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Thunor: visualization and analysis of high-throughput dose–response datasets
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 v...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8265171/ https://www.ncbi.nlm.nih.gov/pubmed/34038546 http://dx.doi.org/10.1093/nar/gkab424 |
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author | Lubbock, Alexander L R Harris, Leonard A Quaranta, Vito Tyson, Darren R Lopez, Carlos F |
author_facet | Lubbock, Alexander L R Harris, Leonard A Quaranta, Vito Tyson, Darren R Lopez, Carlos F |
author_sort | Lubbock, Alexander L R |
collection | PubMed |
description | 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. IC(50), 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. |
format | Online Article Text |
id | pubmed-8265171 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-82651712021-07-09 Thunor: visualization and analysis of high-throughput dose–response datasets Lubbock, Alexander L R Harris, Leonard A Quaranta, Vito Tyson, Darren R Lopez, Carlos F Nucleic Acids Res Web Server Issue 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. IC(50), 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. Oxford University Press 2021-05-26 /pmc/articles/PMC8265171/ /pubmed/34038546 http://dx.doi.org/10.1093/nar/gkab424 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Web Server Issue Lubbock, Alexander L R Harris, Leonard A Quaranta, Vito Tyson, Darren R Lopez, Carlos F Thunor: visualization and analysis of high-throughput dose–response datasets |
title | Thunor: visualization and analysis of high-throughput dose–response datasets |
title_full | Thunor: visualization and analysis of high-throughput dose–response datasets |
title_fullStr | Thunor: visualization and analysis of high-throughput dose–response datasets |
title_full_unstemmed | Thunor: visualization and analysis of high-throughput dose–response datasets |
title_short | Thunor: visualization and analysis of high-throughput dose–response datasets |
title_sort | thunor: visualization and analysis of high-throughput dose–response datasets |
topic | Web Server Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8265171/ https://www.ncbi.nlm.nih.gov/pubmed/34038546 http://dx.doi.org/10.1093/nar/gkab424 |
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