Plot segregation ratios for either observed or simulated marker data

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Description

Plots an object of S3 class segRatio

Usage

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## 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.

Value

Used for its side-effects

Author(s)

Peter Baker p.baker1@uq.edu.au

See Also

segRatio, segregationRatios, sim.autoMarkers, sim.autoCross

Examples

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## generate some autooctoploid data
a <- sim.autoMarkers(8,c(0.7,0.2,0.09,0.01))

## print markers and plot segratios
print(a)
plot(a$seg.ratios)  # plot the segregation ratios directly
plot(a)             # plot the simAutoMarkers object

## add some missing values and plot all histograms
plot(addMissing(a,0.2)$seg.ratios, type="all")