Description Usage Arguments Details Value Author(s) See Also Examples
Build a simple array from a peak object.
1 | peak.2.array(peak)
|
peak |
An object of class |
Useful for a genome-wide eQTL mapping. Formats the results as a simple array which allows to use all of classical R functions (graphical, statistical, summaries, ...) and permits the results to be manipulated in the simplest way. All expression traits are represented and those which are not affected by any QTL, contain the empty data <NA>
in each column.
Return an object of class array.peak
which is a data frame whith columns:
trait |
The name of the studied traits. |
chr |
The number of the chromosome. |
mname.peak |
The peak (pseudo-)marker name when a QTL was detected. |
lod |
The peak LOD score when a QTL was detected. |
peak.cM |
The genetic position of the peak in centiMorgan(cM) when QTL was detected. |
mname.inf |
The (pseudo-)marker name corresponding to the inferior SI bound when a QTL was detected. |
inf.cM |
The genetic position of the inferior SI bound in centiMorgan(cM) when a QTL was detected. |
mname.sup |
The (pseudo-)marker names corresponding to the superior SI bound when a QTL was detected. |
sup.cM |
The genetic position of the superior SI bound in centiMorgan(cM) if a QTL was detected. |
si.quality |
The subjective quality if the support interval. See ‘ |
According the methods used to create the peak object, the following columns could be persent:
additive.effect |
The additive effects of the QTL. |
peak.bp |
The physical position of the maximum LOD peak. |
inf.bp |
The physical position of the SI lower bound. |
sup.bp |
The physical position of the SI upper bound. |
type |
The estimated type of the eQTLs ( trans or cis for cis- and trans- eQTL respectively). |
Hamid A. Khalili
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | data(seed10);
# Defining QTLs for all traits
out.em <- scanone( seed10, pheno.col=1:50, model='normal', method='hk');
out.peak <- define.peak( out.em, 'all',graph=TRUE,save.pict=TRUE);
## Not run: out.array <- peak.2.array(out.peak);
# Computing additive effect
out.peak <- calc.adef(seed10,out.em,out.peak);
# Localizing peak
data(BSpgmap);
out.peak <- localize.qtl(seed10,out.peak,BSpgmap);
## End(Not run)
out.array <- peak.2.array(out.peak);
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