calculateCorForTwoMatrices: Identify the significant correlations between two matrices.

In multiOmicsViz: Plot the effect of one omics data on other omics data along the chromosome

Description

The calculateCorForTwoMatrices function uses the spearman correlation to identify the significant correlations between two matrices.

Usage

calculateCorForTwoMatrices(matrix1,matrix2,fdr)

Arguments

matrix1	A R matrix, data.frame or SummarizedExperiment object containing the numeric values.
matrix2	A R matrix, data.frame or SummarizedExperiment object containing the numeric values. matrix2 should have at least 6 overlapping samples with matrix1.
fdr	The FDR threshold for identifying significant correlations.

Value

This function will return a R matrix object containing significant correlations. "1" represents the significant positive correlation, "-1" represents the significant negative correlation and "0" represents no significant correlation.

Author(s)

Jing Wang

Examples

	matrix1 <- system.file("extdata","sourceOmics.txt",package="multiOmicsViz")
	matrix1 <- read.table(matrix1,header=TRUE,sep="\t",stringsAsFactors=FALSE,
	check.names=FALSE)
	
	matrix2 <- system.file("extdata","targetOmics.txt",package="multiOmicsViz")
	matrix2 <- read.table(matrix2,header=TRUE,sep="\t",stringsAsFactors=FALSE,
	check.names=FALSE)
	
	sig <- calculateCorForTwoMatrices(matrix1=matrix1,
	matrix2=matrix2,fdr=0.01)

multiOmicsViz documentation built on Nov. 8, 2020, 7:45 p.m.