bim.model {bim} | R Documentation |
Posterior number and pattern of QTL, along with posterior/prior Bayes factor ratios.
bim.model( bim, cross, nqtl = 1, pattern=NULL, exact=FALSE, cutoff = 1 ) bim.nqtl( bim ) bim.pattern( bim, cross, nqtl = 1, pattern=NULL, exact=FALSE, cutoff = 1 )
bim |
object of class bim |
cross |
corresponding object of class cross (extracted by
bim.cross if not provided) |
nqtl |
subset on number of QTL |
pattern |
subset on chromosome pattern of QTL |
exact |
subset on exact pattern or number of QTL if true |
cutoff |
percent cutoff for inclusion in model selection |
bim.model
creates results from both bim.nqtl
and
bim.pattern
.
bim.nqtl
estimates posterior frequency of number of QTLs as the
margine over all other model parameters. However, note that
posterior may be influenced by prior, while Bayes factor is
empirically less sensitive for QTL model selection. Bayes factors are
ratios of bf=posterior/prior
ratios.
bim.pattern
shows at most 15 model patterns with at least
cutoff
% posterior are returned.
Patterns are comma-separate list of chromosomes, with asterisk
*
for multiple QTL per chromosome.
bim
is first subsetted using subset.bim
.
List with items nqtl
and pattern
, each containing:
posterior |
posterior for number of QTL |
prior |
prior for number of QTL |
bf |
rank-ordered posterior/prior ratios rescaled so bf[1] = 1 |
bfse |
approximate standard error for bf computed using binomial variance |
In addition, there is an object param
with values for
nqtl
, pattern
, exact
and cutoff
.
Brian S. Yandell, yandell@stat.wisc.edu
http://www.stat.wisc.edu/~yandell/qtl/software/bmqtl
plot.bim
,plot.bim.model
,subset.bim
data( verngeo.bim ) bim.model( verngeo.bim )