predict.tsp {tspair} | R Documentation

## Prediction based on a tsp object

### Description

This function can be used to predict outcome values for a data set based on a tsp object.

### Usage

      ## S3 method for class 'tsp':
      predict(object,dat=NULL,select=NULL,...)

### Arguments

`object` | A tsp object
`dat` | Can take two values: (a) an m genes by n arrays matrix of expression data or (b) an eSet object
`select` | An indicator of which TSP to use,defaults to the first TSP.
`...` | Plotting arguments (ignored)

### Details

predict() accepts a tsp object calculated on an expression set or gene expression matrix. If no other data set is included, the tsp predictions for the original data set are produced. If a second gene expression matrix or expression set is included, predict() looks for the gene names of the TSP in tspobj and attempts to match them in the rownames or featureNames of the gene expression matrix. If rownames or featureNames are not available, the prediction is based on the row numbers. If a match is identified, predict() makes a prediction for each gene based on the output.

### Value

`predict` | A class prediction for each array of dat based on the TSP from tspobj

### Author(s)

Jeffrey T. Leek jtleek@jhu.edu

### References

D. Geman, C. d'Avignon, D. Naiman and R. Winslow, "Classifying gene expression profiles from pairwise mRNA comparisons," Statist. Appl. in Genetics and Molecular Biology, 3, 2004.

A.C. Tan, D.Q. Naiman, L. Xu, R.L. Winslow, D. Geman, "Simple decision rules for classifying human cancers from gene expression profiles," Bioinformatics, 21:3896-3904, 2005.

### See Also

`tspplot`,`ts.pair`, `tspcalc`,`tspsig`,`summary.tsp`

### Examples

      ## Not run:
      ## Load data
      data(tspdata)

      ## Run tspcalc() on a data matrix and grp vector
      tsp1 <- tspcalc(dat,grp)

      ## Get predictions for a new eSet or data matrix
      predict.tsp(tsp1,dat2,1)
      predict(tsp1,eSet2,1)
     ## End(Not run)

[Package tspair version 1.2.0 Index]