| qb.BestPattern {qtlbim} | R Documentation |
Multidimensional scaling and hierarchical clustering of most common patterns of genetic architecture.
qb.best(...)
qb.BestPattern(qbObject, epistasis = TRUE,
category = c("pattern", "nqtl"), cutoff, score.type =
c("sq.atten","attenuation","variance","recombination","distance"),
include = c("nested","all","exact"),
center = c("median","mean"), level = 5, ...)
## S3 method for class 'qb.BestPattern':
plot(x, type = c("mds", "hclust"),
main, xlab, method = "complete", cluster = 3, cexmax = 5,
colmax = 75, cex, col,
symbol = c("pattern","nqtl","cluster","c@n","c@p","n@p","c@n@p"), ...)
## S3 method for class 'qb.BestPattern':
summary(object, method = "complete",
cluster = 3, n.best = 1, ...)
qbObject |
Object of class qb. |
x,object |
Object of class qb.BestPattern. |
epistasis |
Include epistasis in patterns if TRUE. |
category |
Distances indexed by nqtl or pattern. |
cutoff |
Percent cutoff for pattern inclusion in model
selection. Default is 0.25 (0.5) if epistasis is TRUE
(FALSE). |
score.type |
Type of score to use as distance. See
qb.close. |
type |
Plot dendrogram for hclust or 2-D multidimensional
scaling projection for mds. |
main |
Main plot title as character string. |
xlab |
Character string for horizontal (x) axis. |
method |
Method for hierarchical clustering. |
cluster |
Number of clusters desired. |
n.best |
Number of better models to display. |
cexmax |
Maximum font size (minimum is set to 1); patterns are
displayed in mds plot proportional to their posterior
probability. |
colmax |
Maximum number of colors. |
cex |
Manual override of font size for mds plot; should be
length 1 or the number of patterns exceeding cutoff. |
col |
Colors for plotting. |
symbol |
Plot symbol for mds plot. Shorthand using at sign
@ signifies catenation of two or more symbols into one. |
include |
Action for model averaging of chromosome-specific locus
and explained variance:
use all MCMC samples that match the chromosome;
use only MCMC samples for patterns that have the target pattern
nested within them;
or use only MCMC samples with the exact same target pattern. |
center |
Method of estimating the center for locus and
explained variance. |
level |
Confidence level as percent between 0 and 100 for loci and variance contributions. |
... |
Parameters to methods. |
This uses the closeness measure from qb.close to
compute a similarity matrix among patterns whose posterior probabilities
exceed cutoff. Distance = 1 - similarity is used for hierarchical
clustering or multidimensional scaling.
The best pattern is chosen as the one with highest posterior
mean; all other patterns are compared to that pattern in terms of the
score.type. This best pattern is a natural target for qb.close.
Brian S. Yandell, yandell@stat.wisc.edu
data(qbExample) temp <- qb.BestPattern(qbExample) summary(temp, n.best = 3) plot(temp, type = "hclust") plot(temp) plot(temp, symbol = "c@n") best <- summary(temp)$best temp <- qb.close(qbExample, best) summary(temp) plot(temp)