tr.wgaim {wgaim} | R Documentation |
Display diagnostic information about the QTL detected.
Description
Displays diagnostic infomation about QTL detection and
significance for the sequence of models generated in a wgaim
analysis.
Usage
## S3 method for class 'wgaim'
tr(object, iter = 1:length(object$QTL$effects),
lik.out = TRUE, ...)
Arguments
object |
an object of class |
iter |
a vector of integers specifying what rows of the p-value matrix to display |
lik.out |
logical value. If |
... |
arguments passed to |
Details
By default the printing of the objects occur with arguments quote = FALSE
and right = TRUE
. Users should avoid using these arguments.
Value
For the selected QTL, a probability value matrix is displayed
with rows specified by iter
. If lik.out =
TRUE
then a matrix with rows consisting of the likelihood with
additive genetic variance, the likelihood without additive genetic
variance (NULL model), the test statistic and the p-value for the statistic.
Author(s)
Julian Taylor
References
Verbyla, A. P & Taylor, J. D, Verbyla, K. L (2012). RWGAIM: An efficient high dimensional random whole genome average (QTL) interval mapping approach. Genetics Research. 94, 291-306.
Julian Taylor, Arunas Vebyla (2011). R Package wgaim: QTL Analysis in Bi-Parental Populations Using Linear Mixed Models. Journal of Statistical Software, 40(7), 1-18. URL http://www.jstatsoft.org/v40/i07/.
See Also
Examples
## Not run:
# read in data
data(phenoRxK, package = "wgaim")
data(genoRxK, package = "wgaim")
# subset linkage map and convert to "interval" object
genoRxK <- subset(genoRxK, chr = c("1A", "2D1", "2D2", "3B"))
genoRxK <- cross2int(genoRxK, impute = "Martinez", id = "Genotype")
# base model
rkyld.asf <- asreml(yld ~ lrow, random = ~ Genotype + Range,
residual = ~ ar1(Range):ar1(Row), data = phenoRxK)
# find QTL
rkyld.qtl <- wgaim(rkyld.asf, intervalObj = genoRxK, merge.by = "Genotype",
trace = "trace.txt", na.action = na.method(x = "include"))
# diagnostic check
tr(rkyld.qtl, digits = 4)
## End(Not run)