Rsq.2.array {eqtl} | R Documentation |
Add the single QTL R square data to the related general QTL description contained within peak.array
data frame.
Rsq.2.array(rsq,peak.array)
rsq |
An object of classrsq . See calc.Rsq for function details. |
peak.array |
An object of class peak.array . See peak.2.array for function details. |
Useful to store whole single QTL description within a simple array by adding the single QTL R square data. Add two columns containing the R square data from rsq
object to the related peak.array
data frame. Column Rsq
contains the R square values and column RpF
contains the R square significance. The R square data are computed by the function calc.Rsq
.
Return an object of class rsq
which is a simple data frame with columns:
qtl |
The name of the genetic determinant. If the genetic determinant is an individual QTL, the name is formated as 'trait_name'.'chr_number'.'a number' . In the case of interactives QTL, the genetic determinant name is formated as the list of individual genetic determinant names separated by ': '. |
rsq |
The Fisher value (set to NA if not significant: pF < th ). |
pF |
The significance (set to NA if not significant: pF < th ). |
Hamid A. Khalili
data(seed10); # Genotype probabilities seed10 <- calc.genoprob( cross=seed10, step=2, off.end=0, error.prob=0, map.function='kosambi', stepwidth='fixed'); seed10 <- sim.geno( cross=seed10, step=2, off.end=0, error.prob=0, map.function='kosambi', stepwidth='fixed'); # Genome scan and QTL detection out.em <- scanone( seed10, pheno.col=1:50, model='normal', method='em'); out.peak <- define.peak( out.em, 'all'); # Computing additive effect out.peak <- calc.adef(seed10,out.em,out.peak); # Localizing peak data(BSpgmap); out.peak <- localize.qtl(seed10,out.peak,BSpgmap); out.array <- peak.2.array(out.peak); # R square computing out.rsq <- calc.Rsq(seed10,out.peak); # Adding R square data out.array <- Rsq.2.array(out.rsq,out.array);