simcross (version 0.6)

sim_crossovers: Simulate crossover locations using the Stahl model

Description

Simulate crossover locations on a single meiotic product using the Stahl model.

Usage

sim_crossovers(L, m = 10, p = 0, obligate_chiasma = FALSE, Lstar = NULL)

Value

Numeric vector of crossover locations, in cM

Arguments

L

length of chr in cM

m

Interference parameter (m=0 is no interference)

p

Proportion of chiasmata from no-interference mechanism (p=0 gives pure chi-square model)

obligate_chiasma

If TRUE, require an obligate chiasma on the 4-strand bundle at meiosis.

Lstar

Adjusted chromosome length, if obligate_chiasma=TRUE. Calculated if not provided.

Details

Chiasma locations are a superposition of two processes: a proportion p exhibiting no interference, and a proportion (1-p) following the chi-square model with interference parameter m. Crossover locations are derived by thinning the chiasma locations with probability 1/2.

Simulations are under the Stahl model with the interference parameter being an integer. This is an extension of the chi-square model, but with chiasmata being the superposition of two processes, one following the chi-square model and the other exhibiting no interference.

References

Copenhaver, G. P., Housworth, E. A. and Stahl, F. W. (2002) Crossover interference in arabidopsis. Genetics 160, 1631--1639.

Foss, E., Lande, R., Stahl, F. W. and Steinberg, C. M. (1993) Chiasma interference as a function of genetic distance. Genetics 133, 681--691.

Zhao, H., Speed, T. P. and McPeek, M. S. (1995) Statistical analysis of crossover interference using the chi-square model. Genetics 139, 1045--1056.

Examples

x <- sim_crossovers(200, 10, 0)
x <- sim_crossovers(200, 10, 0.04)
x <- sim_crossovers(100, 0, 0, obligate_chiasma=TRUE)