ktspair (version 1.0)

ktspcalc2: The k-TSP with chosen pairs of genes

Description

This function creates a ktsp object where the pairs of genes used have been selected by the user.

Usage

ktspcalc2(indice, dat, grp, length = 40, cross =5, display = display, med = FALSE, performance = FALSE, seed = NULL, healthy = NULL)

Arguments

indice

The pairs that should be used to construct the ktsp object

dat

Can either be (a) a matrix of m lines (the gene expressions) and n columns (the observations) or (b) an eSet object.

grp

Can either be (a) a character (or numeric) vector indicating the group of each observations or (b) an integer indicating the column of pData(dat) that represents the group of the observations.

length

This paramters allows the used to control the length of the list used in the C code.

cross

The number of fold that should be used in the crossvalidation.

display

Allows the user to avoid the function ktspcalc() to print waring message over the loop.

med

If the mean of the median between the two groups for each gene should be substracted to the dataset or not.

performance

An indicator if the performance of the model should be computed or not.

seed

The crossvalidation and the computation of the performance of the model are based on a random partition of the dataset. The variable seed allows the user to fix a seed.

healthy

This variable is used to determine which group will be considerer as the healthy group (specificity). Need to give the label of the group in the same form as given in the variable grp.

Value

A ktsp object, see the function ktspcalc() for more details.

Details

This function would be useful when the user wants to select pairs of genes based on the results of the bootstrap. The pairs of genes will be then reordered based on the score Delta and Gamma from the best one to the worst one. When the genes are inserted (through the variable indice), the two first genes will represent the first pair, the two next genes the second pair, etc.

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.

J. Damond, supervised by S. Morgenthaler and S. Hosseinian, "Presentation and study of robustness for several methods to classify individuals based on their gene expressions", Master thesis, Swiss Federal Institute of Technology Lausanne (Switzerland), 2011. J. Damond, S. Morgenthaler, S. Hosseinian, "The robustness of the TSP and the k-TSP and the computation of ROC curves", paper is submitted in Bioinformatics, December 2011. Jeffrey T. Leek (). tspair: Top Scoring Pairs for Microarray Classification. R package version 1.10.0.

See Also

ktspcalc, ktspplot,predict.ktsp, summary.ktsp

Examples

  ## Not run: 
#   ## Load data
#   data(ktspdata) 
#   ktsp2 <- ktspcalc2(c(100,200,300,400),dat, grp)
#   ktsp2
#  ## End(Not run)