qtlhot (version 1.0.4)

SimCrossCausal: Simulate Cross for Causal 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)
SimCrossIndep(n.ind, len, n.mar, beta, add.eff.1, dom.eff.1,
  add.eff.h, dom.eff.h, sig2.1 = 1, sig2.2 = 1, sig2.h = 1, 
  eq.spacing = FALSE, cross.type = "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, add.eff.1, add.eff.h

additive genetic effect

dom.eff, dom.eff.1, dom.eff.h

dominance genetic effect

sig2.1

residual variance for first phenotype

sig2.2, sig2.h

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

# NOT RUN {
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)
# }