AllCloseByRegions: Extract clusters of RNA editing sites located closely in...
In rnaEditr: Statistical analysis of RNA editing sites and hyper-editing regions

Description Usage Arguments Details Value See Also Examples

A wrapper function to extract clusters of RNA editing sites that are located closely in genomic regions.

AllCloseByRegions(
  regions_gr,
  rnaEditMatrix,
  maxGap = 50,
  minSites = 3,
  progressBar = "time"
)

`regions_gr`	A GRanges object of input genomic regions.
`rnaEditMatrix`	A matrix (or data frame) of RNA editing level values on individual sites, with row names as site IDs in the form of "chrAA:XXXXXXXX", and column names as sample IDs. Please make sure to follow the format of example dataset (`data(rnaedit_df)`).
`maxGap`	An integer, genomic locations within `maxGap` from each other are placed into the same cluster. Defaults to 50.
`minSites`	An integer, minimum number of RNA editing sites within each resulting cluster. Defaults to 3.
`progressBar`	Name of the progress bar to use. There are currently five types of progress bars: `"time"`, `"none"`, `"text"`, `"tk"`, and `"win"`. Defaults to `"time"`. See `create_progress_bar` for more details.

The algorithm of this function is based on the clusterMaker function in the bumphunter R package. Each cluster is essentially a group of site locations such that two consecutive locations in the cluster are separated by less than maxGap.

A GRanges object containing genomic regions of RNA editing sites located closely within each input pre-defined genomic region.

TransformToGR, AllCoeditedRegions, CreateEditingTable, SummarizeAllRegions, TestAssociations, AnnotateResults

  data(rnaedit_df)
  
  exm_regions <- TransformToGR(
    genes_char = c("PHACTR4", "CCR5", "METTL7A"),
    type = "symbol",
    genome = "hg19"
  )
  
  AllCloseByRegions(
    regions_gr = exm_regions,
    rnaEditMatrix = rnaedit_df,
    maxGap = 50,
    minSites = 3,
    progressBar = "time"
  )