| NOIA package {noia} | R Documentation |
The NOIA model, as described extensively in Alvarez-Castro & Carlborg (2007) Genetics 176: 1151-1167, is a framework facilitating the estimation of geneticEffects and genotype-to-phenotype maps. This package provides the basic tools to perform linear and multilinearRegressions from real populations (provided the phenotype and the genotype of every individuals), estimating the geneticEffects from different reference points, the genotypic values, and the decomposition of genetic variances in a multi-locus, 2 alleles system
| Package: | noia |
| Type: | Package |
| Version: | 0.91 |
| Date: | 2008-04-25 |
| License: | GPL v 2 |
linearRegressionlinearRegression and
multilinearRegressiongeneticEffectsGPmapvarianceDecompositionArnaud Le Rouzic
Maintainer: Arnaud Le Rouzic <a.p.s.lerouzic@bio.uio.no>
Alvarez-Castro JM, Carlborg O. (2007). A unified model for functional and statistical epistasis and its application in quantitative trait loci analysis. Genetics 176(2):1151-1167.
Alvarez-Castro JM, Le Rouzic A, Carlborg O. (2008). How to perform meaningful estimates of genetic effects. PLoS Genetics, in press.
Le Rouzic A, Alvarez-Castro JM. (2008). Estimation of genetic effects and genotype-phenotype maps. Evolutionary Bioinformatics, in press.
set.seed(123456789)
map <- c(0.25, -0.75, -0.75, -0.75, 2.25, 2.25, -0.75, 2.25, 2.25)
names(map) <- genNames(2)
pop <- simulatePop(map, N=500, sigmaE=0.2, type="F2")
# Regressions
linear <- linearRegression(phen=pop$phen, gen=pop[2:3])
multilinear <- multilinearRegression(phen=pop$phen, gen=cbind(pop$Loc1,
pop$Loc2))
# Linear effects, associated variances and stderr
linear
# Multilinear effects
multilinear
# Change of reference: geneticEffects in the "11" genotype (parental 1)
geneticEffects(linear, ref.genotype="P1")
# Variance decomposition
varianceDecomposition(linear)
# GP maps
maps <- cbind(map, GPmap(linear)[,1], GPmap(multilinear)[,1])
colnames(maps) <- c("Actual", "Linear", "Multilinear")
maps