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صفحه اصلی
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4th international edition and 13th Iranian Conference on Bioinformatics
Orthology inference at scale with FastOMA
نویسندگان :
Sina Majidian
1
Yannis Nevers
2
Ali Yazdizadeh Kharrazi
3
Christophe Dessimoz
4
1- John Hopkins University
2- University of Lausanne
3- University of Tehran
4- University of Lausanne
کلمات کلیدی :
Orthology،k-mers،Comparative Genomics
چکیده :
The unprecedented increase in genomic data, fueled by initiatives such as the Earth BioGenome Project, which aims to sequence 1.5 million eukaryotic genomes, holds immense potential to advance our understanding of evolution and biological diversity. However, traditional orthology inference methods, which identify genes of common ancestry across species, struggle to process datasets at this scale. We present FastOMA, a novel orthology inference tool that scales linearly with input size, enabling the analysis of thousands of genomes in under 24 hours with minimal computational resources. By combining k-mer-based clustering, taxonomy-guided subsampling, and efficient parallelization, FastOMA maintains high accuracy and recall, outperforming established orthology methods in benchmarks. FastOMA demonstrates remarkable precision on the Quest for Orthologs and SwissTree benchmarks and achieves low topological error in species tree comparisons, establishing it as a state-of-the-art solution for large-scale orthology inference. The tool’s flexibility with taxonomic inputs, robustness to phylogenetic errors, and compatibility with the OMA ecosystem provide an essential resource for researchers aiming to explore evolutionary patterns at unprecedented scales. FastOMA is available at https://github.com/DessimozLab/FastOMA/.
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