| 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)