"FCSmetadata-class" {rflowcyt}R Documentation

Class "FCSmetadata" Metadata portion of a Flow Cytometry Standard object

Description

Information from the HEADER and TEXT of a raw binary FCS file about the data and other parameters are stored in the metadata.

Objects from the Class

Objects can be created by calls of the form new("FCSmetadata", ...).

Slots

mode:
Object of class "character" the "$MODE" mode of the raw binary FCS file
size:
Object of class "numeric" the "$TOT" row dimension of the data; describing the number of observations or cells
nparam:
Object of class "numeric" the "$PAR" column dimension of the data; describing the number of parameters
shortnames:
Object of class "vector" the "$PnN" short names corresponding to the column variables of the data; these names are generally non-descript and are not used as the names of the columns of the data
longnames:
Object of class "vector" the "$PnS" long names used for the column variables of the data
paramranges:
Object of class "vector" the "$PnR" maximum value corresponding to the column variables
filename:
Object of class "character" path and/or name of the original raw binary FCS object
objectname:
Object of class "character" the name of the original, FCS-class object
original:
Object of class "logical" the original status of the current object
fcsinfo:
Object of class "list" the other parameters and values in the HEADER and TEXT of the raw binary FCS file

Methods

"["
signature(x = "FCSmetadata"): Extracts the metadata slots or metadata@fcsinfo slots by using a single character name index; Extracts the metadata@fcsinfo slots by using a single or vector of numerical indicies
"[<-"
signature(x = "FCSmetadata"): Replaces the metadata slots or metadata@fcsinfo slots by using a single character name index; Replaces the metadata@fcsinfo slots by using a single or vector of numerical indicies;Adds a new slot to the metadata@fcsinfo
"[["
signature(x = "FCSmetadata"): Extracts the metadata slots or metadata@fcsinfo slots by using a single character name index; Extracts the metadata@fcsinfo slots by using a single or vector of numerical indicies
"[[<-"
signature(x = "FCSmetadata"): Replaces the metadata slots or metadata@fcsinfo slots by using a single character name index; Replaces the metadata@fcsinfo slots by using a single or vector of numerical indicies;Adds a new slot to the metadata@fcsinfo
"print-methods"
signature(x = "FCSmetadata"): prints the original status, the objectname, filename, and dimensions of the data
"show-methods"
signature(object = "FCSmetadata"): same as 'print'
"summary-methods"
signature(object = "FCSmetadata"): summaries the metadata in a string output

Note

For more information about the different parameters in the metadata@fcsinfo slot, please look at the documentation for read.FCS.

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

read.FCS, "FCS-class", "print-methods", "show-methods", "summary-methods", "[-methods", "[[-methods", "[<--methods", "[[<--methods"

Examples

default<-new("FCSmetadata")

some.meta<-new("FCSmetadata", fcsinfo=list("comment"=rep("none", 10)),
mode="none", nparam=0, size=0)

## extract/subset the metadata
some.meta[["nparam"]]
some.meta["paramranges"]
## replace the metadata/subsetassign the metadata
## 3 parameters with ranges
some.meta[["nparam"]]<-3
some.meta["paramranges"]<-rep(1,3)
## show
show(some.meta)
## print
print(some.meta)
some.meta
## summary
summary(some.meta)

[Package rflowcyt version 1.10.1 Index]