anal.mcmc: Analyze a backcross by MCMC

In kbroman/qtlsim: Software for Testing QTL Analysis via Simulations

Analyze a backcross by MCMC

Description

Analyze a backcross using an MCMC model selection method.

Usage

anal.mcmc(dat, bic.mult=2.5, n.steps=1000, start=NULL)

Arguments

dat	The data: a list with components geno (the genotype data, as a matrix) and pheno (the phenotype data, as a vector).
bic.mult	Multiplier for BIC, for choosing the size of the model.
n.steps	Number of steps to take in the Markov chain.
start	Model at which to start the chain: a vector giving the columns of the genotype matrix to use as an initial state.

Value

A list giving the marker numbers chosen, the BIC criterion for the chosen model, the iteration of MCMC at which this model was first seen, and vectors giving the number of QTLs in the model and the BIC criterion, at each step of the chain

Author(s)

Karl W Broman, [e-mail]

References

Broman, K. W. (1997) Identifying quantitative trait loci in experimental crosses. PhD dissertation, Department of Statistics, University of California, Berkeley.

See Also

simbc, anal.all, anal.leaps, perm

Examples

dat <- simbc()
results <- anal.mcmc(dat)

kbroman/qtlsim documentation built on May 17, 2023, 11:53 p.m.