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CASAS: Cancer Survival Analysis Suite, a web based application

We present CASAS, a shiny R based tool for interactive survival analysis and visualization of results. The tool provides a web-based one stop shop to perform the following types of survival analysis:  quantile, landmark and competing risks, in addition to standard survival analysis.  The interface m...

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Detalles Bibliográficos
Autores principales: Rupji, Manali, Zhang, Xinyan, Kowalski, Jeanne
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000Research 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5580407/
https://www.ncbi.nlm.nih.gov/pubmed/28928946
http://dx.doi.org/10.12688/f1000research.11830.2
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author Rupji, Manali
Zhang, Xinyan
Kowalski, Jeanne
author_facet Rupji, Manali
Zhang, Xinyan
Kowalski, Jeanne
author_sort Rupji, Manali
collection PubMed
description We present CASAS, a shiny R based tool for interactive survival analysis and visualization of results. The tool provides a web-based one stop shop to perform the following types of survival analysis:  quantile, landmark and competing risks, in addition to standard survival analysis.  The interface makes it easy to perform such survival analyses and obtain results using the interactive Kaplan-Meier and cumulative incidence plots.  Univariate analysis can be performed on one or several user specified variable(s) simultaneously, the results of which are displayed in a single table that includes log rank p-values and hazard ratios along with their significance. For several quantile survival analyses from multiple cancer types, a single summary grid is constructed. The CASAS package has been implemented in R and is available via http://shinygispa.winship.emory.edu/CASAS/. The developmental repository is available at https://github.com/manalirupji/CASAS/.
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spelling pubmed-55804072017-09-18 CASAS: Cancer Survival Analysis Suite, a web based application Rupji, Manali Zhang, Xinyan Kowalski, Jeanne F1000Res Software Tool Article We present CASAS, a shiny R based tool for interactive survival analysis and visualization of results. The tool provides a web-based one stop shop to perform the following types of survival analysis:  quantile, landmark and competing risks, in addition to standard survival analysis.  The interface makes it easy to perform such survival analyses and obtain results using the interactive Kaplan-Meier and cumulative incidence plots.  Univariate analysis can be performed on one or several user specified variable(s) simultaneously, the results of which are displayed in a single table that includes log rank p-values and hazard ratios along with their significance. For several quantile survival analyses from multiple cancer types, a single summary grid is constructed. The CASAS package has been implemented in R and is available via http://shinygispa.winship.emory.edu/CASAS/. The developmental repository is available at https://github.com/manalirupji/CASAS/. F1000Research 2017-07-31 /pmc/articles/PMC5580407/ /pubmed/28928946 http://dx.doi.org/10.12688/f1000research.11830.2 Text en Copyright: © 2017 Rupji M et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software Tool Article
Rupji, Manali
Zhang, Xinyan
Kowalski, Jeanne
CASAS: Cancer Survival Analysis Suite, a web based application
title CASAS: Cancer Survival Analysis Suite, a web based application
title_full CASAS: Cancer Survival Analysis Suite, a web based application
title_fullStr CASAS: Cancer Survival Analysis Suite, a web based application
title_full_unstemmed CASAS: Cancer Survival Analysis Suite, a web based application
title_short CASAS: Cancer Survival Analysis Suite, a web based application
title_sort casas: cancer survival analysis suite, a web based application
topic Software Tool Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5580407/
https://www.ncbi.nlm.nih.gov/pubmed/28928946
http://dx.doi.org/10.12688/f1000research.11830.2
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