get_sample: Read an FCS File and Do Some Processing
In rogerswt/wadeTools: Wade's Hodgepodge of Flow Cytometry Functions

get_sample

R Documentation

Read an FCS File and Do Some Processing

Description

Read a FCS file using read.FCS and return a flowFrame. Along the way, optionally apply compensation, transformation, removal of 'rail' events, and apply some parameter renaming for convenience and nice pictures.

Usage

get_sample(
  fn,
  compensate = TRUE,
  spill_matrix = NULL,
  transform = TRUE,
  transform.method = c("biexp", "asinh", "log"),
  a = 0.002,
  cofactor = 5,
  derail = TRUE,
  nice.names = TRUE,
  verbose = FALSE
)

Arguments

`fn`	The fully qualified FCS filename
`compensate`	Logical, apply compensation
`spill_matrix`	Default NULL applies the SPILL matrix provided in the header of the input file. Provide a SPILL matrix of your own, if desired. Be careful that the column labels are consistent with the parameter labeling in the corresponding input file.
`transform`	Logical, apply linear transformation to scattering parameters and biexponential transformation to fluorescence parameters. If TRUE, transform.method specifies which non-linear transformation and its associated adjustable parameter (e.g. a, cofactor) is to be applied to non-scattering (e.g. fluorescence) parameters, in which case. See documentation for `doTransform` for further details.
`transform.method`	Non-linear method to be applied. Default = biexp.
`a`	The adjustable parameter for the biexp transformation (ignored unless transform.method = biexp)
`cofactor`	The adjustable parameter for the asinh transformation (ignored unless transform.method = asinh)
`derail`	Logical, get rid of events on the FSC-A and SSC-A positive axes
`nice.names`	Logical, swap 'desc' for 'name' in the flowFrame
`verbose`	Logical, report progress on the console

Details

This function is a convenience wrapper to apply commonly used processing steps as FCS data are read in. It's often important that all files in a project get processed identically. Consolidating most of the steps in one function helps us avoid mistakes.