test_segregation_of_a_marker: test_segregation_of_a_marker

In onemap: Construction of Genetic Maps in Experimental Crosses

test_segregation_of_a_marker

Description

Applies the chi-square test to check if markers 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. It does not use Yate's correction.

Usage

test_segregation_of_a_marker(x, marker, simulate.p.value = FALSE)

Arguments

x	an object of class onemap, with data and additional information.
marker	the marker which will be tested for its segregation.
simulate.p.value	a logical indicating whether to compute p-values by Monte Carlo simulation.

Details

First, the function selects the correct segregation pattern, then it defines the H0 hypothesis, and then tests it, together with percentage of missing data.

Value

a list with the H0 hypothesis being tested, the chi-square statistics, the associated p-values, and the % of individuals genotyped.

Examples

data(onemap_example_bc) # Loads a fake backcross dataset installed with onemap
test_segregation_of_a_marker(onemap_example_bc,1)

data(onemap_example_out) # Loads a fake outcross dataset installed with onemap
test_segregation_of_a_marker(onemap_example_out,1)

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