ArticleGenetics, selection, evolution : GSE2025
randPedPCA: rapid approximation of principal components from large pedigrees.
Article in Genetics, selection, evolution : GSE, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Fine-scale structure of a whole regional population through genetics and genealogies.Nature communications · 2026Article
- On ARGs, pedigrees, and genetic relatedness matrices.Genetics · 2026Article
- Quantitative genetic analysis of respiratory function and related traits in Bulldogs, French Bulldogs and Pugs.PloS one · 2026Article
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Authors and funding
4 authors.
Funding
Abstract
backgroundPedigrees continue to be extremely important in agriculture and conservation genetics, with the pedigrees of modern breeding programmes easily comprising millions of records. This size can make visualising the structure of such pedigrees challenging. Being graphs, pedigrees can be represented as matrices, including, most commonly, the additive (numerator) relationship matrix,
resultsWe present the open-access R package randPedPCA for rapid pedigree PCA using sparse matrices. Our rapid pedigree PCA builds on the fact that matrix-vector multiplications with the additive relationship matrix can be carried out implicitly using the extremely sparse inverse relationship factor,
conclusionsThe leading principal components of pedigree matrices can be efficiently obtained using randomised singular value decomposition and other methods. Scatter plots of these scores allow for intuitive visualisation of large pedigrees. For large pedigrees, this is considerably faster than rendering plots of a pedigree graph.
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