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Curated sequences, alignments, and phylogenies for exploring IFNλ diversity across vertebrates.
Interferon lambda (IFNλ) genes are multi-copy, rapidly evolving, and prone to recombination, making them difficult to align and analyse reproducibly. Misaligned datasets have contributed to controversies in their evolutionary history.
IFNL-Evolution addresses this challenge by providing a curated, open, and reproducible framework. Using GLUE’s reference-constrained alignment system, the resource enforces standardisation across datasets while retaining flexibility for new data. Combined with phylogenetic structure, functional annotations, and a Dockerised environment, IFNL-Evolution enables reproducible evolutionary analyses and collaborative refinement of alignments.
IFNλ biology
IFNλs (IFNλ1–4) mediate antiviral defence at epithelial surfaces. Their restricted receptor distribution enables localised immunity with limited inflammation. Variation in IFNλs has been linked to infection outcomes and treatment responses, making their diversity of biomedical relevance.
GLUE framework
GLUE is an open toolkit for sequence data management and comparative genomics. GLUE projects integrate sequences, multiple alignments, gene annotations, and metadata within a relational database. IFNL-Evolution applies this framework to interferon lambda genes.
- Curated database: Comprehensive set of IFNλ sequences with metadata.
- Reference-constrained alignments: Standardised, reproducible comparisons across taxa.
- Phylogenetic framework: Structured exploration of IFNλ diversity.
- Functional annotations: Motifs, structural elements, and receptor-binding sites.
- Dockerised reproducibility: All analyses (phylogenies, glycosylation scanning, entropy measures, selection tests) are reproducible via containerised workflows.
With IFNL-Evolution you can:
- Explore IFNλ diversity across vertebrate genomes.
- Reproduce alignments and phylogenies underlying published analyses.
- Map sequence variation onto protein structures.
- Compare results across studies in a standardised framework.
- Extend the resource with new sequences or analyses.
For installation and usage guides, see the Requirements, Docker Installation, and Usage Overview pages in this Wiki.
We welcome contributions from the community! Please see our Contribution Guidelines.
Licensed under the GNU Affero General Public License v3.0.
- Issues and feature requests: GitHub issue tracker