Using OneMap internal function test_segregation_of_a_marker(), performs the Chi-square test to check if all markers in a dataset are following the expected segregation pattern, i. e., 1:1:1:1 (A), 1:2:1 (B), 3:1 (C) and 1:1 (D) according to OneMap's notation.
test_segregation(x, simulate.p.value =FALSE)
Arguments
x: an object of class onemap, with data and additional information.
simulate.p.value: a logical indicating whether to compute p-values by Monte Carlo simulation.
Returns
an object of class onemap_segreg_test, which is a list with marker name, H0 hypothesis being tested, the chi-square statistics, the associated p-values and the % of individuals genotyped. To see the object, it is necessary to print it.
Details
First, it identifies the correct segregation pattern and corresponding H0 hypothesis, and then tests it.
Examples
data(onemap_example_out)# Loads a fake outcross dataset installed with onemap Chi <- test_segregation(onemap_example_out)# Performs the chi-square test for all markers print(Chi)# Shows the results