FineMAV

FineMAV identifies positively selected genetic variants across human populations from whole-genome sequencing data to prioritize population-specific, high-frequency, functionally derived polymorphisms.

Key Features:

• High-Throughput Analysis: Performs high-throughput processing of large whole-genome sequencing datasets.
• Variant Prioritization: Prioritizes population-specific, high-frequency, and functionally derived variants indicative of positive selection.
• FineMAV Statistic Computation: Computes genome-wide FineMAV statistics to identify candidate variants under positive selection, applicable to low- and high-coverage whole-genome sequencing.
• Population-Scale Data Support: Operates on population-based genomic sequences, including datasets such as the 1000 Genomes Project.
• bigWig Output for Visualization: Exports statistics in the bigWig file format for visualization and annotation in genome browsers.

Scientific Applications:

• Population Genomics: Detects adaptive genetic variation and candidates of positive selection across human populations.
• Comparative Population Analysis: Enables comparison of genomic regions and FineMAV scores across populations (e.g., African, European, East Asian).
• Regional Dataset Analysis: Applies FineMAV scoring to regional datasets such as those from Singapore and China to identify localized adaptive variants.
• Annotation and Visualization: Facilitates annotation and visual comparison of candidate loci using bigWig outputs in genome browsers.

Methodology:

Calculates genome-wide FineMAV statistics from population-based whole-genome sequencing data (low- and high-coverage) and produces bigWig files for downstream visualization and annotation.