calculateCorForTwoMatrices: Identify the significant correlations between two matrices.

Description Usage Arguments Value Author(s) Examples

View source: R/calculateCorForTwoMatrices.R

Description

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

Usage

1
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

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
	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)

wangj26/multiOmicsViz documentation built on May 4, 2019, 12:58 a.m.