plateClassification: Set and retrieve classifications for multiple wells.

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

Description

Retrieve multiple classification factors that have been assigned to a ddpcrPlate object.

Usage

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

Arguments

theObject	A ddpcrPlate object.
cMethod	This is the name of the classification to retrieve and should be a character vector. If NULL, then all of the classifications are obtained. Defaults to NULL.
withAmplitudes	If TRUE, the droplet amplitudes are included. Defaults to FALSE.
wellCol	If TRUE, an additional column is included in the output, where each entry is the name of the well from which the droplet originated. In this case, this setting forces the withAmplitudes parameter to TRUE. Defaults to FALSE.
value	Either: A list of factors, where each item of the list corresponds to a well; A single factor corresponding to all of the wells combined. This should be ordered by the order of the output of the amplitudes function when the rows of the data frames have been bound together, i.e. with do.call(rbind, amplitudes(theObject)).

Value

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.

Author(s)

Anthony Chiu, [e-mail]

Examples

### 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)

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