Learn R Programming

MineICA (version 1.12.0)

buildMineICAParams: Creates an object of class MineICAParams

Description

This function builds an object of class MineICAParams. It contains the parameters that will be used by function runAn to analyze the ICA decomposition contained in an object of class IcaSet.

Usage

buildMineICAParams(Sfile = new("character"), Afile = new("character"), datfile = new("character"), annotfile = new("character"), resPath = "", genesPath, annot2col = new("character"), pvalCutoff = 0.05, selCutoff = 3)

Arguments

Sfile
A txt file containing the Source matrix S.
Afile
A txt file containing the Mixing matrix A.
datfile
A txt file containing the data (e.g expression data) on which the decomposition was calculated.
annotfile
Either a "rda" or "txt" file containing the annotation data for the samples (must be of dimensions samples x annotations).
resPath
The path where the outputs of the analysis will be written, default is the current directory.
genesPath
The path _within_ the resPath where the gene projections will be written. If missing, will be automatically attributed as resPath/ProjByComp/.
annot2col
A vector of colors indexed by annotation levels. If missing, will be automatically attributed using function annot2Color.
pvalCutoff
The cutoff used to consider a p-value significant, default is 0.05.
selCutoff
The cutoff applied to the absolute feature/gene projection values to consider them as contributors, default is 3. Must be either of length 1 and the same treshold is applied to all components, or of length equal to the number of components in order to a specific threshold is for each component.

Value

An object of class MineICAParams

See Also

MineICAParams, runAn

Examples

Run this code
## define default parameters and fill resPath
params <- buildMineICAParams(resPath="resMineICACarbayo/")

## change the default cutoff for selection of contribugint genes/features
params <- buildMineICAParams(resPath="resMineICACarbayo/", selCutoff=4)

Run the code above in your browser using DataLab