Pool-hmm

Pool-hmm estimates allele frequencies and detects selective sweeps from pooled next-generation sequencing (Pool-Seq) data to infer selection and allele frequency dynamics within populations.

Key Features:

• Allele Frequency Estimation: Estimates allele frequencies from pooled NGS (Pool-Seq) data and analyzes the allele frequency spectrum to infer selection-related signals.
• Selective Sweep Detection: Identifies genomic regions undergoing selective sweeps by detecting deviations in allele frequency patterns indicative of positive selection.
• Flexible Analysis Options: Provides configurable analysis parameters to accommodate diverse Pool-Seq experimental designs and data characteristics.
• Parallel Processing Capability: Supports multi-processor execution to accelerate genome-wide analyses of large NGS datasets.

Scientific Applications:

• Evolutionary and Population Genetics: Analyzes allele frequency dynamics and selection processes in populations using pooled sequencing data.
• Selection Mapping and Adaptation Studies: Detects selective sweeps to identify genomic regions under positive selection with implications for disease resistance, adaptation, and biodiversity conservation.

Methodology:

Pool-hmm applies statistical models that interpret the allele frequency spectrum from pooled sequencing (Pool-Seq) data by comparing observed frequencies to neutral expectations to identify deviations indicative of selective pressures.