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Related Experiment Video

Updated: Jun 11, 2026

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Published on: December 22, 2017

AEGIS: an annotation extraction and genomic integration resource.

David Navarro-Payá¹, Antonio Santiago^1,2, Amandine Velt³

¹Institute for Integrative Systems Biology (I2SysBio, CSIC-UV), Valencia, 46980, Spain.

Bioinformatics (Oxford, England)

|June 9, 2026

Summary

Genome annotation files (GFF3/GTF) often have inconsistencies. AEGIS (Annotation Extraction and Genomic Integration Suite) is a new toolkit that parses, standardizes, and validates these files, enabling robust comparative genomics.

Related Experiment Videos

Last Updated: Jun 11, 2026

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Published on: December 22, 2017

Area of Science:

Bioinformatics
Genomics
Computational Biology

Background:

Genome annotation files (GFF3/GTF) are essential for genomic feature data storage.
Formatting inconsistencies in these files create bottlenecks for downstream bioinformatics analyses.
A unified framework is needed for parsing, standardizing, and validating genome annotations to ensure interoperability.

Purpose of the Study:

To present AEGIS (Annotation Extraction and Genomic Integration Suite), a toolkit for parsing, correcting, and standardizing genome annotations.
To provide advanced modules for feature extraction and comparative genomic analysis.
To integrate multiple lines of evidence for assessing gene model correspondence and inferring orthology.

Main Methods:

AEGIS is implemented in Python.
It offers modules for flexible feature extraction (e.g., coding sequences, promoters).
It integrates sequence homology, synteny, and coordinate-based lift-overs for orthology inference.

Main Results:

AEGIS quantifies structural changes between Arabidopsis annotation versions.
It identifies high-confidence orthologues across diverse plant genomes.
The toolkit facilitates robust comparative genomic tasks.

Conclusions:

AEGIS provides a comprehensive solution for genome annotation quality control and standardization.
It enables advanced comparative genomic analyses, including orthology inference.
The toolkit enhances interoperability and facilitates complex genomic tasks.