ReviewRNA (New York, N.Y.)2020
Misuse of RPKM or TPM normalization when comparing across samples and sequencing protocols.
Review in RNA (New York, N.Y.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 246 papers.
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Who cites it
246 citing papers in PubMed.
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- Phytohormonal and Transcriptomic Mechanisms of Multigenerational Stress Memory in Wheat Under Weed Competition.Plant, cell & environment · 2026Article
- Long-Term Application of Fermented Fertilizer Attenuates the Accumulation of Antibiotic Resistance Genes in Aquaculture Sediment.Microorganisms · 2026Article
- Evolution of regulatory networks controlling plasticity in gene expression betweenbioRxiv : the preprint server for biology · 2026Article
- Locus-specific LINE-1 mRNA expression reflects cell-type- and stimulus-specific senescence states.Nucleic acids research · 2026Article
- Genome-wide analysis of the NAC gene family in Qu-1 doubled haploid cell line from Populus simonii × P. nigra and expression patterns under abscisic acid (ABA) treatment.BMC plant biology · 2026Article
- HER2-targeted doxorubicin-loaded cell-derived extracellular vesicles induce apoptosis of breast cancer cells via ROS/TXNIP pathway activation.Cancer cell international · 2026Article
- Role of PTK6 in the diagnosis, prognosis, and immune infiltration of pancreatic cancer based on evidence from bioinformatics analysis and experimental validation.Discover oncology · 2026Article
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- Deciphering the RNA landscapes on mammalian cell surfaces.Protein & cell · 2026Article
- Metagenome-based virome analysis identifies the oral viral signatures for periodontitis.Journal of oral microbiology · 2026Article
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186 more citing papers are in PubMed but not listed here.
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, RNA-sequencing (RNA-seq) has emerged as a powerful technology for transcriptome profiling. For a given gene, the number of mapped reads is not only dependent on its expression level and gene length, but also the sequencing depth. To normalize these dependencies, RPKM (reads per kilobase of transcript per million reads mapped) and TPM (transcripts per million) are used to measure gene or transcript expression levels. A common misconception is that RPKM and TPM values are already normalized, and thus should be comparable across samples or RNA-seq projects. However, RPKM and TPM represent the relative abundance of a transcript among a population of sequenced transcripts, and therefore depend on the composition of the RNA population in a sample. Quite often, it is reasonable to assume that total RNA concentration and distributions are very close across compared samples. Nevertheless, the sequenced RNA repertoires may differ significantly under different experimental conditions and/or across sequencing protocols; thus, the proportion of gene expression is not directly comparable in such cases. In this review, we illustrate typical scenarios in which RPKM and TPM are misused, unintentionally, and hope to raise scientists' awareness of this issue when comparing them across samples or different sequencing protocols.
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