ArticleScientific reports2020
Variability in estimated gene expression among commonly used RNA-seq pipelines.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 2 of them syntheses that pooled it.
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Who cites it
39 citing papers in PubMed, 2 syntheses or guidelines pooled it, 67 citations in OpenAlex.
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- What genes are differentially expressed in individuals with schizophrenia? A systematic review.Molecular psychiatry · 2022Pooled it
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- Harmonizing and integrating the NCI Genomic Data Commons through accessible, interactive, and cloud-enabled workflows.PloS one · 2025Article
- Identification of HER2-positive breast cancer molecular subtypes with potential clinical implications in the ALTTO clinical trial.Nature communications · 2024Article
- HOXD12 defines an age-related aggressive subtype of oligodendroglioma.Acta neuropathologica · 2024Article
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- Critical Differential Expression Assessment for Individual Bulk RNA-Seq Projects.bioRxiv : the preprint server for biology · 2024Article
- The target atlas for antibody-drug conjugates across solid cancers.Cancer gene therapy · 2024Article
- CAT Bridge: an efficient toolkit for gene-metabolite association mining from multiomics data.GigaScience · 2024Article
- Dysregulation of ferroptosis-related genes in granulosa cells associates with impaired oocyte quality in polycystic ovary syndrome.Frontiers in endocrinology · 2024Article
- Advances in multi-omics integrated analysis methods based on the gut microbiome and their applications.Frontiers in microbiology · 2024Review
- Identifying the stability of housekeeping genes to be used for the quantitative real-time PCR normalization in retinal tissue of streptozotocin-induced diabetic rats.International journal of ophthalmology · 2024Article
- Meta-analysis of retinal transcriptome profiling studies in animal models of myopia.Frontiers in medicine · 2024Article
- Assessment of NanoString technology as a tool for profiling circulating miRNA in maternal blood during pregnancy.Extracellular vesicles and circulating nucleic acids · 2024Article
- Spaceflight Induces Strength Decline inCells · 2023Article
- Variability in donor leukocyte counts confound the use of common RNA sequencing data normalization strategies in transcriptomic biomarker studies performed with whole blood.Scientific reports · 2023Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
RNA-sequencing data is widely used to identify disease biomarkers and therapeutic targets using numerical methods such as clustering, classification, regression, and differential expression analysis. Such approaches rely on the assumption that mRNA abundance estimates from RNA-seq are reliable estimates of true expression levels. Here, using data from five RNA-seq processing pipelines applied to 6,690 human tumor and normal tissues, we show that nearly 88% of protein-coding genes have similar gene expression profiles across all pipelines. However, for >12% of protein-coding genes, current best-in-class RNA-seq processing pipelines differ in their abundance estimates by more than four-fold when applied to exactly the same samples and the same set of RNA-seq reads. Expression fold changes are similarly affected. Many of the impacted genes are widely studied disease-associated genes. We show that impacted genes exhibit diverse patterns of discordance among pipelines, suggesting that many inter-pipeline differences contribute to overall uncertainty in mRNA abundance estimates. A concerted, community-wide effort will be needed to develop gold-standards for estimating the mRNA abundance of the discordant genes reported here. In the meantime, our list of discordantly evaluated genes provides an important resource for robust marker discovery and target selection.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.