WinPCA: A package for windowed principal component analysis
Year: 2025
Type: article
Abstract: With chromosomal reference genomes and population-scale whole genome-sequencing becoming increasingly accessible, contemporary studies often include characterizations of the genomic landscape as it varies along chromosomes, commonly termed genome scans. While traditional summary statistics like F ST and d XY between pre-assigned populations remain integral to characterizing the genomic divergence profile, PCA differs by providing single-sample resolution, thereby supporting the identification of polymorphic inversions, introgression and other types of divergent sequence that may not be fully aligned with global population structure. Here, we introduce WinPCA, a user-friendly package to compute, polarize and visualize genetic principal components in windows along the genome. To accommodate low-coverage whole genome-sequencing datasets, WinPCA can optionally make use of PCAngsd methods to compute principal components in a genotype likelihood framework. WinPCA accepts variant data in either VCF or BEAGLE format and can generate rich plots for interactive data exploration and downstream presentation.
Source: Apollo (University of Cambridge)
DOI: 10.17863/cam.121823
Authors: Blumer, Moritz, Durbin, Richard, Good, Jeffrey M
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7084584395
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