extractGatedData {rflowcyt} | R Documentation

## Extract the data of a FCS object using a specified Gating Index

### Description

This function will subset/reduce the rows of the data of an FCS object according to a column index of the "gate" matrix, which is created by using the function `createGate-methods`.

### Usage

    extractGatedData(x, gateNum = NULL, IndexValue.In = 1, MY.DEBUG = FALSE)

### Arguments

`x` | an "FCSgate" object obtained from `createGate`
`gateNum` | the column position of the gating index that is specified in the "gate" matrix
`IndexValue.In` | either 0 or 1 depending on what value should be set for inclusion in the extraction. The default is the value 1.
`MY.DEBUG` | a boolean value that prints out debugging comments The default is FALSE and no debugging comments are printed.

### Details

A "FCSgate" object with data having a reduced row length will be output along with an update to the following slots: "extractGatedData.msg" (The gateNum along with the inclusion value will be noted as a string), "current.data.obs" (the index of original data row positions that are currently in the data will be noted), and "metadata" (data dimension information will be updated along with the original status being changed to FALSE).

### Value

A "FCSgate" S4 object is returned that extends the "FCS" object to contain additional slots:

`gate` | a matrix whose columns are the gating indices for the original data
`history` | vector which corresponds to each column gating index in "gate" and holds information about what variables and type of gate that was implemented and for what ranges of values
`extractGatedData.msg` | vector of strings to specify what if any extraction has been implemented using `extractGatedData`; "NONE" specifies no extraction has been implemented on the data for that particular corresponding gating index
`current.data.obs` | vector of the original data row positions that are currently still in the data matrix

### Author(s)

A.J. Rossini and J.Y. Wan

### 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

`FCS-class`, `FCSgate-class`, `createGate`

### Examples

     if (require(rfcdmin)) {
          data.there<-is.element("MC.053",objects())
          if ((sum(data.there) != length(data.there))) {
            ## obtaining the FCS objects from VRC data
            data(MC.053min)
          }

    ####  test1 : Gating type: uniscut, univariate single cut
    test1 <- createGate(MC.053, varpos=1, gatingrange=256,
                        type="uniscut", MY.DEBUG=TRUE)

    #### test2.3 : Gating type : biscut -/-
    test2.3 <- createGate(test1, varpos=c(1,2),
                          gatingrange=c(256, 300),
                          type="biscut",
                          biscut.quadrant="-/-",
                          prev.gateNum=NULL,
                          MY.DEBUG=TRUE)

    ### test 2.3.1 : extraction
    test2.3.1 <- extractGatedData(test2.3, gateNum=2,
                                  IndexValue.In=1,
                                  MY.DEBUG=TRUE)
    }

[Package rflowcyt version 1.16.0 Index]