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 1.1.0 Index]