DOE OSTI · code-168619
Accuracy-Based Annotation Quality Score (ABAQS) v1.0
Abstract
Assessing genome annotation quality is crucial for downstream analyses, but current methods are inadequate for eukaryotes. We present Accuracy-Based Annotation Quality Score (ABAQS), a novel, minimal-data-driven method that comprehensively assesses annotation quality. ABAQS evaluates multiple factors, including genome completeness, gene model validity, and protein profile accuracy, outperforming other metrics like BUSCO and PSAURON. We applied ABAQS to over 2500 eukaryotic genomes and showed its robustness and effectiveness in evaluating genome annotation quality, making it a valuable tool for researchers working with genomic data. ABAQS reveals significant variation in annotation quality and highlights the importance of filtering in improving annotation quality and accuracy.
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Haridas, Sajeet [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)], Salamov, Asaf [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)], Shabalov, Igor [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)], Liu, Ran [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); University of California, Berkeley, CA (United States)]. 2025-10-14. Accuracy-Based Annotation Quality Score (ABAQS) v1.0. https://doi.org/10.11578/dc.20251031.1
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