scanonevar | R Documentation |
Genome scan with a single QTL model for loci that can affect the variance as well as the mean.
scanonevar(cross, pheno.col=1, mean_covar=NULL, var_covar=NULL,
maxit=25, tol=1e-6, quiet=TRUE)
cross |
An object of class |
pheno.col |
Column number in the phenotype matrix which should be used as the phenotype. This must be a single value (integer index or phenotype name) or a numeric vector of phenotype values, 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. |
mean_covar |
Numeric matrix with covariates affecting the mean. |
var_covar |
Numeric matrix with covariates affecting the variances. |
maxit |
Maximum number of iterations in the algorithm to fit the model at a given position. |
tol |
Tolerance for convergence. |
quiet |
If |
A data frame (with class "scanone"
, in the form output by
scanone
), with four columns: chromosome, position, the -log P-value for
the mean effect, and the -log P-value for the effect on the variance.
The result is given class "scanone"
Lars Ronnegard and Karl Broman
Ronnegard, L. and Valdar W. (2011) Detecting major genetic loci controlling phenotypic variability in experimental crosses. Genetics 188:435-447
Ronnegard, L. and Valdar W. (2012) Recent developments in statistical methods for detecting genetic loci affecting phenotypic variability. BMC Genetics 13:63
scanone
,
summary.scanone
, calc.genoprob
,
summary.scanoneperm
data(fake.bc)
fake.bc <- calc.genoprob(fake.bc, step=2.5)
out <- scanonevar(fake.bc)
color <- c("slateblue", "violetred")
plot(out, lod=1:2, col=color, bandcol="gray80")
legend("topright", lwd=2, c("mean", "variance"), col=color)
# use format="allpeaks" to get summary for each of mean and variance
# also consider format="tabByCol" or format="tabByChr"
summary(out, format="allpeaks")
# with sex and age as covariates
covar <- fake.bc$pheno[,c("sex", "age")]
out.cov <- scanonevar(fake.bc, mean_covar=covar, var_covar=covar)
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