plot.geno {qtl} | R Documentation |
Plot the genotypes on a particular chromosome for a set of individuals, flagging likely errors.
plot.geno(x, chr, ind, include.xo=TRUE, horizontal=TRUE, cutoff=3.5, min.sep=2, cex=1.2, ...)
x |
An object of class cross . See
read.cross for details. |
chr |
Chromosome number to plot. |
ind |
Vector of individuals to plot. If missing, all individuals are plotted. |
include.xo |
If TRUE, plot red X's in intervals having a crossover. |
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. |
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.
None.
Karl W Broman, kbroman@jhsph.edu
calc.errorlod
,
plot.errorlod
, top.errorlod
,
image
data(hyper) # run calc.genoprob, then calc.errorlod; use same error.prob hyper <- calc.genoprob(hyper,error.prob=0.01) hyper <- calc.errorlod(hyper,error.prob=0.01) # plot the error LOD scores; print those above a specified cutoff plot.errorlod(hyper) plot.errorlod(hyper,chr=1) top.errorlod(hyper,cutoff=4) # plot genotype data, flagging genotypes with error LOD > cutoff plot.geno(hyper, chr=1, ind=160:200, cutoff=7, min.sep=2) # Note that if markers are extremely tightly linked, # any recombination event will have a high error LOD plot.geno(hyper, chr=1, ind=101:118, min.sep=2) hyper$geno[[1]]$map