GWideCodeML: A Python Package for Testing Evolutionary Hypotheses at the Genome-Wide Level

Area of Science:

• Molecular Evolution
• Bioinformatics
• Computational Biology

Background:

• The codeml program in PAML is widely used for detecting molecular positive selection.
• Current methods are limited to gene-by-gene analysis, restricting genome-wide studies.
• Existing approaches often require one-to-one orthologs, limiting the scope of analysis.

Purpose of the Study:

• To develop a scalable solution for genome-wide positive selection detection.
• To overcome the limitations of the gene-by-gene approach of codeml.
• To enhance the analysis of molecular evolution across diverse genomic datasets.

Main Methods:

• Introduction of GWideCodeML, a novel Python package.
• Implementation of parallelized genome-wide codeml analysis.
• Automated pruning of phylogenetic topologies to fit alignments with variable taxa.

Main Results:

• GWideCodeML facilitates efficient genome-wide detection of positive selection.
• The package maximizes the number of analyzed genes by handling variable taxa.
• Automated topology pruning ensures compatibility with diverse genomic alignments.

Conclusions:

• GWideCodeML significantly advances genome-wide evolutionary analyses.
• The package overcomes previous limitations in scale and scope for positive selection studies.
• This tool enables more comprehensive molecular evolution research.