SweepFinder

SweepFinder detects selective sweeps in genomic single nucleotide polymorphism (SNP) data, identifying regions of recent positive selection while accounting for complex ascertainment schemes and demographic influences.

Key Features:

• Robust Detection Methodology: Employs a parametric, composite likelihood-based test (Nielsen et al. 2005) with high power and robustness to varying recombination rates and demographic assumptions, reducing Type I error.
• Estimation Capabilities: Identifies genomic locations of candidate selective sweeps and estimates the magnitude of selection coefficients for those regions.
• Handling Ascertainment Bias: Accounts for SNP ascertainment bias inherent to SNP discovery processes to improve accuracy of sweep detection.
• Application to Real Data Sets: Has been applied to the Seattle SNP project and HapMap Chromosome 2 data, reporting a signal at the lactase gene and sweeps in regions containing DPP10 and COL4A3.

Scientific Applications:

• Evolutionary Biology: Maps regions under recent positive selection to study adaptive evolution.
• Medical Genetics: Identifies loci and candidate risk genes that may contribute to disease susceptibility.
• Population Genomics: Enables genome-wide scans for selective sweeps across populations while correcting for demographic effects and ascertainment bias.

Methodology:

Implements composite likelihood-based parametric tests (Nielsen et al. 2005) to scan SNP data for sweep signals, estimates sweep locations and selection coefficient magnitudes, and accounts for variation in recombination rates, demographic structure, ascertainment bias, and missing data.