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runPCA

Source: R/dim_reduction.R
runPCA.Rd

Performs a Principal Component Analysis (PCA) on the expression matrix specified in data_slot.

Usage

runPCA(
  fcd,
  data_slot = "orig",
  seed = 91,
  prefix = NULL,
  markers = colnames(fcd$expr[["orig"]]),
  discard = FALSE
)

Arguments

fcd

flow cytometry dataset.

data_slot

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

seed

A seed is set for reproducibility.

prefix

Optional prefix for the slot name of the output.

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 with a Principle Components (PC) data frame saved in fcd$pca. The name of the output consists of the prefix (if given) and the data slot.

Details

runPCA

The calculation of the PC is based on the function prcomp from the R Stats Package. See the RDocumentation (https://www.rdocumentation.org/packages/stats/versions/3.6.2/topics/prcomp) for more details.