tranestmult {LMGene}R Documentation

Glog transformation parameter estimation function for multiple parameters

Description

A sub-function of tranest which searches the best parameters for glog transformation.

Usage

tranestmult (eS, starting = FALSE, lambda = 1000, alpha = 0, gradtol = 0.001, lowessnorm=FALSE, method=1, max_iter=200, model=NULL)

Arguments

eS Array data. must be an ExpressionSet object.
starting TRUE, if the given initial parameter values are used.
lambda Initial parameter value for lambda.
alpha Initial parameter value for alpha.
gradtol a positive scalar giving the tolerance at which the scaled gradient is considered close enough to zero to terminate the algorithm.
lowessnorm TRUE, if lowess method is going to be used.
method Set optimization method; default is modified Gauss-Newton (nlm). See tranest.
max_iter Max. number of iterations of nlm to use in optimization.
model Model in terms of vlist which is compared to transformed expression data. See tranest.

Details

This is primarily an internal function. The normal way of calling it would be to call tranest with the option mult=TRUE.

The argument eS must be an ExpressionSet object from the Biobase package. If you have a data in a matrix and information about the considered factors, then you can use neweS to convert the data into an ExpressionSet object. Please see neweS in more detail.

The model argument is an optional character string, constructed like the right-hand side of a formula for lm. It specifies which of the variables in the ExpressionSet will be used in the model and whether interaction terms will be included. If model=NULL, it uses all variables from the ExpressionSet without interactions. Be careful of using interaction terms with factors; this often leads to overfitting, which will yield an error.

Value

tranpar A list (not a vector) containing the best parameter for 'lambda' and the best vector for 'alpha'.

Author(s)

David Rocke and Geun-Cheol Lee

References

B. Durbin and D.M. Rocke, (2003) Estimation of Transformation Parameters for Microarray Data, Bioinformatics, 19, 1360-1367.

http://www.idav.ucdavis.edu/~dmrocke/

See Also

tranest, tranest2

Examples

#library
library(Biobase)
library(LMGene)

#data
data(sample.eS)

tranpar <- tranestmult(sample.eS, lambda= 500, alpha=50)
tranpar

[Package LMGene version 1.12.0 Index]