4.8 Article

Thunor: visualization and analysis of high-throughput dose-response datasets

Journal

NUCLEIC ACIDS RESEARCH
Volume 49, Issue W1, Pages W633-W640

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/nar/gkab424

Keywords

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Funding

  1. National Science Foundation [1411482, 1942255]
  2. National Cancer Institute [U01CA215845, U54CA217450, R50CA243783, K22CA237857]
  3. National Library of Medicine [5T15-LM007450-14]
  4. Defense Advanced Research Projects Agency [W911 NF-14-2-0022]
  5. Direct For Biological Sciences
  6. Div Of Molecular and Cellular Bioscience [1411482, 1942255] Funding Source: National Science Foundation

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Thunor is an open-source software platform designed to manage, analyze, and visualize large dose-dependent cell proliferation datasets. It supports both end-point and time-based proliferation assays, providing a user-friendly interface with interactive plots.
High-throughput cell proliferation assays to quantify drug-response are becoming increasingly common and powerful with the emergence of improved automation and multi-time point analysis methods. However, pipelines for analysis of these datasets that provide reproducible, efficient, and interactive visualization and interpretation are sorely lacking. To address this need, we introduce Thunor, an open-source software platform to manage, analyze, and visualize large, dose-dependent cell proliferation datasets. Thunor supports both end-point and time-based proliferation assays as input. It provides a simple, user-friendly interface with interactive plots and publication-quality images of cell proliferation time courses, dose-response curves, and derived dose-response metrics, e.g. IC50, including across datasets or grouped by tags. Tags are categorical labels for cell lines and drugs, used for aggregation, visualization and statistical analysis, e.g. cell line mutation or drug class/target pathway. A graphical plate map tool is included to facilitate plate annotation with cell lines, drugs and concentrations upon data upload. Datasets can be shared with other users via point-and-click access control. We demonstrate the utility of Thunor to examine and gain insight from two large drug response datasets: a large, publicly available cell viability database and an in-house, high-throughput proliferation rate dataset. Thunor is available from www.thunor.net.

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