fitqtlShape: fitqtlShape
In nnavarro/shapeQTL: shape QTL mapping experiment using R

Description Usage Arguments Details Value Author(s) Examples

View source: R/qtleffect_shape.R

Estimates qtl effect

1 2	fitqtlShape(cross, pheno.col, qtl, covar = NULL, formula, method = "hk", forceXcovar = FALSE, pca = NULL)

`cross`	A cross object containing genotypes and some phenotypes
`pheno.col`	A numerical vector with column indicies in cross$pheno of the phenotypes to map or a vector containing their names.
`qtl`	An
`covar`	An optional data.frame of covariates
`formula`	A formula ccc
`method`	Indicates whether to use multiple imputation or Haley-Knott regression. Only 'hk' is tested so far.
`forceXcovar`	Not use so far. Keep it default.
`pca`	An optional prcomp object from `prcomp` function use to get PC scores or just the corresponding eigenvector matrix. Use to return the effect in their original coordinates (PCscores back to tgCoords)

Function takes a cross object

Function returns qtl effects

Nicolas Navarro

data(fake.bc)
fake.bc <- update.cross(fake.bc, phen2keep=colnames(fake.bc$pheno))
fake.bc <- calc.genoprob(fake.bc)
qtl <- makeqtl(fake.bc, chr = c(1, 8, 13), pos=c(26, 56, 28), what="prob")
eff <- fitqtlShape(fake.bc, pheno.col=grep('pheno',colnames(fake.bc$pheno)), qtl)
# Using PC scores
pca <- prcomp(fake.bc$pheno[,c('pheno1','pheno2')])
PCs <- data.frame(Id=1:nrow(pca$x), pca$x)
fake.bc <- update(fake.bc, new.pheno=PCs)
eff <- fitqtlShape(fake.bc, pheno.col=grep("PC",colnames(fake.bc$pheno)), qtl, pca=pca)