Make.full.adjacency: Computing an adjacency table with or without Pvalues, with...

In jtcasemajor/GENEXPRESSO: Comparison of DEG and coexpression tools

Description

Calling Make.adjacencyPVal() with all the implemented methods.

Usage

Make.full.adjacency(data, PValue = T)

Arguments

data	Dataset of gene expression levels with genes in row and samples in columns
PValue	Logical value. if PValue = TRUE, all the pvalues associated with the corresponding coeffients of correlation will be computed. Could be very long on large dataframe if PValue = FALSE, only the coefficient of correlation, and TOM similarity will be computed.

Value

Dataframe with several columns. The two firsts are the pair of genes, the others are the coefficient of correlation depending on the used method, and maybe the PValues depending on the argument.

Examples

# Creating a dataset
df = matrix(runif(500, 10, 100), ncol=20)
group = paste0(rep(c("control", "case"), each = 10),rep(c(1:10),each = 1))
genes <- paste0(rep(LETTERS[1:25], each=1))
colnames(df) = group
row.names(df) = genes

# computing fast correlation and pvalues 
Adj = Make.full.adjacency(df,PValue = TRUE)

jtcasemajor/GENEXPRESSO documentation built on Dec. 21, 2021, 4:11 a.m.