image.scanone: Heatmap of scanone object
In atbroman/neqtl: Tools for analyzing expression QTL by position on genome

Description Usage Arguments Details Author(s) See Also Examples

Heatmap of scanone object; useful for a subset of expression traits (<100).

1	image.scanone(x,chr = levels(x$chr), lodcolumn = 1:min(ncol(x)-2,100), n.col = 256, allow.neg = FALSE, threshold.lod = 0, cluster = TRUE, bwd = 0.001, annot, cisnam, ...)

`x`	An object of class `"scanone"`, as output by `scanone`
`chr`	Optional vector indicating chromosomes to plot; this should be a character vector referring to chromosomes by name
`lodcolumn`	A vector of integers indicating which of the LOD score columns to plot. Although the number of columns is suggested to be <100, larger numbers are allowed.
`n.col`	Number of colors / bins to use for LOD scores
`allow.neg`	Logical, if FALSE, sets negative LOD scores to 0
`threshold.lod`	Logical, default is 0. If traits do not have LOD >= threshold.lod, they are excluded from plot.
`cluster`	Logical; if TRUE, hierarchical clustering used to order traits by similar LOD patterns. If FALSE, same order as specified in lod.column
`bwd`	Numeric value for space between chromosomes in plot; in same units as "pos" values in x.
`annot`	Optional data.frame of trait annotation consisting of two columns: `chr` (Chromosome name, as a factor, with levels in the same order as x$chr) and `pos` (Position of trait in the same units as x$pos) rownames(annot) should be the trait IDs, the same as colnames(x)[-(1:2)].
`cisnam`	Optional character vector of trait names that are defined as CIS; these will be labelled in red on the plot. See Details.
`...`	Optional parameters to pass to axis(), points() or mtext() functions

The cisname vector can be taken from the output of peaks: Let peaks.out be output from the peaks() function. Then use either unlist(sapply(peaks.out$maxpos.cis, names)) or peaks.out$peaks$id[peaks.out$peaks$cis==1].

Brian Yandell and Aimee Teo Broman

peaks

data(fake.f2expr)
fake.f2expr <- calc.genoprob(fake.f2expr)

scan.f2 <- scanone(fake.f2expr,pheno.col=1:100, method="hk")
maxlod.f2 <- maxlod(scan.f2)
sigpos.f2 <- maxlod.sigpos(maxlod.f2,sig.lod=3)

## Fake annotation ##
data(fake.annot)

peaks.f2 <- peaks(maxlod.f2,sigpos.f2,fake.annot)

cisnam <- peaks.f2$peaks$id[peaks.f2$peaks$cis==1]
# unlist(sapply(peaks.f2$maxpos.cis,names))

image.scanone(scan.f2,lodcolumn=1:100,threshold.lod=3,
   cisnam=cisnam,annot=fake.annot)