onemap (version 3.0.0)

test_segregation: test_segregation

Description

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.

Usage

test_segregation(x, simulate.p.value = FALSE)

Value

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.

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.

Details

First, it identifies the correct segregation pattern and corresponding H0 hypothesis, and then tests it.

Examples

# \donttest{
 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
# }