calculateCorForTwoMatrices {multiOmicsViz} | R Documentation

## Identify the significant correlations between two matrices.

### 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)

[Package multiOmicsViz version 1.4.0 Index]