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# runPhenograph

Source: `R/clustering.R`
`runPhenograph.Rd`

Run Phenograph based clustering.

## Usage

    runPhenograph(
      fcd,
      input_type,
      data_slot,
      k,
      seed = 91,
      prefix = NULL,
      nPC = ncol(fcd$pca[[data_slot]]),
      markers = colnames(fcd$expr[[data_slot]]),
      discard = FALSE
    )

## Arguments

fcd

  flow cytometry dataset.

input_type

  data to use for the calculation, e.g. "expr" or "pca" (suggested: "pca").

data_slot

  data slot to use for the calculation, e.g. "orig" or "norm".

k

  K value used for clustering.

seed

  A seed is set for reproducibility.

prefix

  Optional prefix for the slot name of the output.

nPC

  Number of principal components to use for the analysis.

markers

  vector of marker names to include or exclude from the calculation according to the discard parameter. See functions used_markers and measured_markers for the extraction of markers directly from the condor object

discard

  LOGICAL if the markers specified should be included, "F", or excluded, "T", from the calculation. Default = F.

## Value

The function returns a fcd including a data frame containing the phenograph clustering saved in `fcd$clustering`. The name of the output consists of the prefix (if given) and the data slot and the defined `k`. If a `nPC` is given it will be added to the output name.

## Details

runPhenograph

See [Stuchly J (2020). "Rphenoannoy: R implementation of the phenograph algorithm - approximate KNN modification, based on Rphenograph package". R package version 0.1.0.] (https://github.com/stuchly/Rphenoannoy)