Make.adjacency.table: Computing an adjacency table

In jtcasemajor/GENEXPRESSO: Comparison of DEG and coexpression tools

Description

This function is similar to Cor.square.matrix() and TOM.square.matrix() as it converts the square matrix into a 3 columns dataframe with no repeated pair of variables.

Usage

Make.adjacency.table(data, method)

Arguments

data	Dataset of gene expression levels with genes in row and samples in columns
method	Methods to compute the correlation coefficients. "spearman" computes the Spearman's rho, "kendall" uses the Kendall's tau and "pearson" the Pearson's product moment correlation coefficient. These functions are called via the cor() function in the stats package. "TOM" uses the TOMsimilarityFromExpr() function from the WGCNA package.

Value

Datraframe of three columns. Two first contains pair of genes, and the third one the correlation coefficient or the TOM similarity.

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 correlation for pairs of genes with Spearman's rho
Adj = Make.adjacency.table(df,method = "spearman")

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