Population Assignment using Genetic, Non-Genetic or Integrated Data in a Machine-learning Framework
This R package helps perform population assignment and infer population structure using a machine-learning framework. It employs supervised machine-learning methods to evaluate the discriminatory power of your data collected from source populations, and is able to analyze large genetic, non-genetic, or integrated (genetic plus non-genetic) data sets. This framework is designed for solving the upward bias issue discussed in previous studies. Main features are listed as follows.
You can install the released version from CRAN or the up-to-date version from this Github respository.
install.packages("assignPOP") in your R console
step 3. Then enter
Note: When you install the package from Github, you may need to install additional packages before the assignPOP can be successfully installed. Follow the hints that R provided and then re-run
Please visit our tutorial website for more infomration * http://alexkychen.github.io/assignPOP/
Changes in ver. 1.1.4 - 2018.3.8 Fix missing assign.matrix function
Changes in ver. 1.1.3 - 2017.6.15 Add unit tests (using package testthat)
Changes in ver. 1.1.2 - 2017.5.13 Change function name read.genpop to read.Genepop; Add function read.Structure. - 2017.5.2 Update read.genpop function, now can read haploid data
Chen K-Y, Marschall EA, Sovic MG, Fries AC, Gibbs HL, Ludsin SA. assignPOP: An R package for population assignment using genetic, non-genetic, or integrated data in a machine-learning framework. Methods in Ecology and Evolution. 2018;9:439–446. https://doi.org/10.1111/2041-210X.12897
Previous packages can be found and downloaded at archive branch