sim_crossovers {simcross}

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)

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.

Value

Numeric vector of crossover locations, in cM

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)