qb.varcomp {qtlbim} | R Documentation |
These routines extract and summarize variance components for Bayesian multiple QTL. Variance components are averaged over genome loci. Covariates and GxE may be included.
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, ...)
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. |
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.
qb.varcomp
creates a matrix with columns of samples for the
variance components. Each row represents an MCMC iteration. Values are
averaged over loci.
Brian S. Yandell
http://www.qtlbim.org
data(qbExample) temp <- qb.varcomp(qbExample) summary(temp) plot(temp)