tspair (version 1.30.0)

tspcalc: Estimate top scoring pairs from a gene expression matrix

Description

This function calculates the pair of genes that show the maximum difference in ranking between two user specified groups. The "top scoring pair" (TSP) maximizes the average of sensitivity and specificity over all rank based classifiers using a pair of genes in the data set.

Usage

tspcalc(dat,grp)

Arguments

dat

Can take two values: (a) an m genes by n arrays matrix of expression data or (b) an eSet object

grp

Can take one of two values: (a) A group indicator in character or numeric form, (b) an integer indicating the column of pData(dat) to use as the group indicator.

Value

A tsp object with elements:

index

A two-column matrix where each row is a pair of indices from the data matrix achieving the top score

tspscore

The rank based score described in Geman et al. (2004), essentially the empirical average of sensitivity and specificity for the pair.

score

The tie-breaking score described in Tan et al. (2005).

grp

The binary group indicator.

tspdat

Row i and row (i + Number of total TSPs) of this data matrix represent the expression data for the ith TSP pair.

labels

The group labels for the two groups as defined by the grp variable.

Details

tspcalc only works for two group classification. The computation time grows rapidly in the number of genes, so for large gene expression matrices one should be prepared to wait or do a pre-filtering step. The top scoring pairs methodology was originally described in Geman et al. (2004) and the unique TSP idea was described in Tan et al. (2005).

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, tspsig,predict.tsp, summary.tsp

Examples

  ## Not run: 
#   ## Load data
#   data(tspdata) 
# 
#   ## Run tspcalc() on a data matrix and grp vector
#   tsp1 <- tspcalc(dat,grp)
#   tsp1$index
# 
#   ## Run tspcalc() on an expression set and a column of the pData matrix
#   tsp2 <- tspcalc(eSet1,1)
#   tsp2$index
#  ## End(Not run)