translationalEff {ORFik} | R Documentation

## Translational efficiency

### Description

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

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

### Usage

    translationalEff(grl, RNA, RFP, tx, with.fpkm = FALSE, pseudoCount = 0)

### Arguments

`grl` | a `GRangesList` object can be either transcripts, 5' utrs, cds', 3' utrs or ORFs as a special case (uORFs, potential new cds' etc).
`RNA` | RnaSeq reads as GAlignment, GRanges or GRangesList object
`RFP` | RiboSeq reads as GAlignment, 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 F, if true return the fpkm values together with translational efficiency
`pseudoCount` | an integer, 0, set it to 1 if you want to avoid NA and inf values. It also helps against bias from low depth libraries.

### Value

a numeric vector of fpkm ratios, if with.fpkm is TRUE, return a data.table with te and fpkm values

### References

doi: 10.1126/science.1168978

### See Also

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

### Examples

    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

[Package ORFik version 1.6.9 Index]