qb.model {qtlbim} | R Documentation |
This function sets up a genome-wide interacting QTL model by specifying global constraints on models and priors on unknowns.
qb.model(cross, epistasis = TRUE, main.nqtl = 3, mean.nqtl = main.nqtl + 3, max.nqtl = NULL, interval = NULL, chr.nqtl = NULL,intcov = c(0), depen = FALSE, prop = c(0.5, 0.1, 0.05), contrast = TRUE, ...)
cross |
An object of class cross . See read.cross for details. |
epistasis |
indicates if epistasis is included in the model: TRUE or FALSE |
main.nqtl |
prior expected number of main effect QTLs. |
mean.nqtl |
prior expected number for all QTLs on all chromosomes including QTLs with main effects, epistatic effects and gene-environment interactions. |
max.nqtl |
maximum number of QTLs allowed in the model. Default
is l+3sqrt{l} where l is main.qtl for
non-epistatic model and mean.qtl for epistatic model. |
interval |
minimum distance between any two flanking QTLs for all chromosomes. Default is the average distance between markers in each chromosome. |
chr.nqtl |
list of the maximum number of QTLs allowed to be detected
on each chromosome. Default is the length of the chromosome
divided by interval . |
intcov |
logical or 0/1 vector for fixed covariates indicating which
gene-environment interaction will be considered (default is all
FALSE , no GxE). |
depen |
=TRUE will use dependent prior for indicator variables of epistatic effects. |
prop |
prior inclusion probabilities for epistatic effects in three different scenarios:
when both (default 0.5), one (0.1) or none (0.05) of the main
effects of the two interacting QTL are included in the model. Note
that the sum of the probabilities need not be equal to 1 and
prop should be specified only when depen=TRUE .
|
contrast |
Use Cockerham model if TRUE ; otherwise estimate
genotypic values. |
... |
Not used. |
This function defines the model for Bayesian QTL mapping using qb.mcmc
.
This model considers two-way interaction as the highest level of both gene-gene and
gene-environment interactions.
qtl_envi |
Indicates if there is an interaction between the QTLs and environmental variables: TRUE or FALSE. |
This function returns a list and hence should have a differenct name from
that of the cross
object.
Dr. Nengjun Yi, et al., nyi@ms.ssg.uab.edu
qbModel <- qb.model(cross, chr.nqtl = rep(3,nchr(cross)), intcov = 1, interval = rep(10,3))