pmscan {twopartqtl}R Documentation

Interval mapping with covariates for point-mass mixtures

Description

Conducts interval mapping with covariates for experimental crosses for which the phenotype has a point-mass mixture distribution. Identifies QTLs by testing the joint null hypothesis of no differences in the proportion of observations in the point-mass and no difference the means of the non-point mass observations.

Usage

pmscan(cross, chr, pheno.col = 1, pm.value = 0, maxit = 4000, tol = 1e-04, 
       addcovar, verbose = FALSE, imp.method = c("imp", "argmax"), 
       error.prob = 1e-04, map.function = c("haldane", "kosambi", "c-v", 
       "morgan"), n.perm, use.log = FALSE)

Arguments

cross An object of class cross. See read.cross for details.
chr Optional vector indicating the chromosomes for which LOD scores should be calculated.
pheno.col Column number in the phenotype matrix which should be used as the phenotype
pm.value Value of the point-mass observations
maxit Maximum number of iterations
tol Tolerance value for determining convergence
addcovar A matrix of additive covariates with dimensions n X number of covariates
verbose In the case n.perm is specified, displays information about the progress of the permutation tests.
imp.method Method used to impute any missing marker genotype data. See fill.geno for details.
error.prob Genotyping error probability assumed when imputing the missing marker genotype data.
map.function Map function used when imputing the missing marker genotype data.
n.perm If specified, a permutation test is performed rather than an analysis of the observed data. This argument defines the number of permutation replicates.
use.log If TRUE phenotype values not in the point-mass are log transformed.

Details

The multipoint genotype probabilities are first calculated using calc.genoprob.

The method is currently implemented only for experimental crosses consisting of two genotypes (e.g., backcross, recombinant inbred lines).

Only autosomal chromosomes are evaluated.

Individuals with any missing phenotypes or covariates are dropped.

Only additive covariates are modeled. Covariates must be numeric matrices.

Value

The function returns an object of the same form as the function scanone.
If n.perm is missing, the function returns the scan results as a data.frame with three columns: chromosome, position, LOD score. Attributes indicate the names and positions of the chosen marker covariates.
If n.perm > 0, the function results the results of a permutation test: a vector giving the genome-wide maximum LOD score in each of the permutations.

Author(s)

Sandra L. Taylor, sltaylor@ucdavis.edu

References

Taylor, S.L. and K.S. Pollard 20XX. Composite interval mapping to identify quantitative trait loci for point-mass mixture phenotypes. Genetics Research, XX, xxx–xxx

See Also

scanone

Examples


# Simulate backcross experiment
Map <- sim.map(c(100,100), n.mar=c(22), include.x=FALSE, eq.spacing=TRUE)
num.ind <- 200
QTL.info <- rbind(c(1,30,0.6,-0.02))
sim <- sim.cross.exp(map=Map, model=QTL.info, n.ind=num.ind, type="bc",
    keep.qtlgeno=TRUE, map.function="haldane", dist="pointmass", params=c(0.5,6,0.6))
sim <- calc.genoprob(sim, step=1)
Covs <- matrix(rnorm(400), nrow=200)

out <- pmscan(sim, chr=c(1:2), pheno.col=1, pm.value=0, addcovar=Covs)

# Permutation tests
## Not run: out.perm <- pmscan(sim, chr=c(1:2), pheno.col=1, pm.value=0, addcovar=Covs, n.perm=1000)

[Package twopartqtl version 1.0 Index]