Measurement of mRNA abundance using RNA-seq data: RPKM measure is inconsistent among samples
Top Cited Papers
- 8 August 2012
- journal article
- research article
- Published by Springer Nature in Theory in Biosciences
- Vol. 131 (4), 281-285
- https://doi.org/10.1007/s12064-012-0162-3
Abstract
Measures of RNA abundance are important for many areas of biology and often obtained from high-throughput RNA sequencing methods such as Illumina sequence data. These measures need to be normalized to remove technical biases inherent in the sequencing approach, most notably the length of the RNA species and the sequencing depth of a sample. These biases are corrected in the widely used reads per kilobase per million reads (RPKM) measure. Here, we argue that the intended meaning of RPKM is a measure of relative molar RNA concentration (rmc) and show that for each set of transcripts the average rmc is a constant, namely the inverse of the number of transcripts mapped. Further, we show that RPKM does not respect this invariance property and thus cannot be an accurate measure of rmc. We propose a slight modification of RPKM that eliminates this inconsistency and call it TPM for transcripts per million. TPM respects the average invariance and eliminates statistical biases inherent in the RPKM measure.Keywords
This publication has 8 references indexed in Scilit:
- Theories of MeaningfulnessPublished by Taylor & Francis ,2012
- Transcriptomic analysis of avian digits reveals conserved and derived digit identities in birdsNature, 2011
- Measurement and Meaning in BiologyThe Quarterly Review of Biology, 2011
- RNA sequencing: advances, challenges and opportunitiesNature Reviews Genetics, 2010
- Statistical inferences for isoform expression in RNA-SeqBioinformatics, 2009
- RNA-Seq: a revolutionary tool for transcriptomicsNature Reviews Genetics, 2009
- Mapping and quantifying mammalian transcriptomes by RNA-SeqNature Methods, 2008
- Function of alternative splicingGene, 2004