Omni-ARMD: an integrated genomic and clinical knowledgebase bridging clinical phenotypes and molecular determinants of antimicrobial resistance
4 affiliations
- 1Zhongshan School of Medicine, Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University , Shenzhen, Guangdong 518107 ,
- 2Department of Clinical Laboratory, The Seventh Affiliated Hospital, Sun Yat-sen University , Shenzhen, Guangdong 518107 ,
- 3State Key Laboratory of Anti-Infective Drug Discovery and Development; School of Pharmaceutical Sciences, Sun Yat-sen University , Guangzhou, Guangdong 510006 ,
- 4Ministry of Education, Key Laboratory of Tropical Diseases Control (Sun Yat-sen University) , Guangzhou, Guangdong 510080 ,
Abstract
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.
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BibTeX
@article{tang2026omniarmd,
title = {{Omni-ARMD: an integrated genomic and clinical knowledgebase bridging clinical phenotypes and molecular determinants of antimicrobial resistance}},
author = {Hai Tang and Xiaoying Xie and Shikang Zheng and Lei Wang and Runtian Yao and Xin Ding and Guo-Bao Tian and Weizhong Li},
journal = {Nucleic Acids Research},
year = {2026},
month = oct,
doi = {10.1093/nar/gkag1045},
url = {https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag1045/9002506},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - Omni-ARMD: an integrated genomic and clinical knowledgebase bridging clinical phenotypes and molecular determinants of antimicrobial resistance
AU - Hai Tang
AU - Xiaoying Xie
AU - Shikang Zheng
AU - Lei Wang
AU - Runtian Yao
AU - Xin Ding
AU - Guo-Bao Tian
AU - Weizhong Li
PY - 2026
DA - 2026/10/27
JO - Nucleic Acids Research
DO - 10.1093/nar/gkag1045
UR - https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag1045/9002506
AB - 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.
SN - 0305-1048
SN - 1362-4962
ER -