SELDESCRIP V1.0: aplicación web para la selección de descriptores en bancos de germoplasma vegetal
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Resumen
El objetivo de este trabajo fue crear una Interfaz gráfica en R con Shiny que facilite realizar la selección de descriptores en bancos de Germoplasma Vegetal. Para conseguir este objetivo se recurre al uso de métodos de selección de variables y de herramientas de inteligencia artificial y estadísticas en el Software R. Esta interfaz tendrá potencialidad e independencia al ser este un lenguaje con entorno de programación libre. Además, permite a los usuarios interactuar con sus datos sin tener que manipular el código.
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Cómo citar
Molina Concepción, O., Peña Ángel, A., Guillen López, Y., & Pons Pérez, C. C. (2022). SELDESCRIP V1.0: aplicación web para la selección de descriptores en bancos de germoplasma vegetal. Agricultura Tropical, 8(1), 25–37. Recuperado a partir de https://agriculturatropical.edicionescervantes.com/index.php/inivit/article/view/198
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Artículos originales
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BEELEY, C. 2013. Web Application Development with R Using Shiny. Olton: Packt Publishing Ltd, first edition.
BEELEY, C. and SUKHDEVE, S. R. 2018. Web Application Development with R Using Shiny. Birmingham UK: Packt Publishing.
CISTERNA, A.; GONZÁLEZ-VIDAL, A.; RUIZ, D.; ORTIZ, J.; GÓMEZ-PASCUAL, A.; CHEN, Z. and BOTÍA, J. A. 2021. PhenoExam: an R package and Web application for the examination of phenotypes linked to genes and gene sets. bioRxiv. https://doi.org/10.1101/2021.06.29.450324.
CHANG, W.; CHENG, J.; ALLAIRE, J.J.; XIE, Y. and MCPHERSON, J. 2020. Shiny: Web Application Framework for R. R package version 1.5. Retrieved Jul. 20, 2020. Available at CRAN.R-project.org/package=shiny.
DWIVEDI, B. AND KOWALSKI, J. 2018. shinyGISPA: A web application for characterizing
phenotype by gene sets using multiple omics data combinations. PLoS ONE, 13
(2). ISSN 1932-6203. doi: 10.1371/journal.pone.0192563.
LI, J.; CUI, B.; DAI, Y.; BAI, L. and HUANG, J. 2018. BioInstaller: A comprehensive R package to construct interactive and reproducible biological data analysis applications based on the R platform. PeerJ, 6, ISSN 2167-8359. doi: 10.7717/peerj.5853.
Elliott, M.S. and Elliott, L.M. 2020. Developing R Shiny Web Applications for Extension Education, Applied Economics Teaching Resources (AETR), Agricultural and Applied Economics Association, vol. 2(4).
LANDAU, S. and Everitt, B. 2004. A Handbook of Statistical Analyses Using SPSS. Chapman &Hall/CRC, Boca Raton. ISBN 978-1-58488-369-2.
LIHUA, J.; WEN, Y.; YINGRU, J.; YANG, L.; ZHIZHAN, W.; HAORAN, L.; FANGFANG H.; JIAMING, L.; TIANTIAN, C. and HUIYONG, Z. 2022. Development of interactive biological web applications with R/Shiny, Briefings in Bioinformatics, 23(1), https://doi.org/10.1093/bib/bbab415.
MOLER, C. and MATHWORKS. 2012. MATLAB 8.0 and Statistics Toolbox 8.1. The MathWorks, Inc.
NIJS, V. 2020. Radiant: Business Analytics using R and Shiny. R package version 1.3.2. Retrieved Jul. 21, 2020. Available at CRAN.R-project.org/package=radiant
R CORE TEAM. 2021. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Available online at https://www.R-project.org/
SALAS, C. 2008. ¿Por qué comprar un programa estadístico si existe R? Ecología Austral, 18: 223-231.
Satyahadewi, N. and Perdana, H. 2021. Web Application Development for Inferential Statistics using R Shiny. Proceedings of the 1st International Conference on Mathematics and Mathematics Education (ICMMEd 2020).
WEIGELT, P.; DENELLE, P.; BRAMBACH, F. and KREFT, H. 2021. BotanizeR: A flexible R package with Shiny app to practice plant identification for online teaching and beyond. Plants, People, Planet.