mCSEAIntegrate: Integrate methylation and expression
In mCSEA: Methylated CpGs Set Enrichment Analysis

Description Usage Arguments Value Author(s) See Also Examples

View source: R/mCSEAIntegrate.R

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

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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)

`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

A data.frame with the integration results.

Jordi Martorell Marug<c3><a1>n, jordi.martorell@genyo.es

rankProbes, mCSEATest

data(precomputedmCSEA)
data(exprTest)

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

resultsInt