summary.wgaim {wgaim} | R Documentation |
Prints a summary of the "wgaim
" object in a presentable format
## S3 method for class 'wgaim': summary(object, parentData, ...) ## S3 method for class 'wgaim': print(x, parentData, ...)
object |
an object of class "wgaim " |
x |
an object of class "wgaim " |
parentData |
A data structure of class "cross " containing
the genotypic data as well as the phenotypic data |
... |
further arguments passed to or from other methods |
It is important that the parentData
is not missing as it
contains vital summary information about each of the QTL's detected.
A summary of the QTL component of the "wgaim
" object is
printed to the screen. For each QTL detected, the
summary.wgaim
prints which chromosome, name and distance of
each flanking marker, size, z-ratio and LOD
score. print.wgaim
provides a narrative brief of the QTL's detected.
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, 195-211.
## 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") # summarise print(zn.qtl, raccasM) summary(zn.qtl, raccasM) ## End(Not run)