OmniReprodubileCellAnalysis: a comprehensive toolbox for the analysis of cellular biology data

Open science and reproducibility are two key pillars of modern scientific research. Open science is making scientific research and data accessible and transparent to the broader scientific community and the public. Reproducibility, on the other hand, is the ability to replicate and confirm research...

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Main Authors: Dora, Tortarolo, Simone, Pernice, Clapero, Fabiana, Valdembri, Donatella, Serini, Guido, Riccardo, Federica, Tarone, Lidia, Bena, Chiara Enrico, Bosia, Carla, Contaldo, Sandro Gepiro, Marco, Beccuti, Pennisi, Marzio, Francesca, Cordero
Other Authors: MICrobiologie de l'ALImentation au Service de la Santé (MICALIS), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Format: Report
Language:English
Published: HAL CCSD 2023
Subjects:
Online Access:https://hal.science/hal-04320698
https://doi.org/10.1101/2023.11.07.565961
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spelling ftagroparistech:oai:HAL:hal-04320698v1 2023-12-31T10:21:43+01:00 OmniReprodubileCellAnalysis: a comprehensive toolbox for the analysis of cellular biology data Dora, Tortarolo Simone, Pernice Clapero, Fabiana Valdembri, Donatella Serini, Guido Riccardo, Federica Tarone, Lidia Bena, Chiara Enrico Bosia, Carla Contaldo, Sandro Gepiro Marco, Beccuti Pennisi, Marzio Francesca, Cordero MICrobiologie de l'ALImentation au Service de la Santé (MICALIS) AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) 2023-12-04 https://hal.science/hal-04320698 https://doi.org/10.1101/2023.11.07.565961 en eng HAL CCSD info:eu-repo/semantics/altIdentifier/doi/10.1101/2023.11.07.565961 hal-04320698 https://hal.science/hal-04320698 BIORXIV: 2023.11.07.565961 doi:10.1101/2023.11.07.565961 https://hal.science/hal-04320698 2023 [SDV]Life Sciences [q-bio] info:eu-repo/semantics/preprint Preprints, Working Papers, . 2023 ftagroparistech https://doi.org/10.1101/2023.11.07.565961 2023-12-05T23:48:19Z Open science and reproducibility are two key pillars of modern scientific research. Open science is making scientific research and data accessible and transparent to the broader scientific community and the public. Reproducibility, on the other hand, is the ability to replicate and confirm research results by following the same methods and procedures. Reproducibility is thus crucial because it ensures the reliability and validity of scientific findings. The relationship between open science and reproducibility is intertwined; indeed open science practices, such as sharing raw data, detailed methodologies, and code, greatly facilitate the reproducibility of research. In recent years, concerns about the reproducibility of scientific research have gained prominence, and indeed scientists still lament the lack of details in the methods sections of published papers and the unavailability of raw data from the authors. To assist cellular biologists and immunologists and to promote a more transparent, open and reproducible research practice, we developed OmniReproducibleCellAnalysis ( ORCA ), a new Shiny Application based in R, for the semi-automated analysis of Western Blot (WB), Reverse Transcription-quantitative PCR (RT-qPCR), Enzyme-Linked ImmunoSorbent Assay (ELISA), Endocytosis and Cytotoxicity experiments. ORCA is open-source and approachable by scientists without advanced R language knowledge. Our application automatically compiles a report containing the finalized data analysis and all its preliminary and intermediate steps, ensuring data analysis standardization and reproducibility. Furthermore, ORCA allows to upload raw data and results directly on the data repository Harvard Dataverse, a valuable tool for promoting transparency and data accessibility in scientific research. By employing ORCA , scientists will cut down analysis time and human-dependent errors, while taking a step towards a research practice compliant with Open Science and FAIR principle. Report Orca AgroParisTech: HAL (Institut des sciences et industries du vivant et de l'environnement)
institution Open Polar
collection AgroParisTech: HAL (Institut des sciences et industries du vivant et de l'environnement)
