplet PCR experiments.
• Applicability to Amplicon-Based Sequencing: Designed for amplicon-based libraries on the Ion Torrent platform, with potential adaptation to other sequencing platforms.

Scientific Applications:

• Translational Medicine: Identifies known and novel SNVs to support precise genetic profiling for personalized medicine.
• Disease Monitoring: Detects low-frequency variants in circulating tumor DNA to aid monitoring of disease progression and treatment response in oncology.
• Cancer Profiling: Accurately identifies SNVs in cancer-related genes to inform targeted therapy decisions and tumor genetics research.

Methodology:

Models position-, strand-, and nucleotide-specific background artifacts using normal samples and applies a Poisson statistical framework to distinguish true SNVs from sequencing noise.