plot.onemap_segreg_test: Plot p-values for chi-square tests of expected segregation

In onemap: Construction of Genetic Maps in Experimental Crosses

Plot p-values for chi-square tests of expected segregation

Description

Draw a graphic showing the p-values (re-scaled to -log10(p-values)) associated with the chi-square tests for the expected segregation patterns for all markers in a dataset. It includes a vertical line showing the threshold for declaring statistical significance if Bonferroni's correction is considered, as well as the percentage of markers that will be discarded if this criterion is used.

Usage

## S3 method for class 'onemap_segreg_test'
plot(x, order = TRUE, ...)

Arguments

x	an object of class onemap_segreg_test (produced by onemap's function test_segregation()), i. e., after performing segregation tests
order	a variable to define if p-values will be ordered in the plot
...	currently ignored

Value

a ggplot graphic

Examples

 data(onemap_example_bc) # load OneMap's fake dataset for a backcross population
 BC.seg <- test_segregation(onemap_example_bc) # Applies chi-square tests
 print(BC.seg) # Shows the results
 plot(BC.seg) # Plot the graph, ordering the p-values
 plot(BC.seg, order=FALSE) # Plot the graph showing the results keeping the order in the dataset

 data(onemap_example_out) # load OneMap's fake dataset for an outcrossing population
 Out.seg <- test_segregation(onemap_example_out) # Applies chi-square tests
 print(Out.seg) # Shows the results
 plot(Out.seg) # Plot the graph, ordering the p-values
 plot(Out.seg, order=FALSE) # Plot the graph showing the results keeping the order in the dataset

onemap documentation built on Nov. 26, 2022, 9:05 a.m.