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Quantitative Genetics
Gota Morota edited this page Apr 27, 2017
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These R packages might be useful for quantitative genetics analyses.
- BGLR: Bayesian Generalized Linear Regression
- synbreed: Framework for the analysis of genomic prediction data using R
- rrBLUP: Ridge regression and other kernels for genomic selection
- rrBlupMethod6: Re-parametrization of RR-BLUP to allow for a fixed residual variance
- GeneticsPed: Pedigree and genetic relationship functions
- pedigree: Pedigree functions
- kinship2: Pedigree functions
- related: an R package for analyzing pairwise relatedness data based on codominant molecular markers (paper)
- GenABEL: genome-wide SNP association analysis
- MultiPhen: MultiPhen, a package for the genetic association testing of multiple phenotypes
- QCGWAS (paper)
- qqman: Q-Q and manhattan plots for GWAS data
- snpStats: SnpMatrix and XSnpMatrix classes and methods
- GWAtoolbox
- repfdr: Replicability Analysis for Multiple Studies of High Dimension (paper)
- lrgpr: Low Rank Gaussian Process Regression (paper)
- snpStats: SnpMatrix and XSnpMatrix classes and methods
- GWASTools
- FunciSNP
- SNPRelate (paper)
- trio
- SNPassoc
- BLueSNP (paper)
- postgwas
- hypred: Simulation of genomic data in applied genetics
- HaploSim: HaploSim
- PopGenome (paper)
- xbreed: Genomic Simulation of Purebred and Crossbred Populations
- PopGenome (paper)
- adegenet (adegenet on the web)
- pegas
- hierfstat: Estimation and tests of hierarchical F-statistics
- hsphase: Phasing, sire imputation, recombination events identification and pedigree reconstruction of half-sib families using SNP data (paper)