qb.data {qtlbim} | R Documentation |
This function selects trait(s) and covariates from a cross
object to build
a model (qb.model
) for MCMC (qb.mcmc
).
qb.data(cross, pheno.col = 1, trait = c("normal","binary","ordinal"), censor = NULL, fixcov = c(0), rancov = c(0), boxcox = FALSE, standardize = FALSE, ...)
cross |
An object of class cross . See read.cross for details. |
pheno.col |
the column number for the phenotype used by model .
Currently, only one phenotype can be analyzed at a time. |
trait |
Type of the quatitative trait or dependent variable: "normal" or "binary" or "ordinal". |
censor |
Matrix of censor values with 2 columns and
nind(cross) rows. Details needed here. |
fixcov |
list of fixed covariates. The column number(s) in cross$pheno
which is(are) considered as fixed covariates. |
rancov |
list of random covariates.The column number(s) in cross$pheno
which is(are) considered as random covariates. |
boxcox |
Indicates whether to use a Boxcox transformation for the dependent variable or not: TRUE or FALSE. Note: trait has to be "normal" and all phenotypic values have to be positive for using this option. |
standardize |
Indicates whether to standardize the dependent variable or not: TRUE or FALSE. Note: trait has to be "normal" to use this option. |
... |
Extra terms not used. |
This function picks the relevant part of the data from the cross
object and prepares data for qb.model
and qb.mcmc
It can also standardize or transform continuous data if specified.
yvalue |
vector of the values of the dependent variable. |
ncategory |
number of category type if it is non-normal data. |
envi |
environment effect: TRUE or FALSE. |
nfixcov |
number of fixed covariates. |
nrancov |
number of random covariates. |
fixcoef |
values of the fixed covariate(s) for all individuals. |
rancoef |
values of the random covariate(s) for all individuals. |
nran |
number of categories defining the random covariate. |
lamda |
value of lamda, the transformation parameter for the boxcox transformation. |
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
qb.genoprob
,
qb.model
, qb.mcmc
qbData <- qb.data(cross, pheno.col = 3, rancov = 2, fixcov = 1)