performLolaEnrichment.diffMeth {RnBeads} | R Documentation

## performLolaEnrichment.diffMeth

### Description

performs LOLA enrichment analysis for a given differential methylation table.

### Usage

    performLolaEnrichment.diffMeth(rnbSet, diffmeth, lolaDbPaths,
      rank.cuts.region = c(100, 500, 1000), add.auto.rank.cut = TRUE,
      rerank = TRUE, verbose = TRUE)

### Arguments

`rnbSet` | RnBSet object for which dirrential methylation was computed
`diffmeth` | RnBDiffMeth object. See `RnBDiffMeth-class` for details.
`lolaDbPaths` | LOLA database paths
`rank.cuts.region` | Cutoffs for combined ranking that are used to determine differentially methylated regions
`add.auto.rank.cut` | flag indicating whether an automatically computed cut-off should also be considered.
`rerank` | For deterimining differential methylation: should the ranks be ranked again or should the absolute ranks be used.
`verbose` | Enable for detailed status report

### Value

a DiffMeth.lola.enrich object (S3) containing the following attributes

`region` | Enrichment information for differential methylation on the region level. A `data.table` object as returned by the `runLOLA` function from the `LOLA` package for furthert details. Each element will contain different user sets for different rank cutoffs and hyper/hypomethylation events(`userSet` column)
`lolaDb` | The loaded `lolaDb` object containing the merged databases as returned by `loadLolaDbs`

### Author(s)

Fabian Mueller

### Examples

    library(RnBeads.hg19)
    data(small.example.object)
    logger.start(fname=NA)
    # compute differential methylation
    dm <- rnb.execute.computeDiffMeth(rnb.set.example,pheno.cols=c("Sample_Group","Treatment"))
    # download LOLA DB
    lolaDest <- tempfile()
    dir.create(lolaDest)
    lolaDirs <- downloadLolaDbs(lolaDest, dbs="LOLACore")
    # perform enrichment analysis
    res <- performLolaEnrichment.diffMeth(rnb.set.example,dm,lolaDirs[["hg19"]])

[Package RnBeads version 1.10.8 Index]