BCM - Computational and Mathematical Biology
pcadapt implements a genome scan for detecting genes involved in local adaptation. The software is available as the R pcadapt package. If you have questions or detect bugs, please open an issue on github.
A brief history of pcadapt
The first version was based on a hierarchical Bayesian factor model (Duforet-Frebourg et al. 2014). The second and much more rapid version used Principal Component Analysis and the communality statistic to look for candidate SNPs (Duforet-Frebourg et al. 2016). The current version uses Principal Component Analysis and the Mahalanobis distance, which provides a better ranking of candidate SNPs than the communality statistic especially when there is hierarchical structure (Luu, Bazin and Blum, 2017).
Luu K, E Bazin, MGB Blum. pcadapt: an R package to perform genome scans for selection based on principal component analysis. Molecular Ecology Resources 1:67-77 (2017)
Duforet-Frebourg N, K Luu, G Laval, E Bazin, MGB Blum. Detecting genomic signatures of natural selection with principal component analysis: application to the 1000 Genomes data. Molecular Biology and Evolution 33:1082-1093 (2016)
Duforet-Frebourg N, E Bazin, MGB Blum. Genome scans for detecting footprints of local adaptation using a Bayesian factor model. Molecular Biology and Evolution, 31:2483-2495 (2014)
Michael BLUM <michael_dot_blum_at_univ-grenoble-alpes_dot_fr>