Plot segregation ratios for either observed or simulated marker data
Plot segregation ratios for either observed or simulated marker data
Plots an object of S3 class segRatio
## S3 method for class 'segRatio'plot(x, main =deparse(substitute(x)), xlab="", xlab.segRatio ="Segregation ratio",xlab.nobs ="Number of dominant markers",xlab.miss ="Number of missing markers per individual",NCLASS =100, type = c("seg.ratio","all","no","missing"),...)## S3 method for class 'simAutoMarkers'plot(x, main = deparse(substitute(x)), xlab ="Segregation ratio",...)## S3 method for class 'simAutoCross'plot(x, main = deparse(substitute(x)), xlab ="Segregation ratio",...)
Arguments
x: An object of class segRatio
xlab: label for x axis: not usually set
main: Title for plot
xlab.segRatio: x--axis label when plotting segregation proportions
xlab.nobs: x axis label when plotting no. of 1's
xlab.miss: x axis label when plotting number of missing individuals per marker
NCLASS: number of classes for histograms (Default: 100)
type: type of plot may be set to
seg.ratioHistogram of segregation proportions (Default)
noHistogram of the number of 1s
missingHistogram of the numbers of missing values per marker
allProduce all plots on one page
...: other parameters passed to plot function
Details
By default the histograms are produced of the segregation proportions. Other histograms that may be produced are numbers of observed dominant markers (recorded as a 1) and the number of individuals missing a particular marker.
## generate some autooctoploid dataa <- sim.autoMarkers(8,c(0.7,0.2,0.09,0.01))## print markers and plot segratiosprint(a)plot(a$seg.ratios)# plot the segregation ratios directlyplot(a)# plot the simAutoMarkers object## add some missing values and plot all histogramsplot(addMissing(a,0.2)$seg.ratios, type="all")