op_collection_id ftagroparistech
language English
topic [SDV]Life Sciences [q-bio]
spellingShingle [SDV]Life Sciences [q-bio]
Dora, Tortarolo
Simone, Pernice
Clapero, Fabiana
Valdembri, Donatella
Serini, Guido
Riccardo, Federica
Tarone, Lidia
Bena, Chiara Enrico
Bosia, Carla
Contaldo, Sandro Gepiro
Marco, Beccuti
Pennisi, Marzio
Francesca, Cordero
OmniReprodubileCellAnalysis: a comprehensive toolbox for the analysis of cellular biology data
topic_facet [SDV]Life Sciences [q-bio]
description Open science and reproducibility are two key pillars of modern scientific research. Open science is making scientific research and data accessible and transparent to the broader scientific community and the public. Reproducibility, on the other hand, is the ability to replicate and confirm research results by following the same methods and procedures. Reproducibility is thus crucial because it ensures the reliability and validity of scientific findings. The relationship between open science and reproducibility is intertwined; indeed open science practices, such as sharing raw data, detailed methodologies, and code, greatly facilitate the reproducibility of research. In recent years, concerns about the reproducibility of scientific research have gained prominence, and indeed scientists still lament the lack of details in the methods sections of published papers and the unavailability of raw data from the authors. To assist cellular biologists and immunologists and to promote a more transparent, open and reproducible research practice, we developed OmniReproducibleCellAnalysis ( ORCA ), a new Shiny Application based in R, for the semi-automated analysis of Western Blot (WB), Reverse Transcription-quantitative PCR (RT-qPCR), Enzyme-Linked ImmunoSorbent Assay (ELISA), Endocytosis and Cytotoxicity experiments. ORCA is open-source and approachable by scientists without advanced R language knowledge. Our application automatically compiles a report containing the finalized data analysis and all its preliminary and intermediate steps, ensuring data analysis standardization and reproducibility. Furthermore, ORCA allows to upload raw data and results directly on the data repository Harvard Dataverse, a valuable tool for promoting transparency and data accessibility in scientific research. By employing ORCA , scientists will cut down analysis time and human-dependent errors, while taking a step towards a research practice compliant with Open Science and FAIR principle.
author2 MICrobiologie de l'ALImentation au Service de la Santé (MICALIS)
AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
format Report
author Dora, Tortarolo
Simone, Pernice
Clapero, Fabiana
Valdembri, Donatella
Serini, Guido
Riccardo, Federica
Tarone, Lidia
Bena, Chiara Enrico
Bosia, Carla
Contaldo, Sandro Gepiro
Marco, Beccuti
Pennisi, Marzio
Francesca, Cordero
author_facet Dora, Tortarolo
Simone, Pernice
Clapero, Fabiana
Valdembri, Donatella
Serini, Guido
Riccardo, Federica
Tarone, Lidia
Bena, Chiara Enrico
Bosia, Carla
Contaldo, Sandro Gepiro
Marco, Beccuti
Pennisi, Marzio
Francesca, Cordero
author_sort Dora, Tortarolo
title OmniReprodubileCellAnalysis: a comprehensive toolbox for the analysis of cellular biology data
title_short OmniReprodubileCellAnalysis: a comprehensive toolbox for the analysis of cellular biology data
title_full OmniReprodubileCellAnalysis: a comprehensive toolbox for the analysis of cellular biology data
title_fullStr OmniReprodubileCellAnalysis: a comprehensive toolbox for the analysis of cellular biology data
title_full_unstemmed OmniReprodubileCellAnalysis: a comprehensive toolbox for the analysis of cellular biology data
title_sort omnireprodubilecellanalysis: a comprehensive toolbox for the analysis of cellular biology data
publisher HAL CCSD
publishDate 2023
url https://hal.science/hal-04320698
https://doi.org/10.1101/2023.11.07.565961
genre Orca
genre_facet Orca
op_source https://hal.science/hal-04320698
2023
op_relation info:eu-repo/semantics/altIdentifier/doi/10.1101/2023.11.07.565961
hal-04320698
https://hal.science/hal-04320698
BIORXIV: 2023.11.07.565961
doi:10.1101/2023.11.07.565961
op_doi https://doi.org/10.1101/2023.11.07.565961
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