Description Usage Arguments Details Value Note Author(s) See Also Examples
Not counting markers classified as “FAIL” or “MONO-filt”, calculate the ratio of markers that are called for each array
1 | countFailedSNP(BSRed, inclPedErrors = TRUE)
|
BSRed |
|
inclPedErrors |
If |
In order to include pedigree errors, BSRed
must have an
assayData
entry ped.check
(see
validateCallsPedigree
)
An "AlleleSetIllumina"
object with an added
phenoData
column “passRatio”. This is a numeric vector
holding the ratio of non-missing calls for each array
This function may be used to discard arrays with a low number of called markers. Note however that an array may be valuable even if the sample falls just outside the cluster borders for many markers (e.g. for a high intensity array). Should therefore be used with caution
Lars Gidskehaug
callGenotypes
, validateCallsPedigree
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | ## Not run:
#Read pre-processed data directly into AlleleSetIllumina object
rPath <- system.file("extdata", package="beadarrayMSV")
normOpts <- setNormOptions()
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],beadInfo=beadInfo)
#Genotype calling
BSRed <- callGenotypes(BSRed)
BSRed <- validateCallsPedigree(BSRed)
BSRed <- countFailedSNP(BSRed,inclPedErrors=TRUE)
print(range(pData(BSRed)$passRatio))
#Plot highlighting markers to be discarded
#NB! Such a high passRatio is not recommended
indGoodArrays <- pData(BSRed)$passRatio > 0.6
plotGenotypes(BSRed,indHighlight=which(!indGoodArrays))
## End(Not run)
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