translationalEff: Translational efficiency
In ORFik: Open Reading Frames in Genomics

Description Usage Arguments Value References See Also Examples

Uses RnaSeq and RiboSeq to get translational efficiency of every element in 'grl'. Translational efficiency is defined as:

1	(density of RPF within ORF) / (RNA expression of ORFs transcript)

translationalEff(
  grl,
  RNA,
  RFP,
  tx,
  with.fpkm = FALSE,
  pseudoCount = 0,
  librarySize = "full",
  weight.RFP = 1L,
  weight.RNA = 1L
)

`grl`	a `GRangesList` object can be either transcripts, 5' utrs, cds', 3' utrs or ORFs as a special case (uORFs, potential new cds' etc). If regions are not spliced you can send a `GRanges` object.
`RNA`	RnaSeq reads as `GAlignments`, `GRanges` or GRangesList object
`RFP`	RiboSeq reads as `GAlignments`, `GRanges` or GRangesList object
`tx`	a GRangesList of the transcripts. If you used cage data, then the tss for the the leaders have changed, therefor the tx lengths have changed. To account for that call: ' translationalEff(grl, RNA, RFP, tx = extendLeaders(tx, cageFiveUTRs)) ' where cageFiveUTRs are the reannotated by CageSeq data leaders.
`with.fpkm`	logical, default: FALSE, if true return the fpkm values together with translational efficiency as a data.table
`pseudoCount`	an integer, by default is 0, set it to 1 if you want to avoid NA and inf values.
`librarySize`	either numeric value or character vector. Default ("full"), number of alignments in library (reads). If you just have a subset, you can give the value by librarySize = length(wholeLib), if you want lib size to be only number of reads overlapping grl, do: librarySize = "overlapping" sum(countOverlaps(reads, grl) > 0), if reads[1] has 3 hits in grl, and reads[2] has 2 hits, librarySize will be 2, not 5. You can also get the inverse overlap, if you want lib size to be total number of overlaps, do: librarySize = "DESeq" This is standard fpkm way of DESeq2::fpkm(robust = FALSE) sum(countOverlaps(grl, reads)) if grl[1] has 3 reads and grl[2] has 2 reads, librarySize is 5, not 2.
`weight.RFP`	a vector (default: 1L). Can also be character name of column in RFP. As in translationalEff(weight = "score") for: GRanges("chr1", 1, "+", score = 5), would mean score column tells that this alignment region was found 5 times.
`weight.RNA`	Same as weightRFP but for RNA weights. (default: 1L)

a numeric vector of fpkm ratios, if with.fpkm is TRUE, return a data.table with te and fpkm values (total 3 columns then)

doi: 10.1126/science.1168978

Other features: computeFeaturesCage(), computeFeatures(), countOverlapsW(), disengagementScore(), distToCds(), distToTSS(), entropy(), floss(), fpkm_calc(), fpkm(), fractionLength(), initiationScore(), insideOutsideORF(), isInFrame(), isOverlapping(), kozakSequenceScore(), orfScore(), rankOrder(), ribosomeReleaseScore(), ribosomeStallingScore(), startRegionCoverage(), startRegion(), stopRegion(), subsetCoverage()

ORF <- GRanges(seqnames = "1",
               ranges = IRanges(start = c(1, 10, 20), end = c(5, 15, 25)),
               strand = "+")
grl <- GRangesList(tx1_1 = ORF)
RFP <- GRanges("1", IRanges(25, 25), "+")
RNA <- GRanges("1", IRanges(1, 50), "+")
tx <-  GRangesList(tx1 = GRanges("1", IRanges(1, 50), "+"))
# grl must have same names as cds + _1 etc, so that they can be matched.
te <- translationalEff(grl, RNA, RFP, tx, with.fpkm = TRUE, pseudoCount = 1)
te$fpkmRFP
te$te