Description Usage Arguments Value Author(s) References Examples
A function to calculate the expected conditional F-statistics as a measure of differential gene co-expression patterns.
1 |
data.y |
A vector containing the expression values of one gene across two datasets |
data.x |
A vector containing the expression values of another gene across two datasets |
type |
A vector indicating the type of each sample, whose length is the sum of the sample sizes of data.y and data.x |
The ECF-statistics of a specific gene
Yinglei Lai
http://bioinformatics.oxfordjournals.org/content/20/17/3146.long
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | #load two of the simulated datasets
data(simulated_data)
set1_data<-simulated_data[[1]]
control_data<-simulated_data[[7]]
num_sample <- dim(set1_data)[1]
num_gene <- dim(set1_data)[2]
type <- c(rep(0,num_sample),rep(1,num_sample))
#Compute the ECF-statistic for the gene pair of gene 1 and gene 2
i=1
j=2
data.x <- c(set1_data[,i],control_data[,i])
data.y <- c(set1_data[,j],control_data[,j])
ecf <- ( cond.fyx(data.y,data.x,type) +
cond.fyx(data.x,data.y,type) )/2
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