ExRec: a python pipeline for generating recombination-filtered multi-locus datasets

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Coalescent-based analyses in population genomics, phylogeography, and phylogenomics often assume no intralocus recombination.
• Filtering recombined DNA blocks is crucial for meeting this assumption and improving analytical accuracy.

Purpose of the Study:

• To introduce ExRec, a user-friendly, dependency-free Python pipeline for automated filtering of recombined DNA blocks.
• To provide a tool that enhances the quality of DNA sequence data for various population genetic studies.

Main Methods:

• Implementation of the four-gamete test to identify and exclude recombined DNA blocks.
• Development of a pipeline with five standalone applications, including file conversion and recombination filtering scripts.
• Inclusion of a novel feature allowing users to select either the longest nonrecombined blocks or randomly selected nonrecombined blocks from recombined loci.

Main Results:

• ExRec successfully filtered recombined DNA blocks from six diverse published phylogenomic datasets.
• Analysis of datasets ranging from 27 to 2237 loci was efficient, completing in seconds to under 30 minutes on a standard laptop.
• The pipeline outputs filtered data in multiple common formats and provides descriptive statistics.

Conclusions:

• ExRec is an effective and efficient tool for removing recombined DNA, thereby improving the quality of data for population genomic and phylogenomic research.
• The pipeline's user-friendly design, flexibility in handling recombined loci, and efficient performance make it a valuable resource for researchers.