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PAnno: A pharmacogenomics annotation tool for clinical genomic testing

Affiliation
State Key Laboratory of Genetic Engineering ,Human Phenome Institute ,School of Life Sciences and Shanghai Cancer Center ,Fudan University ,Shanghai ,China
Liu, Yaqing;
Affiliation
State Key Laboratory of Genetic Engineering ,Human Phenome Institute ,School of Life Sciences and Shanghai Cancer Center ,Fudan University ,Shanghai ,China
Lin, Zipeng;
Affiliation
State Key Laboratory of Genetic Engineering ,Human Phenome Institute ,School of Life Sciences and Shanghai Cancer Center ,Fudan University ,Shanghai ,China
Chen, Qingwang;
Affiliation
State Key Laboratory of Genetic Engineering ,Human Phenome Institute ,School of Life Sciences and Shanghai Cancer Center ,Fudan University ,Shanghai ,China
Chen, Qiaochu;
Affiliation
State Key Laboratory of Genetic Engineering ,Human Phenome Institute ,School of Life Sciences and Shanghai Cancer Center ,Fudan University ,Shanghai ,China
Sang, Leqing;
Affiliation
Department of Breast Surgery ,Precision Cancer Medicine Center ,Key Laboratory of Breast Cancer in Shanghai ,Fudan University Shanghai Cancer Center ,Shanghai ,China
Wang, Yunjin;
Affiliation
State Key Laboratory of Genetic Engineering ,Human Phenome Institute ,School of Life Sciences and Shanghai Cancer Center ,Fudan University ,Shanghai ,China
Shi, Leming;
Affiliation
State Key Laboratory of Multiphase Complex Systems ,Institute of Process Engineering ,Chinese Academy of Sciences ,Beijing ,China
Guo, Li;
Affiliation
State Key Laboratory of Genetic Engineering ,Human Phenome Institute ,School of Life Sciences and Shanghai Cancer Center ,Fudan University ,Shanghai ,China
Yu, Ying

Introduction: Next-generation sequencing (NGS) technologies have been widely used in clinical genomic testing for drug response phenotypes. However, the inherent limitations of short reads make accurate inference of diplotypes still challenging, which may reduce the effectiveness of genotype-guided drug therapy. Methods: An automated Pharmacogenomics Annotation tool (PAnno) was implemented, which reports prescribing recommendations and phenotypes by parsing the germline variant call format (VCF) file from NGS and the population to which the individual belongs. Results: A ranking model dedicated to inferring diplotypes, developed based on the allele (haplotype) definition and population allele frequency, was introduced in PAnno. The predictive performance was validated in comparison with four similar tools using the consensus diplotype data of the Genetic Testing Reference Materials Coordination Program (GeT-RM) as ground truth. An annotation method was proposed to summarize prescribing recommendations and classify drugs into avoid use, use with caution, and routine use, following the recommendations of the Clinical Pharmacogenetics Implementation Consortium (CPIC), etc. It further predicts phenotypes of specific drugs in terms of toxicity, dosage, efficacy, and metabolism by integrating the high-confidence clinical annotations in the Pharmacogenomics Knowledgebase (PharmGKB). PAnno is available at https://github.com/PreMedKB/PAnno . Discussion: PAnno provides an end-to-end clinical pharmacogenomics decision support solution by resolving, annotating, and reporting germline variants.

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License Holder: Copyright © 2023 Liu, Lin, Chen, Chen, Sang, Wang, Shi, Guo and Yu.

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