thresholdClassify: Set thresholds to classify droplets.

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

Description

Classify droplets as "NN", "NP", "PN" or "PP" depending on whether they lie above or below given thresholds. This is illustrated in the details and parameters for more detail.

Usage

thresholdClassify(droplets, ch1Threshold = 6500, ch2Threshold = 2900, ...)

## S4 method for signature 'data.frame'
thresholdClassify(
  droplets,
  ch1Threshold = 6500,
  ch2Threshold = 2900,
  fullTable = TRUE
)

## S4 method for signature 'ddpcrWell'
thresholdClassify(
  droplets,
  ch1Threshold = 6500,
  ch2Threshold = 2900,
  classMethodLabel = "thresholds"
)

## S4 method for signature 'ddpcrPlate'
thresholdClassify(
  droplets,
  ch1Threshold = 6500,
  ch2Threshold = 2900,
  classMethodLabel = "thresholds"
)

Arguments

droplets	A ddpcrWell object or a data frame of droplet amplitudes with columns Ch1.Amplitude and Ch2.Amplitude.
ch1Threshold	The channel 1 upper bound for the NN and NP classes. Defaults to 8000
ch2Threshold	The channel 2 upper bound for the NN and PN classes. Defaults to 3000.
...	Other options depending on the type of droplets.
fullTable	Whether to return a data frame including amplitude figures. If TRUE, a data frame with columns Ch1.Amplitude, Ch1.Amplitude and class is returned. If FALSE, a factor with levels in ddpcr$classesRain is returned, where each entry corresponds to each row in droplets (and trainingData is automatically set to FALSE). Defaults to TRUE.
classMethodLabel	A name (as a character string) of the classification method. Defaults to "thresholds".

Details

The threshold parameters correspond to those in the following diagram:

Ch1 ^          |
    |          |
    |          |
    |    PN    |    PP
    |          |
    |          |
   a|__________|__________
    |          |
    |          |
    |    NN    |    NP
    |          |
    |          |
    --------------------->
               b      Ch2

Specifically:

a:

ch1Threshold,

b:

ch2Threshold.

Value

If droplets is a data frame, return a data frame or factor (depending on the trainingData and fullTable parameters) with a classification for droplets in the chosen regions.

If droplets is a ddpcrWell object, return a ddpcrWell object with the appropriate classification.

If droplets is a ddpcrPlate object, return a ddpcrPlate object with the appropriate classification.

Author(s)

Anthony Chiu, [e-mail]

See Also

This function is a special case of gridClassify.

Examples

## Use thresholds to set a classification for a data frame.
gCl <- thresholdClassify(KRASdata[["E03"]],
                         ch1Threshold=6789, ch2Threshold=3000)
str(gCl)

## The same works for ddpcrWell objects.
aWell <- ddpcrWell(well=KRASdata[["E03"]])
aWell <- thresholdClassify(aWell, ch1Threshold=6789, ch2Threshold=3000)
str(aWell)

## ddpcrPlate objects work in exactly the same way.
krasPlate <- ddpcrPlate(wells=KRASdata)
krasPlate <- thresholdClassify(krasPlate,
                               ch1Threshold=6789, ch2Threshold=3000)
lapply(plateClassification(krasPlate, withAmplitudes=TRUE), head, n=1)

## The default classification method (column name) is 'threshold'. It can be
## changed by providing a label.
krasPlate <- ddpcrPlate(wells=KRASdata)
krasPlate <- thresholdClassify(krasPlate,
                               ch1Threshold=6789, ch2Threshold=3000,
                               classMethodLabel="manual")
lapply(plateClassification(krasPlate, withAmplitudes=TRUE), head, n=1)

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