qtl (version 1.66)

plotPXG: Plot phenotypes versus marker genotypes

Description

Plot the phenotype values versus the genotypes at a marker or markers.

Usage

plotPXG(x, marker, pheno.col=1, jitter=1, infer=TRUE,
         pch, ylab, main, col, ...)

Value

A data.frame with initial columns the marker genotypes, then the phenotype data, then a column indicating whether any of the marker genotypes were inferred (1=at least one genotype inferred, 0=none were inferred).

Arguments

x

An object of class cross. See read.cross for details.

marker

Marker name (a character string; can be a vector).

pheno.col

Column number in the phenotype matrix which should be used as the phenotype. One may also give a character string matching a phenotype name. Finally, one may give a numeric vector of phenotypes, in which case it must have the length equal to the number of individuals in the cross, and there must be either non-integers or values < 1 or > no. phenotypes; this last case may be useful for studying transformations.

jitter

A positive number indicating how much to spread out the points horizontally. (Larger numbers correspond to greater spread.)

infer

If TRUE, missing genotypes are filled in with a single random imputation and plotted in red; if FALSE, only individuals typed at the specified marker are plotted.

pch

Plot symbol.

ylab

Label for y-axis.

main

Main title for the plot. If missing, the names of the markers are used.

col

A vector of colors to use for the confidence intervals (optional).

...

Passed to plot.

Author

Karl W Broman, ; Brian Yandell

Details

Plots the phenotype data against the genotypes at the specified marker. If infer=TRUE, the genotypes of individuals that were not typed is inferred based the genotypes at linked markers via a single imputation from sim.geno; these points are plotted in red. For each genotype, the phenotypic mean is plotted, with error bars at \(\pm\) 1 SE.

See Also

find.marker, effectplot, find.flanking, effectscan

Examples

data(listeria)
mname <- find.marker(listeria, 5, 28) # marker D5M357
plotPXG(listeria, mname)

mname2 <- find.marker(listeria, 13, 26) # marker D13Mit147
plotPXG(listeria, c(mname, mname2))
plotPXG(listeria, c(mname2, mname))

# output of the function contains the raw data
output <- plotPXG(listeria, mname)
head(output)

# another example
data(fake.f2)
mname <- find.marker(fake.f2, 1, 37) # marker D1M437
plotPXG(fake.f2, mname)

mname2 <- find.marker(fake.f2, "X", 14) # marker DXM66
plotPXG(fake.f2, mname2)

plotPXG(fake.f2, c(mname,mname2))
plotPXG(fake.f2, c(mname2,mname))