Omni-ARMD: an integrated genomic and clinical knowledgebase bridging clinical phenotypes and molecular determinants of antimicrobial resistance
Antimicrobial resistance (AMR) is a major global health threat, yet its molecular determinants remain difficult to characterize in real-world settings, as genomic and clinical data are fragmented across resources. Existing databases typically separate gene-level mechanisms, curated genotype-phenotype associations, and large-scale clinical antimicrobial susceptibility testing (AST) data, limiting cross-scale interpretation. Here, we present Omni-ARMD, an open-access knowledgebase that integrates multi-source genomic and clinical data to systematically infer genotype-phenotype relationships in AMR. Omni-ARMD bridges large-scale clinical AST records and gene-level resistance evidence through a confidence-weighted log-odds enrichment framework, which quantifies genotype-phenotype associations at the organism-antimicrobial level and integrates these associations into aggregated cross-domain evidence representations. The current release includes over 12 million de-identified microbiology records from more than 1 million patients, harmonized to generate over 7.83 million standardized AST records. It also integrates over 0.36 million gene-phenotype associations, spanning 38 organisms, 52 antimicrobials, and 375 resistance genes. Omni-ARMD links over 5.16 million clinical records to genomic evidence, achieving a 65.86% match rate and a 2.61% coverage of organism-antimicrobial pairs. Omni-ARMD provides interactive modules for clinical investigation, genomic evidence analysis, mechanistic interpretation, and artificial intelligence-assisted exploration, enabling integrative and data-driven discovery in AMR. Omni-ARMD is freely available at www.omniarmd.cn.
Authors
- Hai Tang (ORCID: https://orcid.org/0000-0002-8608-692X)
- Shikang Zheng (ORCID: https://orcid.org/0009-0002-9170-9535)
- Xiaoying Xie (ORCID: https://orcid.org/0000-0002-6113-6505)
- Guo‐Bao Tian (ORCID: https://orcid.org/0000-0001-6750-5482)
- Xin Ding (ORCID: https://orcid.org/0000-0002-5982-8799)
- Weizhong Li (ORCID: https://orcid.org/0000-0002-9003-7733)
- Runtian Yao (ORCID: https://orcid.org/0009-0006-5483-3667)
- Lei Wang (ORCID: https://orcid.org/0009-0003-6483-5568)
Institutions
- Sun Yat-sen University (CN)
- The Seventh Affiliated Hospital of Sun Yat-sen University (CN)
Publication Details
- Journal
- Nucleic Acids Research
- Published
- 2026-10-27
- DOI
- https://doi.org/10.1093/nar/gkag1045
- Primary Topic
- Antibiotic Resistance in Bacteria
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China