binoSNP

binoSNP detects low-frequency resistance‑mediating single nucleotide polymorphisms (SNPs) in Mycobacterium tuberculosis complex (MTBC) from reference-mapped next-generation sequencing (NGS) data to support genotypic drug-resistance profiling.

Key Features:

• Low-frequency variant detection: Identifies resistance-mediating SNPs across MTBC genomes at allele frequencies validated from 1% to 30% in NGS datasets.
• Per-position statistical evaluation: Evaluates each genomic position of interest to assess the presence and frequency of SNPs.
• Binomial test procedure: Applies a binomial test at each assessed position using a reference-mapped file as input.
• Input data: Operates on reference-mapped NGS files for position-wise SNP frequency assessment.
• Validation and coverage range: Validated with in-silico simulations, in-vitro experiments, and serial patient isolates across coverage depths of 100–500× and SNP allele frequencies of 1–30%.
• Detection limits: Demonstrates detection of resistance-associated SNPs at 1% frequency with minimum coverage depth ≥400×.

Scientific Applications:

• Genotypic resistance profiling: Enables sensitive detection of resistance-associated SNPs for genotypic characterization of MTBC isolates from NGS data.
• Heteroresistance analysis: Detects low-frequency resistant subpopulations within mixed MTBC infections to inform interpretations of heteroresistance.
• Research on drug-resistance dynamics: Supports studies that quantify allele-frequency dynamics across serial patient isolates and experimental datasets.

Methodology:

Applies a binomial test to reference-mapped NGS data at each genomic position to assess SNP presence and estimate allele frequency.