test_segregation_of_a_marker function

test_segregation_of_a_marker

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.

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.

Returns

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

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.

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)