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SonicParanoid2: fast, accurate, and comprehensive orthology inference with machine learning and language models
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SonicParanoid2: fast, accurate, and comprehensive orthology inference with machine learning and language models
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Journal Article
SonicParanoid2: fast, accurate, and comprehensive orthology inference with machine learning and language models
2024
Overview
Accurate inference of orthologous genes constitutes a prerequisite for comparative and evolutionary genomics. SonicParanoid is one of the fastest tools for orthology inference; however, its scalability and accuracy have been hampered by time-consuming all-versus-all alignments and the existence of proteins with complex domain architectures. Here, we present a substantial update of SonicParanoid, where a gradient boosting predictor halves the execution time and a language model doubles the recall. Application to empirical large-scale and standardized benchmark datasets shows that SonicParanoid2 is much faster than comparable methods and also the most accurate. SonicParanoid2 is available at
https://gitlab.com/salvo981/sonicparanoid2
and
https://zenodo.org/doi/10.5281/zenodo.11371108
.
Publisher
BioMed Central,Springer Nature B.V,BMC
Subject
