Function for replacing outliers for single observations by NA.
Usage
removeSingleOut(TP, singleOut, trait = attr(x = singleOut, which = "trait"))
Arguments
- TP
An object of class TP.
- singleOut
A data.frame with at least the columns plotId and timePoint with values corresponding to those in TP. If a column outlier is present, as in the output of
detectSingleOut
, only plotId x timePoint combinations for which outlier = 1 will be set to NA. If no column outlier is present, all observations in singleOut will be set to NA.- trait
The trait that should be set to NA. Can be ignored when using the output of
detectSingleOut
as input.
See also
Other functions for detecting outliers for single observations:
detectSingleOut()
,
detectSingleOutMaize()
,
plot.singleOut()
Examples
## Create a TP object containing the data from the Phenovator.
PhenovatorDat1 <- PhenovatorDat1[!PhenovatorDat1$pos %in%
c("c24r41", "c7r18", "c7r49"), ]
phenoTP <- createTimePoints(dat = PhenovatorDat1,
experimentName = "Phenovator",
genotype = "Genotype",
timePoint = "timepoints",
repId = "Replicate",
plotId = "pos",
rowNum = "y", colNum = "x",
addCheck = TRUE,
checkGenotypes = c("check1", "check2",
"check3", "check4"))
## First select a subset of plants, for example here 9 plants.
plantSel <- phenoTP[[1]]$plotId[1:9]
# Then run on the subset
resuVatorHTP <- detectSingleOut(TP = phenoTP,
trait = "EffpsII",
plotIds = plantSel,
confIntSize = 3,
nnLocfit = 0.1)
## Replace the studied trait by NA for the plants marked as outliers.
phenoTPOut <- removeSingleOut(phenoTP, resuVatorHTP)