Easyreporting simplifies the implementation of Reproducible Research layers in R software.

During last years "irreproducibility" became a general problem in omics data analysis due to the use of sophisticated and poorly described computational procedures. For avoiding misleading results, it is necessary to inspect and reproduce the entire data analysis as a unified product. Repr...

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Main Authors: Dario Righelli, Claudia Angelini
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2021-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0244122
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spelling doaj-64b88bb12ed74a14836b49e972f18c492021-05-28T04:30:57ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-01165e024412210.1371/journal.pone.0244122Easyreporting simplifies the implementation of Reproducible Research layers in R software.Dario RighelliClaudia AngeliniDuring last years "irreproducibility" became a general problem in omics data analysis due to the use of sophisticated and poorly described computational procedures. For avoiding misleading results, it is necessary to inspect and reproduce the entire data analysis as a unified product. Reproducible Research (RR) provides general guidelines for public access to the analytic data and related analysis code combined with natural language documentation, allowing third-parties to reproduce the findings. We developed easyreporting, a novel R/Bioconductor package, to facilitate the implementation of an RR layer inside reports/tools. We describe the main functionalities and illustrate the organization of an analysis report using a typical case study concerning the analysis of RNA-seq data. Then, we show how to use easyreporting in other projects to trace R functions automatically. This latter feature helps developers to implement procedures that automatically keep track of the analysis steps. Easyreporting can be useful in supporting the reproducibility of any data analysis project and shows great advantages for the implementation of R packages and GUIs. It turns out to be very helpful in bioinformatics, where the complexity of the analyses makes it extremely difficult to trace all the steps and parameters used in the study.https://doi.org/10.1371/journal.pone.0244122
collection DOAJ
language English
format Article
sources DOAJ
author Dario Righelli
Claudia Angelini
spellingShingle Dario Righelli
Claudia Angelini
Easyreporting simplifies the implementation of Reproducible Research layers in R software.
PLoS ONE
author_facet Dario Righelli
Claudia Angelini
author_sort Dario Righelli
title Easyreporting simplifies the implementation of Reproducible Research layers in R software.
title_short Easyreporting simplifies the implementation of Reproducible Research layers in R software.
title_full Easyreporting simplifies the implementation of Reproducible Research layers in R software.
title_fullStr Easyreporting simplifies the implementation of Reproducible Research layers in R software.
title_full_unstemmed Easyreporting simplifies the implementation of Reproducible Research layers in R software.
title_sort easyreporting simplifies the implementation of reproducible research layers in r software.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2021-01-01
description During last years "irreproducibility" became a general problem in omics data analysis due to the use of sophisticated and poorly described computational procedures. For avoiding misleading results, it is necessary to inspect and reproduce the entire data analysis as a unified product. Reproducible Research (RR) provides general guidelines for public access to the analytic data and related analysis code combined with natural language documentation, allowing third-parties to reproduce the findings. We developed easyreporting, a novel R/Bioconductor package, to facilitate the implementation of an RR layer inside reports/tools. We describe the main functionalities and illustrate the organization of an analysis report using a typical case study concerning the analysis of RNA-seq data. Then, we show how to use easyreporting in other projects to trace R functions automatically. This latter feature helps developers to implement procedures that automatically keep track of the analysis steps. Easyreporting can be useful in supporting the reproducibility of any data analysis project and shows great advantages for the implementation of R packages and GUIs. It turns out to be very helpful in bioinformatics, where the complexity of the analyses makes it extremely difficult to trace all the steps and parameters used in the study.
url https://doi.org/10.1371/journal.pone.0244122
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