Evidence map›Paper›PMID 42262904›Full record

ArticleBioinformatics (Oxford, England)2026

AEGIS: an annotation extraction and genomic integration resource.

David Navarro-Payá, Antonio Santiago, Amandine Velt, Marco Moretto, Camille Rustenholz, José Tomás Matus

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2026. 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. Review
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.

David Navarro-PayáInstitute for Integrative Systems Biology (I2SysBio, CSIC-UV), Valencia, 46980, Spain.ORCID 0000-0003-1623-3039
Antonio SantiagoInstitute for Integrative Systems Biology (I2SysBio, CSIC-UV), Valencia, 46980, Spain.ORCID 0000-0002-9180-3241
Amandine VeltINRAE-Université de Strasbourg, SVQV, Colmar, 68000, France.
Marco MorettoUnit of Digital Agriculture, Research and Innovation Centre, Fondazione Edmund Mach, San Michele all'Adige, 38098, Italy.ORCID 0000-0003-4555-7243
Camille RustenholzINRAE-Université de Strasbourg, SVQV, Colmar, 68000, France.ORCID 0000-0001-5355-3408
José Tomás MatusInstitute for Integrative Systems Biology (I2SysBio, CSIC-UV), Valencia, 46980, Spain.ORCID 0000-0002-9196-1813

Funding

Agencia Estatal de InvestigaciónFondo Europeo de Desarrollo RegionalGeneralitat Valenciana (GVA)Grapedia COST innovators IEC-BG1-2023-4Grapedia COST innovators IG17111Institute for Catalan Studies (IEC)Metacell PID2024-163039NB-I00Ministerio de Ciencia, Innovación y UniversidadesPROMETEO PROMETEO/2021/056-01Valinet PID2021-128865NB-I00
6 · The paper itself

Abstract

motivationGenome annotation files (GFF3/GTF) are the standard for storing genomic feature data, yet their flexibility often results in formatting inconsistencies that create bottlenecks for downstream bioinformatics analyses. A robust, unified framework is required to parse, standardise, and validate these files to ensure interoperability and facilitate complex comparative genomic tasks.

resultsWe present AEGIS (Annotation Extraction and Genomic Integration Suite), a comprehensive toolkit designed to parse, correct, and standardise genome annotations. Beyond quality control, AEGIS provides advanced modules for flexible feature extraction (e.g., coding sequences, promoters) and comparative genomic analysis. Uniquely, it integrates multiple lines of evidence, including sequence homology, synteny, and coordinate-based lift-overs, to assess gene model correspondence and infer orthology. We demonstrate the utility of AEGIS by quantifying complex structural changes between Arabidopsis annotation versions and identifying high-confidence orthologues across diverse plant genomes. AVAILABILITY: AEGIS is implemented in Python. Source code and documentation are freely available under the GPL-3 license at https://github.com/Tomsbiolab/aegis and as a Docker container at https://hub.docker.com/r/tomsbiolab/aegis. The package is also available on PyPI (pip install aegis-bio).

Indexed as

Genome, PlantGenomicsMolecular Sequence AnnotationSoftwareArabidopsis

Identifiers

PMID42262904
PMCPMC13296998

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.