"FCSsummary-class" {rflowcyt} | R Documentation |
The data summary statistics along with metadata output help summarize a "FCS-class" object using the "summary" method.
Objects can be created by calls of the form new("FCSsummary", ...)
.
num.cells
:"numeric"
the number
of cells or rows from the datanum.param
:"numeric"
the number
of parameters or columns from the dataunivariate.stat
:"matrix"
five-number summary including the standard deviation of all the
column variables metadata.info
:"list"
with
the following slots: "Description", "ColumnParametersSummary", and "fcsinfoNames". signature(x = "FCSsummary")
: prints the output
of the summary statistics of the data and the metadatasignature(object = "FCSsummary")
: same as "print"A.J. Rossini, J.Y. Wan, and Zoe Moodie
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.
"FCS-class"
,
"show-methods"
,
"print-methods"
default.sum<-new("FCSsummary") ## show, print default.sum