SimCrossCausal: Simulate Cross for Causal Tests

In byandell/qtlcmst: QTL Causal Model Selection Tests

Description

Creates cross with certain pattern of dependence across phenotypes.

Usage

SimCrossCausal(n.ind, len, n.mar, beta, add.eff, dom.eff, 
  sig2.1 = 1, sig2.2 = 1, eq.spacing = FALSE, 
  cross.type = c("bc", "f2"), normalize = FALSE)
data(CMSTCross)

Arguments

n.ind	number of individuals to simulate
len	vector specifying the chromosome lengths (in cM)
n.mar	vector specifying the number of markers per chromosome
beta	causal effect (slope) of first phenotype on others
add.eff	additive genetic effect
dom.eff	dominance genetic effect
sig2.1	residual variance for first phenotype
sig2.2	residual variance for all other phenotypes
eq.spacing	if TRUE, markers will be equally spaced
cross.type	type of cross (bc and f2 for now)
normalize	normalize values if TRUE

References

Chaibub Neto E, Broman AT, Keller MP, Attie AD, Zhang B, Zhu J, Yandell BS, Causal model selection hypothesis tests in systems genetics. Genetics (in review).

Examples

set.seed(987654321)
CMSTCross <- SimCrossCausal(n.ind = 100, 
  len = rep(100, 3), n.mar = 101,
  beta = rep(0.5, 2), add.eff = 1, dom.eff = 0, 
  sig2.1 = 0.4, sig2.2 = 0.1, eq.spacing = FALSE, 
  cross.type = "bc", normalize = TRUE)
CMSTCross <- calc.genoprob(CMSTCross, step = 1)
## Not run: 
save(CMSTCross, file = "CMSTCross.RData", compress = TRUE)

## End(Not run)

byandell/qtlcmst documentation built on May 13, 2019, 9:52 a.m.