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shinyCurves, a shiny web application to analyse multisource qPCR amplification data: a COVID‑19 case study
dc.contributor.author | Olaechea Lázaro, Sonia | |
dc.contributor.author | García Santisteban, Iraia ![]() | |
dc.contributor.author | Pineda Martí, José Ramón ![]() | |
dc.contributor.author | Badiola Echaburu, Iker | |
dc.contributor.author | Alonso Alegre, Santos ![]() | |
dc.contributor.author | Bilbao Catalá, José Ramón | |
dc.contributor.author | Fernández Jiménez, Nora ![]() | |
dc.date.accessioned | 2021-11-22T09:28:05Z | |
dc.date.available | 2021-11-22T09:28:05Z | |
dc.date.issued | 2021-10-03 | |
dc.identifier.citation | BMC Bioinformatics 22(1) : (2021) / Article ID 476 | es_ES |
dc.identifier.issn | 1471-2105 | |
dc.identifier.uri | http://hdl.handle.net/10810/53917 | |
dc.description.abstract | [EN]Background Quantitative, reverse transcription PCR (qRT-PCR) is currently the gold-standard for SARS-CoV-2 detection and it is also used for detection of other virus. Manual data analysis of a small number of qRT-PCR plates per day is a relatively simple task, but automated, integrative strategies are needed if a laboratory is dealing with hundreds of plates per day, as is being the case in the COVID-19 pandemic. Results Here we present shinyCurves, an online shiny-based, free software to analyze qRT-PCR amplification data from multi-plate and multi-platform formats. Our shiny application does not require any programming experience and is able to call samples Positive, Negative or Undetermined for viral infection according to a number of user-defined settings, apart from providing a complete set of melting and amplification curve plots for the visual inspection of results. Conclusions shinyCurves is a flexible, integrative and user-friendly software that speeds-up the analysis of massive qRT-PCR data from different sources, with the possibility of automatically producing and evaluating melting and amplification curve plots. | es_ES |
dc.description.sponsorship | This project was supported by funding from the UPV/EHU (Accion Especial "Desarrollo e implementacion del test de diagnostico para COVID-19"). The funding body did not play any roles in the study design; nor in the data collection, analysis and interpretation, or in the writing of the paper. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | BMC | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.subject | diagnosis | es_ES |
dc.subject | qRT‑PCR | es_ES |
dc.subject | melting and amplification curves | es_ES |
dc.subject | COVID‑19 | es_ES |
dc.subject | data analysis | es_ES |
dc.subject | medical informatics | es_ES |
dc.subject | virology | es_ES |
dc.subject | shiny application | es_ES |
dc.title | shinyCurves, a shiny web application to analyse multisource qPCR amplification data: a COVID‑19 case study | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.holder | © The Author(s), 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the mate‑ rial. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data | es_ES |
dc.rights.holder | Atribución 3.0 España | * |
dc.relation.publisherversion | https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-021-04392-1 | es_ES |
dc.identifier.doi | 10.1186/s12859-021-04392-1 | |
dc.departamentoes | Biología celular e histología | es_ES |
dc.departamentoes | Genética, antropología física y fisiología animal | es_ES |
dc.departamentoeu | Biologia zelularra eta morfologia zientziak | es_ES |
dc.departamentoeu | Genetika,antropologia fisikoa eta animalien fisiologia | es_ES |
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Bestelakorik adierazi ezean, itemaren baimena horrela deskribatzen da:© The Author(s), 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits
use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original
author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third
party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the mate‑
rial. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or
exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://
creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco mmons. org/ publi
cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data