Orthology inference at scale with FastOMA.

Détails

ID Serval
serval:BIB_16D2692F826F
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Orthology inference at scale with FastOMA.
Périodique
Nature methods
Auteur⸱e⸱s
Majidian S., Nevers Y., Yazdizadeh Kharrazi A., Warwick Vesztrocy A., Pascarelli S., Moi D., Glover N., Altenhoff A.M., Dessimoz C.
ISSN
1548-7105 (Electronic)
ISSN-L
1548-7091
Statut éditorial
Publié
Date de publication
02/2025
Peer-reviewed
Oui
Volume
22
Numéro
2
Pages
269-272
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: ppublish
Résumé
The surge in genome data, with ongoing efforts aiming to sequence 1.5 M eukaryotes in a decade, could revolutionize genomics, revealing the origins, evolution and genetic innovations of biological processes. Yet, traditional genomics methods scale poorly with such large datasets. Here, addressing this, 'FastOMA' provides linear scalability for orthology inference, enabling the processing of thousands of eukaryotic genomes within a day. FastOMA maintains the high accuracy and resolution of the well-established Orthologous Matrix (OMA) approach in benchmarks. FastOMA is available via GitHub at https://github.com/DessimozLab/FastOMA/ .
Mots-clé
Software, Genomics/methods, Algorithms, Humans, Genome, Computational Biology/methods
Pubmed
Web of science
Open Access
Oui
Création de la notice
09/01/2025 15:14
Dernière modification de la notice
15/02/2025 9:48
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