AGHmatrix: genetic relationship matrices in R.

Bioinformatics

Blueberry, Breeding and Genomics Lab, Horticultural Sciences Department, University of Florida, Gainesville, FL 32611, United States.

Published: July 2023

AI Article Synopsis

  • The resemblance between relatives using pedigree and genomic data aids geneticists and ecologists in exploring gene influence on traits, fitness, and population dynamics.
  • AGHmatrix is an R package that constructs pedigree and molecular marker matrices, capable of combining them to correct for molecular influences, and it includes tools for filtering data and checking for pedigree errors.
  • The software is freely available under GPL-3 license on CRAN and GitHub, complete with a tutorial and real data examples for user guidance.

Article Abstract

Motivation: The resemble between relatives computed from pedigree and genomic data is an important resource for geneticists and ecologists, who are interested in understanding how genes influence phenotypic variation, fitness adaptation, and population dynamics.

Results: The AGHmatrix software is an R package focused on the construction of pedigree (A matrix) and/or molecular markers (G matrix), with the possibility of building a combined matrix of pedigree corrected by molecular markers (H matrix). Designed to estimate the relationships for any ploidy level, the software also includes auxiliary functions related to filtering molecular markers, and checks pedigree errors in large data sets. After computing the relationship matrices, results from the AGHmatrix can be used in different contexts, including on prediction of (genomic) estimated breeding values and genome-wide association studies.

Availability And Implementation: AGHmatrix v2.1.0 is available under GPL-3 license in CRAN at https://cran.r-project.org/web/packages/AGHmatrix/index.html and also in GitHub at https://github.com/rramadeu/AGHmatrix. It has a comprehensive tutorial, and it follows with real data examples.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10371492PMC
http://dx.doi.org/10.1093/bioinformatics/btad445DOI Listing

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