McSNP

McSNP identifies genotypes from Tm-shifted melting curve SNP assays by differentiating alleles based on melting temperature differences for clinical and research genotyping.

Key Features:

• Homogeneous genotyping assays: Uses Tm-shifted melting curve SNP assays that produce signal peaks near theoretical allele-specific melting temperatures to enable allele differentiation.
• Supervised base-calling algorithm: Implements a supervised base-calling algorithm for per-sample genotype assignment to improve calling reliability.
• Peak detection and ordinal regression model: Employs a peak detection procedure and an ordinal regression model that leverages the ordinal pattern of signal intensities (AA, AB, BB) with trained model coefficients for base calling.
• Accuracy and validation: Demonstrated on 12 SNPs from 44 unrelated individuals with a 99.6% call rate, 99.1% concordance with sequencing, and 0.4% signals reported as no-call.

Scientific Applications:

• Clinical genetic testing: Genotyping individual clinical samples using Tm-shifted melting curve SNP assays for diagnostic purposes.
• Diagnostic workflows: Integration of melting curve SNP assay-based genotype calling into diagnostic genotyping pipelines.
• Genetic research and personalized medicine: Support for studies of genetic variation and applications in personalized medicine that require reliable SNP genotyping.

Methodology:

Computational steps include peak detection on Tm-shifted melting curves, extraction of signal intensities near allele-specific melting temperatures, and supervised base calling via an ordinal regression model with trained coefficients.