fpkm_calc: Create normalizations of read counts

In ORFik: Open Reading Frames in Genomics

Description

A helper for [fpkm()] Normally use function [fpkm()], if you want unusual normalization , you can use this. Short for: Fragments per kilobase of transcript per million fragments Normally used in Translations efficiency calculations

Usage

fpkm_calc(counts, lengthSize, librarySize)

Arguments

counts	a list, # of read hits per group
lengthSize	a list of lengths per group
librarySize	a numeric of size 1, the # of reads in library

Value

a numeric vector

References

doi: 10.1038/nbt.1621

See Also

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

ORFik documentation built on March 27, 2021, 6 p.m.