.classifyOnChannel {twoddpcr} | R Documentation

## K-means classify a list of data frames individually, where each data frame comprises droplets that are negative in the same channels only.

### Description

K-means classify a list of data frames individually, where each data frame comprises droplets that are negative in the same channels only.

### Usage

    .classifyOnChannel(
      cl,
      channel,
      centres = NULL,
      minSeparation = 2000,
      fullTable = TRUE
    )

### Arguments

`cl` | List of data frames, where each data frame corresponds to a well with droplets corresponding only to "NN" and "NP" or "NN" and "PN".
`channel` | The channel on which to classify (1 or 2).
`centres` | A data frame of centres. The data frame should have columns `Ch1.Amplitude` and `Ch2.Amplitude` and row names corresponding the cluster label, e.g. "NN", "NP", "PN" or "PP".
`minSeparation` | The minimum distance required between two cluster centres in order for us to assume that k-means found two distinct clusters. Defaults to 2000.
`fullTable` | Whether to return a full table or just a vector. Defaults to 'TRUE'

### Value

A classification for `cl`.

### Author(s)

Anthony Chiu, anthony.chiu@cruk.manchester.ac.uk

[Package twoddpcr version 1.12.0 Index]