varcomp: Variance components for Bayesian multiple QTL

In byandell/qtlbim: QTL Bayesian Interval Mapping

Description

These routines extract and summarize variance components for Bayesian multiple QTL. Variance components are averaged over genome loci. Covariates and GxE may be included.

Usage

qb.varcomp(qbObject, scan, aggregate = TRUE, ...)
## S3 method for class 'qb.varcomp'
summary(object, ...)
## S3 method for class 'qb.varcomp'
print(x, ...)
## S3 method for class 'qb.varcomp'
plot(x, log = TRUE, percent = 5, cex, ...)

Arguments

qbObject	Object of class qb.
object	Object of class qb.varcomp.
x	Object of class qb.varcomp.
scan	Aggregated terms to include in created object (see below).
aggregate	Sum over individual components of aggregated terms if TRUE.
log	Use log10 of variances in plot if TRUE.
percent	Percentile between 0 and 100 for summaries.
cex	Character expansion for plot symbols. Default shrinks with number of MCMC iterations.
...	Arguments to pass along.

Details

Variance components are organized as "main" ("add" and "dom"), "epistasis" ("aa", etc.), "fixcov" (for all fixed covariate terms), "rancov" (random covariates), and "GxE" (genotype by environment, including additive and dominance terms). Any subset of these may be chosen.

Value

qb.varcomp creates a matrix with columns of samples for the variance components. Each row represents an MCMC iteration. Values are averaged over loci.

Author(s)

Brian S. Yandell

References

http://www.qtlbim.org

See Also

qb.mcmc

Examples

data(qbExample)

temp <- qb.varcomp(qbExample)
summary(temp)
plot(temp)

byandell/qtlbim documentation built on Dec. 19, 2021, 12:47 p.m.