BestPattern: Proximity of common genetic architecture patterns.

In fboehm/qtlbim: QTL Bayesian Interval Mapping

Description

Multidimensional scaling and hierarchical clustering of most common patterns of genetic architecture.

Usage

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, ...)

Arguments

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.

Details

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.

Author(s)

Brian S. Yandell, [e-mail]

References

http://www.qtlbim.org

See Also

qb.close

Examples

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)

fboehm/qtlbim documentation built on Feb. 16, 2021, 12:04 a.m.