Journal
GENOMICS PROTEOMICS & BIOINFORMATICS
Volume 20, Issue 3, Pages 587-596Publisher
ELSEVIER
DOI: 10.1016/j.gpb.2022.01.004
Keywords
SynergyFinder; Drug combination; Synergy modeling; Drug discovery; Drug combination sensitivity; analysis
Categories
Funding
- European Research Council (ERC) starting grant DrugComb (informatics approaches for the rational selection of personalized cancer drug combinations) [716063]
- European Commission H2020 EOSC-life (providing an open collaborative space for digital biology in Europe) [824087]
- Academy of Finland [317680]
- Sigrid Juse lius Foundation grant
- University of Helsinki through the Doctoral Program of Biomedicine (DPBM)
- K. Albin Johanssons Stiftelse
- Biomedicum Helsinki Foundation
- University of Helsinki through the Doctoral Program of Integrative Life Science (ILS)
- Cancer Foundation Finland
- Academy of Finland (AKA) [317680] Funding Source: Academy of Finland (AKA)
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The SynergyFinder R package is a software that analyzes drug combination data, offering features such as high-order data analysis, statistical analysis, evaluation of synergy, and fast annotation. It provides improved interpretation and annotation of drug combination screening results.
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.s ynergyfinderplus.org as a user-friendly interface to enable a more flexible and versatile analysis of drug combination data.
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