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

Description Usage Arguments Details Value Author(s) See Also Examples

View source: R/scanone_shape.R

Runs genome scan on multivariate phenotypes with possible covariates

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scanoneShape(cross, chr, pheno.col, addcovar = NULL, intcovar = NULL,
  n.perm, perm.Xsp = FALSE, perm.strata = NULL, n.cluster = 1,
  test = c("Pillai", "Hotelling.Lawley", "Lik.ratio", "GoodallF"), formula)

`cross`	A cross object containing genotypes and some phenotypes
`chr`	(Optional) Names of chromosomes use for mapping
`pheno.col`	A numerical vector with column indicies in cross$pheno of the phenotypes to map or a vector containing their names. If missing, All but \"ID\" columns will be chosen as phenotypes.
`addcovar`	A dataframe with the additive covariates
`intcovar`	A dataframe with the interactive covariates - KEEP IT DEFAULT This argument and the followings except if state otherwise are not use so far They are there for direct
`n.perm`	Number of permutations
`perm.Xsp`	- KEEP IT DEFAULT, not use so far
`perm.strata`	- KEEP IT DEFAULT, not use so far
`n.cluster`	Number of clusters for parallelization of permutations
`test`	Multivariate test statistics: \'Pillai\', 'Hotelling.Lawley', \"Lik.ratio\", \"GoodallF\". Allows partial matching.
`formula`	Provides formula for the null model. Optional.

Function takes a modified cross object with an additional class shape obtained from update.cross. Additional covariates may be provided as supplementary arguments. Ordering of observations in those additional covariates must match the new phenotypes.

Function returns a data.frame similar to the R/qtl scanone function with chromosome and cM positions in the two firsts columns and the $log_10$ of the p-value for the multivariate phenotype. In the case of f2, there are three columns: full, purely additive and dominance models.

Nicolas Navarro

scanone

data(fake.bc)
fake.bc <- calc.genoprob(fake.bc, step=2.5)
out <- scanoneShape(fake.bc, chr = 1, pheno.col = 1:2, addcovar = getsex(cross)$sex,
test = "Pillai")
plot(out)
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Permutations
perm.scan <- scanoneShape(fake.bc, pheno.col=1:2, addcovar = getsex(cross)$sex, n.perm=1000, n.cluster=2)