regionPerReadLength {ORFik} | R Documentation

## Find proportion of reads per position per read length in region

### Description

This is defined as: Given some transcript region (like CDS), get coverage per position. By default only returns positions that have hits, set drop.zero.dt to FALSE to get all 0 positions.

### Usage

    regionPerReadLength(
      grl,
      reads,
      acceptedLengths = NULL,
      withFrames = TRUE,
      scoring = "transcriptNormalized",
      weight = "score",
      exclude.zero.cov.grl = TRUE,
      drop.zero.dt = TRUE,
      BPPARAM = bpparam()
    )

### Arguments

`grl` | a `GRangesList` object with usually either leaders, cds', 3' utrs or ORFs
`reads` | a `GAlignments` or `GRanges` object of RiboSeq, RnaSeq etc. Weigths for scoring is default the 'score' column in 'reads'
`acceptedLengths` | an integer vector (NULL), the read lengths accepted. Default NULL, means all lengths accepted.
`withFrames` | logical TRUE, add ORF frame (frame 0, 1, 2), starting on first position of every grl.
`scoring` | a character (transcriptNormalized), which meta coverage scoring ? one of (zscore, transcriptNormalized, mean, median, sum, sumLength, fracPos), see ?coverageScorings for more info. Use to decide a scoring of hits per position for metacoverage etc. Set to NULL if you do not want meta coverage, but instead want per gene per position raw counts.
`weight` | (default: 'score'), if defined a character name of valid meta column in subject. GRanges("chr1", 1, "+", score = 5), would mean score column tells that this alignment region was found 5 times. ORFik ofst, bedoc and .bedo files contains a score column like this. As do CAGEr CAGE files and many other package formats. You can also assign a score column manually.
`exclude.zero.cov.grl` | logical, default TRUE. Do not include ranges that does not have any coverage (0 reads on them), this makes it faster to run.
`drop.zero.dt` | logical FALSE, if TRUE and as.data.table is TRUE, remove all 0 count positions. This greatly speeds up and most importantly, greatly reduces memory usage. Will not change any plots, unless 0 positions are used in some sense. (mean, median, zscore coverage will only scale differently)
`BPPARAM` | how many cores/threads to use? default: bpparam()

### Value

a data.table with lengths by coverage.

### See Also

Other coverage: `coverageScorings()`, `metaWindow()`, `scaledWindowPositions()`, `windowPerReadLength()`

### Examples

    # Raw counts per gene per position
    cds <- GRangesList(tx1 = GRanges("1", 100:129, "+"))
    reads <- GRanges("1", seq(79,129, 3), "+")
    reads$size <- 28 # <- Set read length of reads
    regionPerReadLength(cds, reads, scoring = NULL)
    ## Sum up reads in each frame per read length per gene
    regionPerReadLength(cds, reads, scoring = "frameSumPerLG")

[Package ORFik version 1.14.7 Index]