CAEN {CAEN} | R Documentation

## Compute the correlation coefficient of gene with category number to identify differentially expressed genes

### Description

To Compute the correlation coefficient of gene with category number to identify differentially expressed genes.

### Usage

    CAEN(dataTable, y, K, gene_no_list)

### Arguments

`dataTable` | would be a SummarizedExperiment Bioconductor object, then it would be transformed into a p times n matrix - i.e. features on the rows and observations on the columns in the function, or dataTable would be a p times n matrix.
`y` | the category for each sample
`K` | the number of class
`gene_no_list` | the number of differentially expressed genes you want to select

### Value

list(.) A list of computed correlation coefficient and the first some differentially expressed genes , where "r" represents correlation coefficient between gene and category number, and "np" represents the top differential feature label.

### Examples

    library(SummarizedExperiment)
    dat <- newCountDataSet(n=40,p=500,sdsignal=0.1,K=4,param=10,drate=0.4)
    x <- dat$sim_train_data
    y <- as.numeric(colnames(dat$sim_train_data))
    myscore <- CAEN(dataTable=x, y=y, K=4, gene_no_list=100)

[Package CAEN version 1.0.0 Index]