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Preprint
VCF2PopTree: a one-click client-side software to construct population phylogeny from genome-wide SNPs
PeerJ Preprints, Vol.7, pp.1-12
PeerJ, Ltd.
2019
Abstract
In the past decades a number of software programs have been developed to deduce the phylogenetic relationship between populations. However, these programs are not suited for large-scale whole genome data. Recently, a few standalone or web applications have been developed to handle genome-wide data, but they were 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 highquality 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 uses this data to construct the phylogeny of populations in a short time. To address this limitation, we have developed a one-click user-friendly software, VCF2PopTree that uses gnome-wide SNPs to construct and display phylogenetic trees in seconds to minutes. For example, it reads a 1 GB VCF file and draws a tree in less than 5 minutes. 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 input file and short documentation are available at: http://sankarsubramanian.net/dat/index.html.
Details
- Title
- VCF2PopTree: a one-click 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 Preprints, Vol.7, pp.1-12
- Publisher
- PeerJ, Ltd.
- Date published
- 2019
- DOI
- 10.7287/peerj.preprints.27682v1
- ISSN
- 2167-9843; 2167-9843
- Copyright note
- Copyright © 2019 The Authors. CC BY 4.0 Open Access
- Organisation Unit
- School of Science and Engineering - Legacy; School of Science, Technology and Engineering; Centre for Bioinnovation
- Language
- English
- Record Identifier
- 99451465602621
- Output Type
- Preprint
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