lolaVolcanoPlot {RnBeads} | R Documentation

## lolaVolcanoPlot

### Description

plot a volcano plot showing LOLA enrichment results: LOLA p-value against the log-odds score. Colored by rank

### Usage

    lolaVolcanoPlot(lolaDb, lolaRes, includedCollections = c(),
      signifCol = "qValue", colorBy = "maxRnk", colorpanel = c())

### Arguments

`lolaDb` | LOLA DB object as returned by `LOLA::loadRegionDB` or `loadLolaDbs`
`lolaRes` | LOLA enrichment result as returned by the `runLOLA` function from the `LOLA` package
`includedCollections` | vector of collection names to be included in the plot. If empty (default), all collections are used
`signifCol` | column name of the significance score in `lolaRes`. Should be one of `c("pValueLog", "qValue")`.
`colorBy` | annotation/column in the the LOLA DB that should be used for point coloring
`colorpanel` | colors to be used for coloring the points

### Value

ggplot object containing the plot

### 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"]])
    # select the 500 most hypermethylated tiling regions in ESCs compared to iPSCs
    # in the example dataset
    lolaRes <- res$region[["hESC vs. hiPSC (based on Sample_Group)"]][["tiling"]]
    lolaRes <- lolaRes[lolaRes$userSet=="rankCut_500_hyper",]
    # plot
    lolaVolcanoPlot(res$lolaDb, lolaRes, signifCol="qValue")

[Package RnBeads version 2.4.0 Index]