tranest {LMGene}R Documentation

Glog transformation parameter estimation function

Description

Finds the best parameters for glog transformation.

Usage

tranest(eS, ngenes = -1, starting = FALSE, lambda = 1000, alpha = 0, gradtol = 0.001, lowessnorm = FALSE, method=1, mult=FALSE, model=NULL)

Arguments

eS Array data. must be exprSet type.
ngenes Number of genes that is going to be used for the parameter estimation
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 Determines optimization method. Default is 1, which corresponds to a Newton-type method (see nlm). Method 2 is based on the Nelder-Mead method (see optim).
mult If true, tranest will use a vector alpha with one entry per sample. Default is false (same alpha for every sample).
model Specifies model to be used. Default is to use all variables from eS without interactions. See details.

Details

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

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

Value

tranpar A list containing the best parameter for 'lambda' and 'alpha'

Author(s)

David Rocke, Geun-Cheol Lee and John Tillinghast

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/

Examples

#library
library(Biobase)
library(LMGene)

#data
data(sample.eS)

tranpar <- tranest(sample.eS, 100)
tranpar
tranpar <- tranest(sample.eS, mult=TRUE)
tranpar


[Package LMGene version 1.8.0 Index]