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Gene expression data visualization tool on the o²S²PARC platform
Background: The identification of differentially expressed genes and their associated biological processes, molecular function, and cellular components are essential for genetic disease studies because they present potential biomarkers and therapeutic targets. Methods: In this study, we developed an...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
F1000 Research Limited
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9932352/ https://www.ncbi.nlm.nih.gov/pubmed/36816807 http://dx.doi.org/10.12688/f1000research.126840.2 |
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author | Ben Aribi, Hiba Ding, Mengyuan Kiran, Anmol |
author_facet | Ben Aribi, Hiba Ding, Mengyuan Kiran, Anmol |
author_sort | Ben Aribi, Hiba |
collection | PubMed |
description | Background: The identification of differentially expressed genes and their associated biological processes, molecular function, and cellular components are essential for genetic disease studies because they present potential biomarkers and therapeutic targets. Methods: In this study, we developed an o²S²PARC template to instantiate an interactive pipeline for gene expression data visualization, ontological mapping, and statistical evaluation. To demonstrate the tool's usefulness, we performed a case study on a publicly available dataset. Results: The tool enables users to identify the differentially expressed genes (DEGs) and visualize them in a volcano plot format. Ontologies associated with the DEGs are assigned and visualized in barplots. Conclusions: The “Expression data visualization” template is publicly available on the o²S²PARC platform. |
format | Online Article Text |
id | pubmed-9932352 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | F1000 Research Limited |
record_format | MEDLINE/PubMed |
spelling | pubmed-99323522023-02-17 Gene expression data visualization tool on the o²S²PARC platform Ben Aribi, Hiba Ding, Mengyuan Kiran, Anmol F1000Res Software Tool Article Background: The identification of differentially expressed genes and their associated biological processes, molecular function, and cellular components are essential for genetic disease studies because they present potential biomarkers and therapeutic targets. Methods: In this study, we developed an o²S²PARC template to instantiate an interactive pipeline for gene expression data visualization, ontological mapping, and statistical evaluation. To demonstrate the tool's usefulness, we performed a case study on a publicly available dataset. Results: The tool enables users to identify the differentially expressed genes (DEGs) and visualize them in a volcano plot format. Ontologies associated with the DEGs are assigned and visualized in barplots. Conclusions: The “Expression data visualization” template is publicly available on the o²S²PARC platform. F1000 Research Limited 2023-02-06 /pmc/articles/PMC9932352/ /pubmed/36816807 http://dx.doi.org/10.12688/f1000research.126840.2 Text en Copyright: © 2023 Ben Aribi H et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Software Tool Article Ben Aribi, Hiba Ding, Mengyuan Kiran, Anmol Gene expression data visualization tool on the o²S²PARC platform |
title | Gene expression data visualization tool on the o²S²PARC platform |
title_full | Gene expression data visualization tool on the o²S²PARC platform |
title_fullStr | Gene expression data visualization tool on the o²S²PARC platform |
title_full_unstemmed | Gene expression data visualization tool on the o²S²PARC platform |
title_short | Gene expression data visualization tool on the o²S²PARC platform |
title_sort | gene expression data visualization tool on the o²s²parc platform |
topic | Software Tool Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9932352/ https://www.ncbi.nlm.nih.gov/pubmed/36816807 http://dx.doi.org/10.12688/f1000research.126840.2 |
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