wgaim.asreml {wgaim} | R Documentation |
Fits an iterative Whole Genome Average Interval Mapping (wgaim) model for QTL detection
## S3 method for class 'asreml': wgaim(baseModel, parentData, TypeI = 0.05, attempts = 5, trace = TRUE, ...)
baseModel |
A model of class "asreml " usually representing
a base model with which to build the qtl model.
|
parentData |
A data structure that inherits the class
"interval " containing the genotypic data as well as the
phenotypic data used in the baseModel . This should contain a
structure called "full.data " from appropriately merging
phenotypic and genotypic data (see read.interval and wmerge ).
|
TypeI |
The level of significance for detecting a QTL. The default is 0.05. |
attempts |
The number of attempts at convergence for the fixed or random qtl model. The default is 5. |
trace |
An automatic tracing facility. If trace = TRUE then
all asreml output is piped to the screen during the analysis.
If trace = "file.txt" , then output from all asreml models is
piped to "file.txt ". Both trace machanisms will display a
message if a QTL is detected. |
... |
Any other extra arguments to be passed to each of the
asreml calls. These may also include asreml.control arguments. |
The parentData
should contain a data structure "full.data
"
which consists of a genotypic and phenotypic information appropriately merged
(see wmerge
.)
As the Whole Genome Average Interval Mapping approach detects QTL's
sequentially it may require many calls to asreml
. For this reason
the function may seem slow and users should be patient.
It is recommended that trace = "file.txt"
be used to pipe the
sometimes invasive tracing of asreml
licensing and fitting
numerics for each model to a file. Errors, warnings and messages will
still appear on screen during this process. Note some warnings that
appear may be passed through from an asreml call and are outputted upon
exit. These may be ignored as they are handled during the execution of
the function.
To avoid lexcial scoping problems the function also places a version of
the "full.data
" from parentData
into a local data object called
"asdata
". This ensures that the final model may also be
investigated using the methods and features of the asreml
package.
An object of class "wgaim
" which also inherits the class
"asreml
" by default. The object returned is actually an asreml
object (see asreml.object
) with the addition of components from
the QTL detection listed below.
QTL |
A list of components from the significant QTL's detected
including a character vector of the significant chromosomes the
QTL's were detected in sig.chr and the significant intervals
on each chromosome in sig.int . For exploratory purposes the
final random effects qtl model is also returned in the component qtlModel . |
Julian Taylor, Simon Diffey, Ari Verbyla and Brian Cullis
Verbyla, A. P., Cullis, B. R., Thompson, R (2007) The analysis of QTL by simultaneous use of the full linkage map. Theoretical And Applied Genetics, 116, 95-111.
wmerge
, print.wgaim
, summary.wgaim
## Not run: # read in data data(zinc, package = "wgaim") data(raccas, package = "wgaim") # subset linkage map and merge genotypic with phenotypic raccasS <- subset(raccas, chr = c("1A1", "2D1", "4D2", "6A1")) raccasM <- wmerge(raccasS, zinc, by = "id") # base model zn.fm <- asreml(znconc ~ Type, random = ~ Block + id, data = zinc) # find QTL's zn.qtl <- wgaim(zn.fm, parentData = raccasM, trace = "trace.txt", na.method.X = "include") ## End(Not run)