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SynergyFinder Plus: Toward Better Interpretation and Annotation of Drug Combination Screening Datasets.
Zheng, Shuyu; Wang, Wenyu; Aldahdooh, Jehad; Malyutina, Alina; Shadbahr, Tolou; Tanoli, Ziaurrehman; Pessia, Alberto; Tang, Jing.
Afiliação
  • Zheng S; Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki 00290, Finland.
  • Wang W; Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki 00290, Finland.
  • Aldahdooh J; Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki 00290, Finland.
  • Malyutina A; Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki 00290, Finland.
  • Shadbahr T; Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki 00290, Finland.
  • Tanoli Z; Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki 00290, Finland.
  • Pessia A; Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki 00290, Finland.
  • Tang J; Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki 00290, Finland. Electronic address: jing.tang@helsinki.fi.
Genomics Proteomics Bioinformatics ; 20(3): 587-596, 2022 06.
Article em En | MEDLINE | ID: mdl-35085776
ABSTRACT
Combinatorial therapies have been recently proposed to improve the efficacy of anticancer treatment. The SynergyFinder R package is a software used to analyze pre-clinical drug combination datasets. Here, we report the major updates to the SynergyFinder R package for improved interpretation and annotation of drug combination screening results. Unlike the existing implementations, the updated SynergyFinder R package includes five main innovations. 1) We extend the mathematical models to higher-order drug combination data analysis and implement dimension reduction techniques for visualizing the synergy landscape. 2) We provide a statistical analysis of drug combination synergy and sensitivity with confidence intervals and P values. 3) We incorporate a synergy barometer to harmonize multiple synergy scoring methods to provide a consensus metric for synergy. 4) We evaluate drug combination synergy and sensitivity to provide an unbiased interpretation of the clinical potential. 5) We enable fast annotation of drugs and cell lines, including their chemical and target information. These annotations will improve the interpretation of the mechanisms of action of drug combinations. To facilitate the use of the R package within the drug discovery community, we also provide a web server at www.synergyfinderplus.org as a user-friendly interface to enable a more flexible and versatile analysis of drug combination data.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Modelos Teóricos Tipo de estudo: Diagnostic_studies / Prognostic_studies / Screening_studies Idioma: En Revista: Genomics Proteomics Bioinformatics Assunto da revista: BIOQUIMICA / GENETICA / INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Finlândia

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Modelos Teóricos Tipo de estudo: Diagnostic_studies / Prognostic_studies / Screening_studies Idioma: En Revista: Genomics Proteomics Bioinformatics Assunto da revista: BIOQUIMICA / GENETICA / INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Finlândia