R/pair.cor.R

In manabusakamoto/evoldiver: What the package does (short line)

pair.cor <- function(x, test=c("pearson", "kendall", "spearman"), p.adj.method=c("holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none")){
	mat <- as.matrix(x)
	n <- length(mat[1,])
	N <- n*(n-1)/2
	cor.stats <- matrix(nrow=length(mat[1,]),ncol=length(mat[1,]))
	p.value <- matrix(nrow=length(mat[1,]),ncol=length(mat[1,]))
	p.adj <- matrix(nrow=length(mat[1,]),ncol=length(mat[1,]))
	for( i in 1:length(mat[1,]) ){
		v1 <- mat[,i]
		cor <- vector()
		p <- vector()
		padj <- vector()
		for( j in 1:length(mat[1,]) ){
			v2 <- mat[,j]
			COR <- cor.test(v1,v2, method=test)
			cor <- append(cor,COR$estimate)
			p <- append(p,COR$p.value)
			padj <- append(padj,p.adjust(p[j], method = p.adj.method, n=N ))
			}
		cor.stats[i,] <- cor
		p.value[i,] <- p
		p.adj[i,] <- padj
		colnames(cor.stats)<-colnames(mat)
		rownames(cor.stats)<-colnames(mat)
		colnames(p.value)<-colnames(mat)
		rownames(p.value)<-colnames(mat)
		colnames(p.adj)<-colnames(mat)
		rownames(p.adj)<-colnames(mat)
		}
	result <- list(stats=cor.stats, p.values=p.value, p.adjust=p.adj)
	return(result)
	}