Selection scans and downstream analysis with selscan

Area of Science:

• Evolutionary genomics
• Population genetics
• Bioinformatics

Background:

• Extended Haplotype Homozygosity (EHH) statistics are crucial for detecting positive selection in genomes.
• Existing methods lack clear guidelines on usage and interpretation, hindering reproducibility.
• The selscan software is widely used but requires better documentation and enhanced features.

Purpose of the Study:

• To provide a comprehensive guide to genomic selection statistics and their implementation in selscan.
• To introduce enhanced normalization and gene-based analysis capabilities in selscan v3.0.
• To improve the interpretation of selection signals and foster reproducibility in evolutionary genomics.

Main Methods:

• Detailed explanation of various EHH-based selection statistics.
• Implementation of enhanced normalization procedures for selection statistics.
• Development of gene-based analysis support using BED annotation files within selscan.
• Demonstration on simulated data and the 1000 Genomes Project dataset.

Main Results:

• A clear framework for understanding and applying selection statistics is presented.
• Enhanced normalization and gene-based analysis features in selscan v3.0 are introduced.
• Best practices for downstream analysis of selection signals are demonstrated.

Conclusions:

• The updated selscan software facilitates biologically meaningful interpretation of genomic selection signals.
• The guidelines and new features aim to enhance reproducibility in evolutionary genomics.
• selscan v3.0 provides powerful tools for analyzing positive selection in genomic data.