Nature MethodsBioinformaticsPeer-reviewed journal article
Orthology inference at scale with FastOMA
Sina MajidianiD, Yannis NeversiD, Ali Yazdizadeh KharraziiD, Alex Warwick VesztrocyiD, Stefano PascarelliiD, David MoiiD, Natasha GloveriD, Adrian AltenhoffiD, Christophe DessimoziD
Abstract
The surge in genome data, with ongoing efforts aiming to sequence 1.5M eukaryotes in a decade, could revolutionise genomics, revealing the origins, evolution, and genetic innovations of biological processes. Yet, traditional genomics methods scale poorly with such large datasets. Addressing this, "FastOMA" provides linear scalability, enabling the processing of thousands of eukaryotic genomes within a day. FastOMA maintains the high accuracy and resolution of the well-established OMA approach in benchmarks. FastOMA is available at https://github.com/DessimozLab/FastOMA/.
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