"FCSgate-class" {rflowcyt} | R Documentation

## Class "FCSgate" Flow Cytometry Standard extension to gating

### Description

This class of objects extends the class `FCS-class` to incorporate information from gating which is a procedure by which rows or cells from the data are selected via one or two dimensional value restrictions or gating ranges.

### Objects from the Class

Objects can be created by calls of the form `new("FCSgate", ...)`. Essentially this new object includes the `FCS-class` object.

### Slots

`gate`:
  Object of class `"matrix"` containing the gating indices such that each column corresponds to a different gating procedure/index and the rows correspond to the positions of the original row/cell observations.
`history`:
  Object of class `"vector"` containing the gating history strings such that each vector element corresponds to a different gating procedure/index and each string contains information about the particular gate, column variables that were used, and other additional comments.
`extractGatedData.msg`:
  Object of class `"vector"` containing strings describing any extraction that took place corresponding to each gating procedure/index and history string; each string contains information about the particular corresponding gate column position and gate name and what value index was for inclusion/selection (ie, IndexValue.In)
`current.data.obs`:
  Object of class `"vector"` contains the current data positional values from the original data
`data`:
  Object of class `"matrix"` which holds integer data such that the columns are the variables (usually immunofluorescence measurements) and the rows are the cell observations.
`metadata`:
  Object of class `"FCSmetadata"` which holds information about the file, data, and column variables among other items in the header of the original raw FCS binary file.

### Extends

Class `"FCS"`, directly.

### Methods

No methods defined with class "FCSgate" in the signature.

### Note

The methods `createGate` and `icreateGate`, functionally without plots or interactively with plots, respectively, extends the `FCS-class` to the FCSgate-class. Some interactive gating schemes are noted in `FHCRC.HVTNFCS` and `VRC.HVTNFCS`. Further testing after gating is implemented by `runflowcytests` on the particular variable of interest which is usually the Interferon Gamma Immunofluoroescence measurement.

### Author(s)

A.J. Rossini, J.Y. Wan, and Zoe Moodie

### References

Trevor Hastie, Robert Tibshirani, and Jerome Friedman. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer Series in Statistics : New York, 2001. pp.279-283.

Jerome H. Friedman and Nicholas I. Fisher. Bump Hunting in High-Dimensional Data. Tech Report. October 28, 1998.

J. Paul Robinson, et al. Current Protocols in Cytometry. John Wiley & Sons, Inc : 2001.

Mario Roederer and Richard R. Hardy. Frequency Difference Gating: A Multivariate Method for Identifying Subsets that Differe between Samples. Cytometry, 45:56-64, 2001.

Mario Roederer and Adam Treister and Wayne Moore and Leonore A. Herzenberg. Probability Binning Comparison: A Metric for Quantitating Univariate Distribution Differences. Cytometry, 45:37-46, 2001.

Keith A. Baggerly. Probability Binning and Testing Agreement between Multivariate Immunofluorescence Histograms: Extending the Chi-Squared Test. Cytometry, 45:141-150, 2001.

### See Also

`createGate`, `icreateGate`, `extractGatedData`, `extractGateHistory`, `FHCRC.HVTNFCS`, `VRC.HVTNFCS`, `"FCS-class"`, `runflowcytests`

### Examples

    default.FCSgateobj<-new("FCSgate")

[Package rflowcyt version 1.16.0 Index]