mqmplotclusteredheatmap: Plot clustered heatmap of MQM scan on multiple phenotypes

In byandell/qtl: Tools for analyzing QTL experiments

Description

Plot the results from a MQM scan on multiple phenotypes.

Usage

mqmplot.clusteredheatmap(cross, mqmresult, directed=TRUE, legend=FALSE, Colv=NA, scale="none", verbose=FALSE, breaks = c(-100,-10,-3,0,3,10,100), col = c("darkblue","blue","lightblue","yellow","orange","red"), ...)

Arguments

cross	An object of class cross. See read.cross for details.
mqmresult	Result object from mqmscanall, the object needs to be of class mqmmulti
directed	Take direction of QTLs into account (takes more time because of QTL direction calculations
legend	If TRUE, add a legend to the plot
Colv	Cluster only the Rows, the columns (Markers) should not be clustered
scale	character indicating if the values should be centered and scaled in either the row direction or the column direction, or none. The default "none"
verbose	If TRUE, give verbose output.
breaks	Color break points for the LOD scores
col	Colors used between breaks
...	Additional arguments passed to heatmap.

Author(s)

Danny Arends [e-mail]

See Also

• The MQM tutorial: http://www.rqtl.org/tutorials/MQM-tour.pdf

• MQM - MQM description and references

• mqmscan - Main MQM single trait analysis

• mqmscanall - Parallellized traits analysis

• mqmaugment - Augmentation routine for estimating missing data

• mqmautocofactors - Set cofactors using marker density

• mqmsetcofactors - Set cofactors at fixed locations

• mqmpermutation - Estimate significance levels

• scanone - Single QTL scanning

Examples

data(multitrait)

multitrait <- fill.geno(multitrait) # impute missing genotype data
result <- mqmscanall(multitrait, logtransform=TRUE)
cresults <- mqmplot.clusteredheatmap(multitrait,result)
groupclusteredheatmap(multitrait,cresults,10)

byandell/qtl documentation built on May 13, 2019, 9:28 a.m.