RNAmodR developments functions

These functions are not intended for general use, but are used for additional package development.

getData is used to load data into a SequenceData object and must be implented for all SequenceData classes. The results must match the requirements outlined in the value section.

In addition the following functions should be implemented for complete functionality:

aggregateData for each SequenceData and Modifier class. See also aggregateData

findMod for each Modifier class. See also findMod.

plotData/plotDataByCoord for each Modifier and ModifierSet class. See also plotData.

The following helper function can be called from within findMod to construct a coordinate for each modification found:

constructModRanges constructs a GRanges object describing the location, type and associated scores of a modification. constructModRanges is typically called from the modify function, which must be implemented for all Modifier classes.

constructModRanges(range, data, modType, scoreFun, source, type)

getData(x, bamfiles, grl, sequences, param, args)

# S4 method for GRanges,DataFrame
constructModRanges(range, data, modType, scoreFun, source, type)

Arguments

range

for constructModRanges: a GRanges object

data

for constructModRanges: a DataFrame object

modType

for constructModRanges: a valid shortName for the modification found. Must be present in shortName(ModRNAString()).

scoreFun

for constructModRanges: a custom function for extracting scores from data. The result must be a list.

source

for constructModRanges: a single character vector for populating the source column of the result.

type

for constructModRanges: a single character vector for populating the source column of the result.

x

for getData:a SequenceData object.

bamfiles

for getData:a BamFileList object.

grl

for getData:a GRangesList object.

sequences

for getData:a XStringSet object.

param

for getData:a ScanBamParam object.

args

for getData: a list with optional arguments.

Value

• getData: returns a list with elements per BamFile in bamfiles. Elements can be IntegerList, NumericList or a CompressedSplitDataFrameList. The data in the elements must be order by increasing positions numbers. However, names and rownames will be discarded.

• constructModRanges: returns a GRanges object with genomic coordinates of modified nucleotides in the associated transcripts.

Examples

# new SequenceData class
setClass(Class = "ExampleSequenceData",
         contains = "SequenceData",
         prototype = list(minQuality = 5L))
ExampleSequenceData <- function(bamfiles, annotation, sequences, seqinfo, ...){
  RNAmodR:::SequenceData("Example", bamfiles = bamfiles, 
                         annotation = annotation, sequences = sequences,
                         seqinfo = seqinfo, ...)
}
setMethod("getData",
          signature = c(x = "ExampleSequenceData",
                        bamfiles = "BamFileList",
                        grl = "GRangesList",
                        sequences = "XStringSet",
                        param = "ScanBamParam"),
          definition = function(x, bamfiles, grl, sequences, param, args){
            ###
          }
)
setMethod("aggregateData",
          signature = c(x = "ExampleSequenceData"),
          function(x, condition = c("Both","Treated","Control")){
            ###
          }
)
setMethod(
  f = "getDataTrack",
  signature = c(x = "ExampleSequenceData"),
  definition = function(x, name, ...) {
    ###
  }
)

# new Modifier class
setClass("ModExample",
         contains = "Modifier",
         prototype = list(mod = "X",
                          score = "score",
                          dataType = "ExampleSequenceData"))
ModExample <- function(x, annotation, sequences, seqinfo, ...){
  RNAmodR:::Modifier("ModExample", x = x, annotation = annotation,
                     sequences = sequences, seqinfo = seqinfo, ...)
}

setMethod(f = "aggregateData",
          signature = c(x = "ModExample"),
          definition =
            function(x, force = FALSE){
              # Some data with element per transcript
            }
)

setMethod("findMod",
          signature = c(x = "ModExample"),
          function(x){
            # an element per modification found.
          }
)
setMethod(
  f = "getDataTrack",
  signature = signature(x = "ModExample"),
  definition = function(x, name, type, ...) {
  }
)
setMethod(
  f = "plotDataByCoord",
  signature = signature(x = "ModExample", coord = "GRanges"),
  definition = function(x, coord, type = "score", window.size = 15L, ...) {
  }
)
setMethod(
  f = "plotData",
  signature = signature(x = "ModExample"),
  definition = function(x, name, from, to, type = "score", ...) {
  }
)
 
# new ModifierSet class
setClass("ModSetExample",
         contains = "ModifierSet",
         prototype = list(elementType = "ModExample"))
ModSetExample <- function(x, annotation, sequences, seqinfo, ...){
  RNAmodR:::ModifierSet("ModExample", x = x, annotation = annotation,
                        sequences = sequences, seqinfo = seqinfo, ...)
}

setMethod(
  f = "plotDataByCoord",
  signature = signature(x = "ModSetExample", coord = "GRanges"),
  definition = function(x, coord, type = "score", window.size = 15L, ...) {
  }
)
setMethod(
  f = "plotData",
  signature = signature(x = "ModSetExample"),
  definition = function(x, name, from, to, type = "score", ...) {
  }
)