sample.bicreg.qtl.models {BayesQTLBIC} | R Documentation |
Models are sampled from each of a set of runs with different sets of independent variables (typically corresponding to multiple chromosomes), according to their posterior probabilities.
sample.bicreg.qtl.models(chrom.fits,nsim,maxtries=10)
chrom.fits |
list of bicreg.qtl objects from separate
fits by chromosome or genomic region |
nsim |
number of models to sample |
maxtries |
maximum number of retries to get nsim unique models |
Each of nsim
combined models is obtained by randomly sampling one model from each
chromosome according to its posterior probability, and combining the
x
-variables from the sampled models.
A list of models represented as a matrix (similar to the
which
matrix returned by bicreg.qtl
,
whose (i,j)
element is TRUE
if the i
th
sampled model contains the j
th variable
R.D. Ball, (rod.ball@AT@scionresearch.com)
Ball, R. D. 2001: Bayesian methods for QTL mapping based on model selection: approximate analysis using the Bayesian Information Criterion. Genetics 159: 1351–1364.
## Not run: mWhich200 <- sample.bicreg.qtl.models(chrom.fits,nsim=200)