PopSc: Computing Toolkit for Basic Statistics of Molecular Population Genetics Simultaneously Implemented in Web-Based Calculator, Python and R

Shi-Yi Chen; Feilong Deng; Ying Huang; Cao Li; Linhai Liu; Xianbo Jia; Song-Jia Lai

doi:10.1371/journal.pone.0165434

PopSc: Computing Toolkit for Basic Statistics of Molecular Population Genetics Simultaneously Implemented in Web-Based Calculator, Python and R

PLoS One. 2016 Oct 28;11(10):e0165434. doi: 10.1371/journal.pone.0165434. eCollection 2016.

Authors

Shi-Yi Chen¹, Feilong Deng¹, Ying Huang², Cao Li¹, Linhai Liu¹, Xianbo Jia¹, Song-Jia Lai¹

Affiliations

¹ Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, 611130, China.
² College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, 611130, China.

Abstract

Although various computer tools have been elaborately developed to calculate a series of statistics in molecular population genetics for both small- and large-scale DNA data, there is no efficient and easy-to-use toolkit available yet for exclusively focusing on the steps of mathematical calculation. Here, we present PopSc, a bioinformatic toolkit for calculating 45 basic statistics in molecular population genetics, which could be categorized into three classes, including (i) genetic diversity of DNA sequences, (ii) statistical tests for neutral evolution, and (iii) measures of genetic differentiation among populations. In contrast to the existing computer tools, PopSc was designed to directly accept the intermediate metadata, such as allele frequencies, rather than the raw DNA sequences or genotyping results. PopSc is first implemented as the web-based calculator with user-friendly interface, which greatly facilitates the teaching of population genetics in class and also promotes the convenient and straightforward calculation of statistics in research. Additionally, we also provide the Python library and R package of PopSc, which can be flexibly integrated into other advanced bioinformatic packages of population genetics analysis.

MeSH terms

Data Interpretation, Statistical*
Genetic Variation / genetics
Genetics, Population / methods*
Genetics, Population / statistics & numerical data
Humans
Internet
Molecular Biology / methods*
Molecular Biology / statistics & numerical data
Software

Grants and funding

SYC is grateful for the financial supports from Department of Science and Technology of Sichuan Province, China (“Three Districts Talent Program” and “Fumin Project") and National Natural Sciences Foundation of China (31172197). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.