R: Assemble training data from aggregate sequence data

trainingData {RNAmodR.ML}

R Documentation

Assemble training data from aggregate sequence data

Description

trainingData subsets the aggregate data of a ModifierML object to positions as defined by coord. Positions with an entry in the mod column are labeled TRUE.

Usage

trainingData(x, coord, ...)

## S4 method for signature 'ModifierML,GRanges'
trainingData(x, coord, ...)

## S4 method for signature 'ModifierML,GRangesList'
trainingData(x, coord, ...)

Arguments

`x`	a `ModifierML` object
`coord`	a `GRanges` or a `GRangesList` object
`...`	See `subsetByCoord` for more details. `type` is hard coded to `FALSE` to disregard subsetting by type. In addition, `merge` is set to `FALSE` by default, but it can be set to `TRUE`.

Value

a CompressedSplitDataFrameList with aggregate data and an addition label column.

Examples

data("dmod",package = "RNAmodR.ML")
setClass("ModMLExample",
         contains = c("RNAModifierML"),
         prototype = list(mod = c("D"),
                          score = "score",
                          dataType = c("PileupSequenceData",
                                       "CoverageSequenceData"),
                          mlModel = character(0)))
data("me",package = "RNAmodR.ML")
nextUPos <- function(gr){
  nextU <- lapply(seq.int(1L,2L),
                  function(i){
                    subseq <- subseq(RNAmodR::sequences(me)[dmod$Parent], start(dmod)+3L)
                    pos <- start(dmod) + 2L +
                      vapply(strsplit(as.character(subseq),""),
                             function(y){which(y == "U")[i]},integer(1))
                    ans <- dmod
                    ranges(ans) <- IRanges(start = pos, width = 1L)
                    ans
                  })
  nextU <- do.call(c,nextU)
  nextU$mod <- NULL
  unique(nextU)
}
nondmod <- nextUPos(dmod)
nondmod <- nondmod[!(nondmod %in% dmod)]
coord <- unique(c(dmod,nondmod))
coord <- coord[order(as.integer(coord$Parent))]
trainingData(me,coord)