Description Usage Arguments Value Note Author(s) See Also Examples
Initial cluster centres are suggested based on the “theta”
values of a single marker. Usually called by getCenters
or getSpecificCenters
1 2 | findClusters(theta, breaks = seq(-0.25, 1.25, 0.05), minBin = 2,
plot = FALSE)
|
theta |
Numeric vector of polar coordinates angles for a single marker, as
given in the |
breaks |
Histogram breakpoints. See |
minBin |
The minimum peak height below which peaks are set to zero |
plot |
If |
A list containing
clPeaks |
Suggested cluster centres |
clSizes |
Estimated number of samples in each cluster |
nCl |
Number of clusters |
This is a “quick and dirty” way of estimating cluster
centres. The function getCenters
is used as a wrapper to
findClusters
and returns interpreted output after calling the
latter function several times with different arguments
Lars Gidskehaug
getCenters
, getSpecificCenters
,
createAlleleSet
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ## Not run:
#Read pre-processed data directly into AlleleSetIllumina object
rPath <- system.file("extdata", package="beadarrayMSV")
dataFiles <- makeFilenames('testdata',normOpts,rPath)
beadFile <- paste(rPath,'beadData_testdata.txt',sep='/')
beadInfo <- read.table(beadFile,sep='\t',header=TRUE,as.is=TRUE)
BSRed <- createAlleleSetFromFiles(dataFiles[1:4],markers=1:10,beadInfo=beadInfo)
#Tune resolution or filter to achieve monomorphic marker
print(findClusters(assayData(BSRed)$theta[1,],plot=TRUE))
print(findClusters(assayData(BSRed)$theta[1,],breaks=seq(-0.25,1.25,0.1),plot=TRUE))
print(findClusters(assayData(BSRed)$theta[1,],minBin=5,plot=TRUE))
#Tune resolution to achieve MSV-5 call
par(mfrow=c(3,1),mai=c(.5,.5,.5,.1))
plot(assayData(BSRed)$theta[2,],assayData(BSRed)$intensity[2,],pch='o')
print(findClusters(assayData(BSRed)$theta[2,],plot=TRUE))
print(findClusters(assayData(BSRed)$theta[2,],breaks=seq(-0.25,1.25,0.04),plot=TRUE))
## End(Not run)
|
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