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ASGARD is A Single-cell Guided Pipeline to Aid Repurposing of Drugs.
He, Bing; Xiao, Yao; Liang, Haodong; Huang, Qianhui; Du, Yuheng; Li, Yijun; Garmire, David; Sun, Duxin; Garmire, Lana X.
  • He B; Department of Computational Medicine and Bioinformatics, Medical School, University of Michigan, Ann Arbor, MI, USA.
  • Xiao Y; Department of Computational Medicine and Bioinformatics, Medical School, University of Michigan, Ann Arbor, MI, USA.
  • Liang H; Department of Statistics, College of Literature, Science, and the Arts, University of Michigan, Ann Arbor, MI, USA.
  • Huang Q; Department of Computational Medicine and Bioinformatics, Medical School, University of Michigan, Ann Arbor, MI, USA.
  • Du Y; Department of Computational Medicine and Bioinformatics, Medical School, University of Michigan, Ann Arbor, MI, USA.
  • Li Y; Department of Computational Medicine and Bioinformatics, Medical School, University of Michigan, Ann Arbor, MI, USA.
  • Garmire D; Department of Electrical Engineering and Computer Science, College of Engineering, University of Michigan, Ann Arbor, MI, USA.
  • Sun D; Department of Pharmaceutical Sciences, College of Pharmacy, University of Michigan, Ann Arbor, MI, USA.
  • Garmire LX; Department of Computational Medicine and Bioinformatics, Medical School, University of Michigan, Ann Arbor, MI, USA. lgarmire@med.umich.edu.
Nat Commun ; 14(1): 993, 2023 02 22.
Article in English | MEDLINE | ID: covidwho-2296306
ABSTRACT
Single-cell RNA sequencing technology has enabled in-depth analysis of intercellular heterogeneity in various diseases. However, its full potential for precision medicine has yet to be reached. Towards this, we propose A Single-cell Guided Pipeline to Aid Repurposing of Drugs (ASGARD) that defines a drug score to recommend drugs by considering all cell clusters to address the intercellular heterogeneity within each patient. ASGARD shows significantly better average accuracy on single-drug therapy compared to two bulk-cell-based drug repurposing methods. We also demonstrated that it performs considerably better than other cell cluster-level predicting methods. In addition, we validate ASGARD using the drug response prediction method TRANSACT with Triple-Negative-Breast-Cancer patient samples. We find that many top-ranked drugs are either approved by the Food and Drug Administration or in clinical trials treating corresponding diseases. In conclusion, ASGARD is a promising drug repurposing recommendation tool guided by single-cell RNA-seq for personalized medicine. ASGARD is free for educational use at https//github.com/lanagarmire/ASGARD .
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Precision Medicine / Drug Repositioning Type of study: Prognostic study Limits: Humans Language: English Journal: Nat Commun Journal subject: Biology / Science Year: 2023 Document Type: Article Affiliation country: S41467-023-36637-3

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Precision Medicine / Drug Repositioning Type of study: Prognostic study Limits: Humans Language: English Journal: Nat Commun Journal subject: Biology / Science Year: 2023 Document Type: Article Affiliation country: S41467-023-36637-3