qtl (version 1.39-5)

plotGeno: Plot observed genotypes, flagging likely errors

Description

Plot the genotypes on a particular chromosome for a set of individuals, flagging likely errors.

Usage

plotGeno(x, chr, ind, include.xo=TRUE, horizontal=TRUE, cutoff=4, min.sep=2, cex=1.2, ...)

Arguments

x

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

chr

The chromosome to plot. Only one chromosome is allowed. (This should be a character string referring to the chromosomes by name.)

ind

Vector of individuals to plot (passed to subset.cross). If missing, all individuals are plotted.

include.xo

If TRUE, plot X's in intervals having a crossover. Not available for a 4-way cross.

horizontal

If TRUE, chromosomes are plotted horizontally.

cutoff

Genotypes with error LOD scores above this value are flagged as possible errors.

min.sep

Markers separated by less than this value (as a percent of the chromosome length) are pulled apart, so that they may be distinguished in the picture.

cex

Character expansion for the size of points in the plot. Larger numbers give larger points; see par.

...

Ignored at this point.

Value

Details

Plots the genotypes for a set of individuals. Likely errors are indicated by red squares. In a backcross, genotypes AA and AB are indicated by white and black circles, respectively. In an intercross, genotypes AA, AB and BB are indicated by white, gray, and black circles, respectively, and the partially missing genotypes "not BB" (D in mapmaker) and "not AA" (C in mapmaker) are indicated by green and orange circles, respectively.

For the X chromosome in a backcross or intercross, hemizygous males are plotted as if they were homozygous (that is, with white and black circles).

For a 4-way cross, two lines are plotted for each individual. The left or upper line indicates the allele A (white) or B (black); the right or lower line indicates the allele C (white) or D (black). For the case that genotype is known to be only AC/BD or AD/BC, we use green and orange, respectively.

See Also

calc.errorlod, top.errorlod, subset.cross

Examples

data(hyper)

# Calculate error LOD scores
hyper <- calc.errorlod(hyper,error.prob=0.01)

# print those above a specified cutoff 
top.errorlod(hyper,cutoff=4)

# plot genotype data, flagging genotypes with error LOD > cutoff
plotGeno(hyper, chr=1, ind=160:200, cutoff=7, min.sep=2)