Evidence map›Paper›PMID 36869033›Full record

ArticleNature communications2023

RNA splicing analysis using heterogeneous and large RNA-seq datasets.

Jorge Vaquero-Garcia, Joseph K Aicher, San Jewell, Matthew R Gazzara, Caleb M Radens, Anupama Jha, Scott S Norton, Nicholas F Lahens, Gregory R Grant, Yoseph Barash

Abstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 84 papers.

0numbers the graph read from it
0cells of the map it votes in
84citing papers in PubMed
–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

84 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
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  14. Article
  15. Article
  16. Role of alternative splicing in cancer progression.Irish journal of medical science · 2026
    Review
  17. Article
  18. Haematologica · 2026
    Article
  19. Article
  20. Article

24 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

10 authors.

Jorge Vaquero-Garcia *Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA.
Joseph K Aicher *Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0001-8850-6070
San Jewell *Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA.
Matthew R Gazzara *Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0001-7710-4551
Caleb M RadensDepartment of Genetics, University of Pennsylvania, Philadelphia, PA, USA.
Anupama JhaDepartment of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, USA.
Scott S NortonDepartment of Genetics, University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0002-1366-0628
Nicholas F LahensInstitute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0002-3965-5624
Gregory R GrantDepartment of Genetics, University of Pennsylvania, Philadelphia, PA, USA.
Yoseph BarashDepartment of Genetics, University of Pennsylvania, Philadelphia, PA, USA. yosephb@upenn.edu.ORCID 0000-0003-3005-5048

Funding

PREDOCTORAL TRAINING PROGRAM IN GENETICST32GM008216 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI EPSTEIN, DOUGLAS J · 1987 to 2023
$8.3M
Methods for RNA splicing variations detection, quantification, visualization, and association from large heterogeneous datasetsR01GM128096 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI BARASH, YOSEPH · 2018 to 2021
$1.8M
Modeling Splicing in normal tissues and neurodegenerative diseaseR01AG046544 · NIA · UNIVERSITY OF PENNSYLVANIA · PI BARASH, YOSEPH · 2014 to 2018
$1.6M
Methods for improving clinical diagnostic by detection, prediction, interpretation and prioritization of aberrant transcriptome variationsR01LM013437 · NLM · UNIVERSITY OF PENNSYLVANIA · PI BARASH, YOSEPH · 2020 to 2023
$1.4M
Enhancing molecular diagnosis in children with multiple congenital anomalies using clinically focused splicing prediction algorithmsF30HD098803 · NICHD · UNIVERSITY OF PENNSYLVANIA · PI AICHER, JOSEPH KRITTAMETH · 2019 to 2021
$152k
Mechanisms and consequences of 3'UTR isoform diversity in erythropoiesisF31HL162546 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI GAZZARA, MATTHEW ROBERT · 2022 to 2024
$136k
NHLBI NIH HHS F31 HL162546NIA NIH HHS R01 AG046544NICHD NIH HHS F30 HD098803NIGMS NIH HHS R01 GM128096NIGMS NIH HHS T32 GM008216NLM NIH HHS R01 LM013437
6 · The paper itself

Abstract

The ubiquity of RNA-seq has led to many methods that use RNA-seq data to analyze variations in RNA splicing. However, available methods are not well suited for handling heterogeneous and large datasets. Such datasets scale to thousands of samples across dozens of experimental conditions, exhibit increased variability compared to biological replicates, and involve thousands of unannotated splice variants resulting in increased transcriptome complexity. We describe here a suite of algorithms and tools implemented in the MAJIQ v2 package to address challenges in detection, quantification, and visualization of splicing variations from such datasets. Using both large scale synthetic data and GTEx v8 as benchmark datasets, we assess the advantages of MAJIQ v2 compared to existing methods. We then apply MAJIQ v2 package to analyze differential splicing across 2,335 samples from 13 brain subregions, demonstrating its ability to offer insights into brain subregion-specific splicing regulation.

Indexed as

AlgorithmsRNA SplicingBrainRNA-Seq

Identifiers

PMID36869033
PMCPMC9984406

What OpenQuestion holds

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Registered trials

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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.