Description Usage Arguments Value Examples
To Compute the correlation coefficient of gene with category number to identify differentially expressed genes.
1 | CAEN(dataTable, y, K, gene_no_list)
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dataTable |
Matrix or data.frame containing read counts and the row denotes the gene |
y |
the category for each sample |
K |
the number of class |
gene_no_list |
the number of differentially expressed genes you want to select |
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.
1 2 3 4 5 6 7 8 9 10 11 12 | library(SummarizedExperiment)
dat <- newCountDataSet(n=40,p=500,sdsignal=0.1,K=4,param=10,drate=0.4)
x <- t(assay(dat$sim_train_data))
y <- as.numeric(colnames(dat$sim_train_data))
xte <- t(assay(dat$sim_test_data))
prob <- estimatep(x=x,y=y,xte=x,beta=1,
type=c("mle","deseq","quantile"),prior=NULL)
prob0 <- estimatep(x=x,y=y,xte=xte,beta=1,
type=c("mle","deseq","quantile"),prior=NULL)
myscore <- CAEN(dataTable=assay(dat$sim_train_data),
y=as.numeric(colnames(dat$sim_train_data)),
K=4,gene_no_list=100)
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