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PredictABEL: an R package for the assessment of risk prediction models
The rapid identification of genetic markers for multifactorial diseases from genome-wide association studies is fuelling interest in investigating the predictive ability and health care utility of genetic risk models. Various measures are available for the assessment of risk prediction models, each...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3088798/ https://www.ncbi.nlm.nih.gov/pubmed/21431839 http://dx.doi.org/10.1007/s10654-011-9567-4 |
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author | Kundu, Suman Aulchenko, Yurii S. van Duijn, Cornelia M. Janssens, A. Cecile J. W. |
author_facet | Kundu, Suman Aulchenko, Yurii S. van Duijn, Cornelia M. Janssens, A. Cecile J. W. |
author_sort | Kundu, Suman |
collection | PubMed |
description | The rapid identification of genetic markers for multifactorial diseases from genome-wide association studies is fuelling interest in investigating the predictive ability and health care utility of genetic risk models. Various measures are available for the assessment of risk prediction models, each addressing a different aspect of performance and utility. We developed PredictABEL, a package in R that covers descriptive tables, measures and figures that are used in the analysis of risk prediction studies such as measures of model fit, predictive ability and clinical utility, and risk distributions, calibration plot and the receiver operating characteristic plot. Tables and figures are saved as separate files in a user-specified format, which include publication-quality EPS and TIFF formats. All figures are available in a ready-made layout, but they can be customized to the preferences of the user. The package has been developed for the analysis of genetic risk prediction studies, but can also be used for studies that only include non-genetic risk factors. PredictABEL is freely available at the websites of GenABEL (http://www.genabel.org) and CRAN (http://cran.r-project.org/). |
format | Text |
id | pubmed-3088798 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-30887982011-06-06 PredictABEL: an R package for the assessment of risk prediction models Kundu, Suman Aulchenko, Yurii S. van Duijn, Cornelia M. Janssens, A. Cecile J. W. Eur J Epidemiol Methods The rapid identification of genetic markers for multifactorial diseases from genome-wide association studies is fuelling interest in investigating the predictive ability and health care utility of genetic risk models. Various measures are available for the assessment of risk prediction models, each addressing a different aspect of performance and utility. We developed PredictABEL, a package in R that covers descriptive tables, measures and figures that are used in the analysis of risk prediction studies such as measures of model fit, predictive ability and clinical utility, and risk distributions, calibration plot and the receiver operating characteristic plot. Tables and figures are saved as separate files in a user-specified format, which include publication-quality EPS and TIFF formats. All figures are available in a ready-made layout, but they can be customized to the preferences of the user. The package has been developed for the analysis of genetic risk prediction studies, but can also be used for studies that only include non-genetic risk factors. PredictABEL is freely available at the websites of GenABEL (http://www.genabel.org) and CRAN (http://cran.r-project.org/). Springer Netherlands 2011-03-24 2011 /pmc/articles/PMC3088798/ /pubmed/21431839 http://dx.doi.org/10.1007/s10654-011-9567-4 Text en © The Author(s) 2011 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. |
spellingShingle | Methods Kundu, Suman Aulchenko, Yurii S. van Duijn, Cornelia M. Janssens, A. Cecile J. W. PredictABEL: an R package for the assessment of risk prediction models |
title | PredictABEL: an R package for the assessment of risk prediction models |
title_full | PredictABEL: an R package for the assessment of risk prediction models |
title_fullStr | PredictABEL: an R package for the assessment of risk prediction models |
title_full_unstemmed | PredictABEL: an R package for the assessment of risk prediction models |
title_short | PredictABEL: an R package for the assessment of risk prediction models |
title_sort | predictabel: an r package for the assessment of risk prediction models |
topic | Methods |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3088798/ https://www.ncbi.nlm.nih.gov/pubmed/21431839 http://dx.doi.org/10.1007/s10654-011-9567-4 |
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