RGSEAsd {RGSEA} | R Documentation

## Random Gene Set Enrichment Analysis features selected based on standard deviation from the mean value

### Description

This is the function for classification with features from top and bottom deviating from the mean value of the whole transcriptome for a certain standard deviations of the subtset features.

### Usage

    RGSEAsd(query, reference, queryclasses, refclasses, random = 5000, sd = 2, iteration = 100)

### Arguments

`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.
`sd` | number of standard deviations the features selected from the subset deviate from the mean value of the subset.
`iteration` | A numeric varialbe. The times of random sampling.

### Value

[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.

### Author(s)

Chengcheng Ma

### Examples

    if(interactive()) {
        data(cmap)
        test <- RGSEAsd(cmap[,1],cmap[,2:6], queryclasses=colnames(cmap)[1],
          refclasses=colnames(cmap)[2:6], random=5000, sd=2, iteration=100)
    }

[Package RGSEA version 1.21.0 Index]