mCSEAIntegrate {mCSEA} | R Documentation

## Integrate methylation and expression

### Description

Uses mCSEA methylation analysis results and expression values to search for significant correlations between DMRs methylation and close genes expression.

### Usage

    mCSEAIntegrate(mCSEAResults, exprData, regionType = c("promoters", "genes",
      "CGI", "custom"), geneIDs = "SYMBOL", dmrName = NULL, pcutoff = 0.05,
      minCor = 0.5, minP = 0.05, makePlot = TRUE, folder = ".", nproc = 1)

### Arguments

`mCSEAResults` | The object generated by mCSEATest function
`exprData` | A matrix or data frame with genes in rows and samples in columns. A SummarizedExperiment object can be used too
`regionType` | The region types to be represented. Must be one or more of "promoters", "genes", "CGI" and "custom"
`geneIDs` | Gene identifiers used in exprData. One of "SYMBOL", "ENSEMBL", "ENTREZID", "GENEID", "REFSEQ" or "UNIGENE"
`dmrName` | The DMR of interest to correlate with expression (e.g. gene name, CGI name...). If NULL (default), all DMRs with P-Value < pcutoff are selected
`pcutoff` | P-Value threshold to select DMRs if dmrName = NULL
`minCor` | Correlation threshold to output the results
`minP` | Correlation P-Value threshold to output the results
`makePlot` | If TRUE, generate corelation and save them in the folder specified by folder parameter
`folder` | Directory to save the correlation plots if makePlot = TRUE
`nproc` | Number of processors to be used

### Value

A data.frame with the integration results.

### Author(s)

Jordi Martorell Marugán, jordi.martorell@genyo.es

### See Also

`rankProbes`, `mCSEATest`

### Examples

    data(precomputedmCSEA)
    data(exprTest)

    resultsInt <- mCSEAIntegrate(myResults, exprTest, "promoters", "ENSEMBL",
                                "GATA2", makePlot = FALSE)

    resultsInt

[Package mCSEA version 1.6.0 Index]