Evidence map›Paper›PMID 41347231›Full record

ArticleNAR genomics and bioinformatics2025

Isoformic: a workflow for transcript-level RNA-seq interpretation.

Izabela Mamede, Lucio R Queiroz, Carlos Mata-Machado, Júlia Teixeira Rodrigues, Thomaz Luscher-Dias, Nayara E de Toledo, Paulo P Amaral, Luigi Marchionni, Gloria R Franco

Abstract read
In one paragraph

Article in NAR genomics and bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

9 authors.

Izabela MamedeLaboratory of Genetics Biochemistry, Departamento de Bioquímica e Imunologia, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais 31270-901, Brazil.ORCID https://orcid.org/0000-0002-0707-5588
Lucio R QueirozLaboratory of Genetics Biochemistry, Departamento de Bioquímica e Imunologia, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais 31270-901, Brazil.
Carlos Mata-MachadoLaboratory of Genetics Biochemistry, Departamento de Bioquímica e Imunologia, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais 31270-901, Brazil.
Júlia Teixeira RodriguesLaboratory for Macromolecular Biophysics, Departamento de Bioquímica e Imunologia, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais 31270-901, Brazil.
Thomaz Luscher-DiasLaboratory of Genetics Biochemistry, Departamento de Bioquímica e Imunologia, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais 31270-901, Brazil.ORCID https://orcid.org/0000-0002-3161-8888
Nayara E de ToledoLaboratory of Genetics Biochemistry, Departamento de Bioquímica e Imunologia, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais 31270-901, Brazil.
Paulo P AmaralInstituto de Ensino e Pesquisa INSPER, São Paulo, SP 04546-042, Brazil.
Luigi MarchionniDepartment of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, United States.ORCID https://orcid.org/0000-0002-7336-8071
Gloria R FrancoLaboratory of Genetics Biochemistry, Departamento de Bioquímica e Imunologia, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais 31270-901, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transcriptome analysis is one of the bases of modern biology, yet it is typically performed at the gene level, ignoring the complexity of alternative splicing and differential transcription initiation/termination events. Over 95% of mammalian genes produce multiple transcripts, yet most RNA-seq analyses rely on short-read data, for which transcript-level interpretation remains challenging. Current tools suffer from low accuracy, inconsistency with annotations, and lack quick solutions for downstream biological interpretation. Here, we present Isoformic, a customizable R pipeline for transcript-level analysis of short-read RNA-seq data, available on GitHub. Isoformic processes differential expression results to detect genes with transcript-level changes, visualize exon-intron structures, and perform functional enrichment stratified by transcript type. Validated on diverse datasets, including preeclampsia, SARS-CoV-2 infection, and murine anxiety models, Isoformic reveals biologically relevant transcript variants and their possible phenotypic associations. Compatible with GENCODE reference transcriptome, Isoformic enhances the resolution of RNA-seq studies, enabling researchers to uncover the regulatory roles of alternative transcription events.

Indexed as

Gene Expression ProfilingRNA-SeqSequence Analysis, RNASoftwareTranscriptomeAlternative SplicingAnimalsCOVID-19FemaleHumansMicePre-EclampsiaPregnancySARS-CoV-2Workflow

Identifiers

PMID41347231
PMCPMC12673842

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.