| addqtl {qtl} | R Documentation |
Scan for an additional QTL in the context of a multiple QTL model.
addqtl(cross, chr, pheno.col=1, qtl, covar=NULL, formula,
method=c("imp","hk"), incl.markers=TRUE, verbose=FALSE)
cross |
An object of class cross. See
read.cross for details. |
chr |
Optional vector indicating the chromosomes to be scanned. If
missing, all chromosomes are scanned. Refer to chromosomes by
name. Refer to chromosomes with a preceding - to have all
chromosomes but those considered. A logical (TRUE/FALSE) vector may
also be used. |
pheno.col |
Column number in the phenotype matrix to be used as the phenotype. One may also give a character string matching a phenotype name. Finally, one may give a numeric vector of phenotypes, in which case it must have the length equal to the number of individuals in the cross, and there must be either non-integers or values < 1 or > no. phenotypes; this last case may be useful for studying transformations. |
qtl |
An object of class qtl, as output from
makeqtl. |
covar |
A matrix or data.frame of covariates. These must be strictly numeric. |
formula |
An object of class formula
indicating the model to be fitted. (It can also be the character
string representation of a formula.) QTLs are referred to as
Q1, Q2, etc. Covariates are referred to by their names
in the data frame covar. If the new QTL is not included in
the formula, its main effect is added. |
method |
Indicates whether to use multiple imputation or Haley-Knott regression. |
incl.markers |
If FALSE, do calculations only at points on an
evenly spaced grid. If calc.genoprob or
sim.geno were run with
stepwidth="variable", we force incl.markers=TRUE. |
verbose |
If TRUE, display information about the progress of
calculations. If verbose is an integer > 1, further messages
from scanqtl are also displayed. |
The formula is used to specified the model to be fit. In the
formula, use Q1, Q2, etc., or q1,
q2, etc., to represent the QTLs, and the column names in the
covariate data frame to represent the covariates.
We enforce a hierarchical structure on the model formula: if a QTL or covariate is in involved in an interaction, its main effect must also be included.
If one wishes to scan for QTL that interact with another QTL, include
it in the formula (with an index of one more than the number of QTL in
the input qtl object).
An object of class scanone, as produced by the
scanone function. LOD scores are relative to the
base model (with any terms that include the new QTL omitted).
Karl W Broman, kbroman@biostat.wisc.edu
Haley, C. S. and Knott, S. A. (1992) A simple regression method for mapping quantitative trait loci in line crosses using flanking markers. Heredity 69, 315–324.
Sen, 'S. and Churchill, G. A. (2001) A statistical framework for quantitative trait mapping. Genetics 159, 371–387.
scanone, fitqtl,
scanqtl, refineqtl,
makeqtl, addtoqtl,
addpair, addint
data(fake.f2) # take out several QTLs and make QTL object qc <- c(1, 8, 13) qp <- c(26, 56, 28) fake.f2 <- subset(fake.f2, chr=c(1,2,3,8,13)) fake.f2 <- calc.genoprob(fake.f2, step=2, err=0.001) qtl <- makeqtl(fake.f2, qc, qp, what="prob") # scan for an additional QTL out1 <- addqtl(fake.f2, qtl=qtl, formula=y~Q1+Q2+Q3, method="hk") max(out1) # scan for an additional QTL that interacts with the locus on chr 1 out2 <- addqtl(fake.f2, qtl=qtl, formula=y~Q1*Q4+Q2+Q3, method="hk") max(out2) # plot interaction LOD scores plot(out2-out1)