SambaR: An R package for fast, easy and reproducible population‐genetic analyses of biallelic SNP data sets
| Autor: | Axel Janke, Joost F. de Jong, A. Rus Hoelzel, Menno J. de Jong |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
0106 biological sciences
0301 basic medicine Bayesian probability Population Biology Filter (higher-order function) computer.software_genre Polymorphism Single Nucleotide 010603 evolutionary biology 01 natural sciences SNP data 03 medical and health sciences Software Genetics SNP education Representation (mathematics) Alleles Ecology Evolution Behavior and Systematics Selection (genetic algorithm) education.field_of_study business.industry selection analyses R package population genetics Bayes Theorem genetic diversity population assignment test Data set Genetics Population 030104 developmental biology Wildlife Ecology and Conservation Data mining business gene flow computer Biotechnology |
| Zdroj: | Molecular Ecology Resources, 2021, Vol.21(4) [Peer Reviewed Journal] Molecular Ecology Resources 21 (2021) 4 Molecular Ecology Resources, 21(4), 1369-1379 |
| ISSN: | 1755-098X |
| DOI: | 10.1111/1755-0998.13339 |
| Popis: | SNP data sets can be used to infer a wealth of information about natural populations, including information about their structure, genetic diversity, and the presence of loci under selection. However, SNP data analysis can be a time-consuming and challenging process, not in the least because at present many different software packages are needed to execute and depict the wide variety of mainstream population-genetic analyses. Here, we present SambaR, an integrative and user-friendly R package which automates and simplifies quality control and population-genetic analyses of biallelic SNP data sets. SambaR allows users to perform mainstream population-genetic analyses and to generate a wide variety of ready to publish graphs with a minimum number of commands (less than 10). These wrapper commands call functions of existing packages (including adegenet, ape, LEA, poppr, pcadapt and StAMPP) as well as new tools uniquely implemented in SambaR. We tested SambaR on online available SNP data sets and found that SambaR can process data sets of over 100,000 SNPs and hundreds of individuals within hours, given sufficient computing power. Newly developed tools implemented in SambaR facilitate optimization of filter settings, objective interpretation of ordination analyses, enhance comparability of diversity estimates from reduced representation library SNP data sets, and generate reduced SNP panels and structure-like plots with Bayesian population assignment probabilities. SambaR facilitates rapid population genetic analyses on biallelic SNP data sets by removing three major time sinks: file handling, software learning, and data plotting. In addition, SambaR provides a convenient platform for SNP data storage and management, as well as several new utilities, including guidance in setting appropriate data filters. The SambaR source script, manual and example data set are distributed through GitHub: https://github.com/mennodejong1986/SambaR. |
| Databáze: | OpenAIRE |
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