wellClassification: Retrieve a classification vector.

In CRUKMI-ComputationalBiology/twoddpcr: Classify 2-d Droplet Digital PCR (ddPCR) data and quantify the number of starting molecules

Description

Retrieve the classification from a ddpcrWell object.

Usage

wellClassification(theObject, cMethod = NULL, withAmplitudes = FALSE)

## S4 method for signature 'ddpcrWell'
wellClassification(theObject, cMethod = NULL, withAmplitudes = FALSE)

wellClassification(theObject, cMethod) <- value

## S4 replacement method for signature 'ddpcrWell'
wellClassification(theObject, cMethod) <- value

Arguments

theObject	A ddpcrWell object.
cMethod	The names (or column numbers) of the classification to retrieve. If NULL, then all of the classifications are obtained. Defaults to NULL when retrieving. When setting a classification, this cannot be NULL.
withAmplitudes	Logical value. If TRUE, returns a data frame with the droplet amplitudes and corresponding classifications. If FALSE, returns the classification vector only. Defaults to FALSE.
value	A factor with the same length as the number of droplets in theObject, with levels in ddpcr$classesRain.

Value

A factor or data frame corresponding to the requested classification(s).

Author(s)

Anthony Chiu, [e-mail]

See Also

wellClassificationMethod for the name of the classification method.

Examples

## Take some droplets with a given classification.
amplitudes <- KRASdata[["E03"]][, c("Ch1.Amplitude", "Ch2.Amplitude")]

## Create a ddpcrWell object with the amplitudes only.
aWell <- ddpcrWell(well=amplitudes)

## This has no classification yet.
head(wellClassification(aWell))

## We check the classification now, showing the amplitudes as well.
head(wellClassification(aWell, withAmplitudes=TRUE))

## Now set a sample classification.
wellClassification(aWell, cMethod="Sample") <-
  rep(c("NN", "NP", "PN", "PP"), numDroplets(aWell) / 4)
head(wellClassification(aWell, withAmplitudes=TRUE))

CRUKMI-ComputationalBiology/twoddpcr documentation built on Feb. 14, 2021, 9:18 p.m.