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VCF2PopTree: a client-side software to construct population phylogeny from genome-wide SNPs
Sankar Subramanian1, Umayal Ramasamy1, David Chen2
1GeneCology Research Centre, The University of the Sunshine Coast, Sippy Downs, QLD, Australia.
Peerj
|December 12, 2019
Summary
VCF2PopTree is a new software that quickly builds phylogenetic trees from whole genome SNP data. It processes Variant Call Format (VCF) files efficiently, aiding population genetics research.
Area of Science:
- Population Genetics
- Bioinformatics
- Computational Biology
Background:
- Phylogenetic tree construction traditionally relies on gene sequences.
- Existing whole-genome data tools are often resource-intensive or require third-party software.
- High-quality, large-scale genomic data is now accessible for population studies.
Purpose of the Study:
- To develop a user-friendly software for rapid phylogenetic tree construction directly from Variant Call Format (VCF) data.
- To address the limitations of existing tools in handling large-scale whole genome datasets efficiently.
- To enable quick visualization and analysis of population structure using genome-wide SNPs.
Main Methods:
- Developed VCF2PopTree, a software utilizing genome-wide Single Nucleotide Polymorphisms (SNPs).
- Implemented UPGMA and Neighbour-Joining algorithms for tree construction.
- Designed to process VCF files locally and display trees in a web browser.
Main Results:
- VCF2PopTree constructs phylogenetic trees in seconds to minutes, even for large datasets (e.g., 4 million SNPs in <30 seconds).
- The software accepts genotype data from local machines, offering a convenient workflow.
- Outputs include pairwise diversity matrices (MEGA, PHYLIP) and trees in Newick format for compatibility with other phylogenetic software.
Conclusions:
- VCF2PopTree provides a fast and efficient solution for constructing population phylogenies directly from VCF files.
- The software democratizes phylogenetic analysis by simplifying the use of large-scale genomic data.
- It facilitates rapid exploration of population structure and evolutionary relationships.
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