Journal article
VCF2PopTree: a client-side software to construct population phylogeny from genome-wide SNPs
PeerJ, Vol.7, e8213
2019
Abstract
In the past decades a number of software programs have been developed to infer phylogenetic relationships between populations. However, most of these programs typically use alignments of sequences from genes to build phylogeny. Recently, many standalone or web applications have been developed to handle large-scale whole genome data, but they are either computationally intensive, dependent on third party software or required significant time and resource of a web server. In the post-genomic era, researchers are able to obtain bioinformatically processed high-quality publication-ready whole genome data for many individuals in a population from next generation sequencing companies due to the reduction in the cost of sequencing and analysis. Such genotype data is typically presented in the Variant Call Format (VCF) and there is no simple software available that directly uses this data format to construct the phylogeny of populations in a short time. To address this limitation, we have developed a user-friendly software, VCF2PopTree that uses genome-wide SNPs to construct and display phylogenetic trees in seconds to minutes. For example, it reads a VCF file containing 4 million SNPs and draws a tree in less than 30 seconds. VCF2PopTree accepts genotype data from a local machine, constructs a tree using UPGMA and Neighbour-Joining algorithms and displays it on a web-browser. It also produces pairwise-diversity matrix in MEGA and PHYLIP file formats as well as trees in the Newick format which could be directly used by other popular phylogenetic software programs. The software including the source code, a test VCF file and a documentation are available at: https://github.com/sansubs/vcf2pop.
Details
- Title
- VCF2PopTree: a client-side software to construct population phylogeny from genome-wide SNPs
- Authors
- Sankar Subramanian (Author) - University of the Sunshine CoastUmayal Ramasamy (Author) - University of the Sunshine CoastDavid Chen (Author) - Griffith University
- Publication details
- PeerJ, Vol.7, e8213; 10
- Publisher
- PeerJ, Ltd.
- Date published
- 2019
- DOI
- 10.7717/peerj.8213
- ISSN
- 2167-8359
- Copyright note
- Copyright © 2019 Subramanian et al. Distributed under Creative Commons CC-BY 4.0
- Organisation Unit
- School of Science and Engineering - Legacy; University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering; Centre for Bioinnovation
- Language
- English
- Record Identifier
- 99451409802621
- Output Type
- Journal article
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