| plateClassification {twoddpcr} | R Documentation |
Retrieve multiple classification factors that have been assigned to
a ddpcrPlate object.
plateClassification(theObject, cMethod = NULL, withAmplitudes = FALSE, wellCol = FALSE) ## S4 method for signature 'ddpcrPlate' plateClassification(theObject, cMethod = NULL, withAmplitudes = FALSE, wellCol = FALSE) plateClassification(theObject, cMethod) <- value ## S4 replacement method for signature 'ddpcrPlate,character,list' plateClassification(theObject, cMethod) <- value ## S4 replacement method for signature 'ddpcrPlate,character,factor' plateClassification(theObject, cMethod) <- value
theObject |
A |
cMethod |
This is the name of the classification to retrieve and should
be a character vector. If |
withAmplitudes |
If |
wellCol |
If |
value |
Either:
|
If requesting one classification without the amplitudes, a list of factors corresponding to the classifications is returned. Otherwise, a list of data frames is returned where each row corresponds to a droplet in the corresponding well.
Anthony Chiu, anthony.chiu@cruk.manchester.ac.uk
### The examples here show how this method works by setting classifications
### using data frames. To do this, we use the
### \code{\link{thresholdClassify}} method on _data frames_. Note that
### \code{thresholdClassify} also works directly on \code{ddpcrWell} and
### \code{ddpcrPlate} objects; this is simply an illustration of
### how to use the \code{plateClassification} method directly. In general,
### it is recommended to use \code{thresholdClassify} directly on
### \code{ddpcrPlate} objects.
## Create a ddpcrPlate object.
krasPlate <- ddpcrPlate(wells=KRASdata)
## Classify a data frame of droplets and keep it in a _single_ data frame.
## Set the new classification from this.
droplets <- do.call(rbind, amplitudes(krasPlate))
clSingle <- thresholdClassify(droplets,
ch1Threshold=7000, ch2Threshold=3500,
fullTable=FALSE)
plateClassification(krasPlate, "thresholdSing") <- clSingle
## We can also set the new classification from a list of factors.
clList <- lapply(KRASdata, thresholdClassify, ch1Threshold=7000,
ch2Threshold=3500, fullTable=FALSE)
plateClassification(krasPlate, "thresholdList") <- clList
## We can get all of the classifications as a list of data frames.
plate <- plateClassification(krasPlate)
lapply(plate, head, n=1)
## We can include the droplet amplitudes columns.
plate <- plateClassification(krasPlate, withAmplitudes=TRUE)
lapply(plate, head, n=1)
## We can focus on specific classifications.
plate <- plateClassification(krasPlate, cMethod=c("thresholdSing",
"thresholdList"))
lapply(plate, head, n=1)
## The wellCol option adds an extra column showing which well the droplet
## came from.
plate <- plateClassification(krasPlate, withAmplitudes=TRUE, wellCol=TRUE)
lapply(plate, head, n=1)