RGSEAfix: Random Gene Set Enrichment Analysis with fixed number of...
In RGSEA: Random Gene Set Enrichment Analysis

Description Usage Arguments Value Author(s) Examples

View source: R/RGSEAfix.R

This is the function for classification and feature selection with fixed number of features from top and bottom of the subtset features.

1 2	RGSEAfix(query, reference, queryclasses, refclasses, random = 5000, featurenum = 500, iteration = 100)

`query`	A matrix, The query data. This is the data which the research wants to know the class.
`reference`	A matrix. The reference data. Based of the reference data, the research infer the class of query data.
`queryclasses`	A character vector. It contains the classes of query data. If you don't know the classes of query data, just give it a character vector equal to the number of query data.
`refclasses`	A character vector. It contains the classes of reference data. You must know it.
`random`	A numeric variable. The number of features in the subset randomly sampled from the whole features each time.
`featurenum`	A numeric varialbe. The number of features selected from top and bottom of the subset respectivelly.
`iteration`	A numeric varialbe. The times of random sampling.

[1] The times of each sample in the reference dataset is the most similar to the query data. [2] The frequencey of features selected from the top and bottom of the subsets from the query data, if the query data is correcly classified.

Chengcheng Ma

if(interactive()) {
    data(e1)
    data(e2)
    RGSEAfix(e1,e2, queryclasses=colnames(e1), refclasses=colnames(e2),      
random=20000, featurenum=1000, iteration=100)->test
}