Evidence map›Paper›PMID 34749764›Full record

ArticleGenome biology2021

IRFinder-S: a comprehensive suite to discover and explore intron retention.

Claudio Lorenzi, Sylvain Barriere, Katharina Arnold, Reini F Luco, Andrew J Oldfield, William Ritchie

Abstract read
In one paragraph

Article in Genome biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

  1. Review
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  8. Long-Read Sequencing Reveals RNA Splicing Complexity in Human Diseases.Computational and structural biotechnology journal · 2026
    Review
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  15. U4 snRNP inhibits premature cleavage and polyadenylation of pre-mRNAs.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
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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

6 authors.

Claudio Lorenzi *Institut de Génétique Humaine, Centre National de la Recherche Scientifique (CNRS), Université de Montpellier, Montpellier, France.
Sylvain Barriere *Institut de Génétique Humaine, Centre National de la Recherche Scientifique (CNRS), Université de Montpellier, Montpellier, France.
Katharina ArnoldInstitut de Génétique Humaine, Centre National de la Recherche Scientifique (CNRS), Université de Montpellier, Montpellier, France.
Reini F LucoInstitut de Génétique Humaine, Centre National de la Recherche Scientifique (CNRS), Université de Montpellier, Montpellier, France.
Andrew J OldfieldInstitut de Génétique Humaine, Centre National de la Recherche Scientifique (CNRS), Université de Montpellier, Montpellier, France.
William RitchieInstitut de Génétique Humaine, Centre National de la Recherche Scientifique (CNRS), Université de Montpellier, Montpellier, France. william.ritchie@igh.cnrs.fr.ORCID 0000-0001-8162-1439

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate quantification and detection of intron retention levels require specialized software. Building on our previous software, we create a suite of tools called IRFinder-S, to analyze and explore intron retention events in multiple samples. Specifically, IRFinder-S allows a better identification of true intron retention events using a convolutional neural network, allows the sharing of intron retention results between labs, integrates a dynamic database to explore and contrast available samples, and provides a tested method to detect differential levels of intron retention.

Indexed as

Alternative SplicingIntronsSoftwareNeural Networks, ComputerSequence Analysis, RNAIntron retentionRNA sequencingSplicing efficiency

Identifiers

PMID34749764
PMCPMC8573998

What OpenQuestion holds

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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.