Fast Principal Component Analysis for Outlier Detection

Methods to detect genetic markers involved in biological adaptation. 'pcadapt' provides statistical tools for outlier detection based on Principal Component Analysis. Implements the method described in (Luu, 2016) .


Build Status AppVeyor build status CRAN_Status_Badge Rdoc Coverage Status

pcadapt has been developed to detect genetic markers involved in biological adaptation. pcadapt provides statistical tools for outlier detection based on Principal Component Analysis (PCA).

To run the package, you can install it from CRAN:

install.packages("pcadapt")
library(pcadapt)

A tutorial for pcadapt is available. To access to the vignette, type the following command in your R console:

browseVignettes("pcadapt")

If you desire to install from GitHub, run the following commands:

install.packages("devtools")
devtools::install_github("bcm-uga/pcadapt")

Reference

[1] Luu, K., Bazin, E., & Blum, M. G. (2017). pcadapt: an R package to perform genome scans for selection based on principal component analysis. Molecular Ecology Resources, 17(1), 67-77.

[2] Duforet-Frebourg, N., Luu, K., Laval, G., Bazin, E., & Blum, M. G. (2015). Detecting genomic signatures of natural selection with principal component analysis: application to the 1000 Genomes data. Molecular biology and evolution, msv334.

News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("pcadapt")

4.0.3 by Michael Blum, 7 months ago


Browse source code at https://github.com/cran/pcadapt


Authors: Keurcien Luu [aut] , Michael Blum [aut, cre] , Florian Privé [aut] , Eric Bazin [ctb] , Nicolas Duforet-Frebourg [ctb]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports data.table, ggplot2, magrittr, mmapcharr, plotly, Rcpp, robust, RSpectra, vcfR

Suggests knitr, rmarkdown, testthat, shiny

Linking to Rcpp, BH, mmapcharr


See at CRAN