Evidence map›Paper›PMID 31341269›Full record

ReviewNature reviews. Genetics2019

RNA sequencing: the teenage years.

Rory Stark, Marta Grzelak, James Hadfield

Abstract readHistorical ArticleReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1,060 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1,060citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1,060 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. A Systematic Review of the Application of Graph Neural Networks to Extract Candidate Genes and Biological Associations.American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics · 2025
    Pooled it
  2. Systematic Analysis of Tumor Microenvironment Using IOBR.Methods in molecular biology (Clifton, N.J.) · 2027
    Article
  3. Article
  4. Review
  5. Identification of Changes in Gene Expression.Biometrical journal. Biometrische Zeitschrift · 2026
    Article
  6. Article
  7. Article
  8. Review
  9. Diffusion MRI reveals amyloid plaque-associated cellular signatures through spatial transcriptomic integration.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
  10. Article
  11. Article
  12. Review
  13. Gene-Based Clustering Identifies QSOX1 and IL1RAP as Biomarkers of Metabolic Dysfunction-Associated Steatotic Liver Disease.Liver international : official journal of the International Association for the Study of the Liver · 2026
    Article
  14. Article
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  18. Article
  19. Review
  20. Review

1,000 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Rory StarkCancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK.ORCID http://orcid.org/0000-0002-1790-5469
Marta GrzelakCancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK.ORCID http://orcid.org/0000-0002-2653-2895
James HadfieldPrecision Medicine, Oncology R&D, AstraZeneca, Cambridge, UK. James.hadfield@astrazeneca.com.ORCID http://orcid.org/0000-0001-9868-4989

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the past decade, RNA sequencing (RNA-seq) has become an indispensable tool for transcriptome-wide analysis of differential gene expression and differential splicing of mRNAs. However, as next-generation sequencing technologies have developed, so too has RNA-seq. Now, RNA-seq methods are available for studying many different aspects of RNA biology, including single-cell gene expression, translation (the translatome) and RNA structure (the structurome). Exciting new applications are being explored, such as spatial transcriptomics (spatialomics). Together with new long-read and direct RNA-seq technologies and better computational tools for data analysis, innovations in RNA-seq are contributing to a fuller understanding of RNA biology, from questions such as when and where transcription occurs to the folding and intermolecular interactions that govern RNA function.

Indexed as

Alternative SplicingGene Expression ProfilingHigh-Throughput Nucleotide SequencingHistory, 21st CenturyHumansRNA, MessengerSequence Analysis, RNARNA, Messenger

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.