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OmicsView: Omics data analysis through interactive visual analytics
With advances in NGS technologies, transcriptional profiling of human tissue across many diseases is becoming more routine, leading to the generation of petabytes of data deposited in public repositories. There is a need for bench scientists with little computational expertise to be able to access a...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8924308/ https://www.ncbi.nlm.nih.gov/pubmed/35356547 http://dx.doi.org/10.1016/j.csbj.2022.02.022 |
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author | Casey, Fergal Negi, Soumya Zhu, Jing Sun, Yu H. Zavodszky, Maria Cheng, Derrick Lin, Dongdong John, Sally Penny, Michelle A. Sexton, David Zhang, Baohong |
author_facet | Casey, Fergal Negi, Soumya Zhu, Jing Sun, Yu H. Zavodszky, Maria Cheng, Derrick Lin, Dongdong John, Sally Penny, Michelle A. Sexton, David Zhang, Baohong |
author_sort | Casey, Fergal |
collection | PubMed |
description | With advances in NGS technologies, transcriptional profiling of human tissue across many diseases is becoming more routine, leading to the generation of petabytes of data deposited in public repositories. There is a need for bench scientists with little computational expertise to be able to access and mine this data to understand disease pathology, identify robust biomarkers of disease and the effect of interventions (in vivo or in vitro). To this end we release an open source analytics and visualization platform for expression data called OmicsView, http://omicsview.org. This platform comes preloaded with 1000 s of samples across many disease areas and normal tissue, including the GTEx database, all processed with a harmonized pipeline. We demonstrate the power and ease-of-use of the platform by means of a Crohn’s disease data mining exercise where we can quickly uncover disease pathology and identify strong biomarkers of disease and response to treatment. |
format | Online Article Text |
id | pubmed-8924308 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-89243082022-03-29 OmicsView: Omics data analysis through interactive visual analytics Casey, Fergal Negi, Soumya Zhu, Jing Sun, Yu H. Zavodszky, Maria Cheng, Derrick Lin, Dongdong John, Sally Penny, Michelle A. Sexton, David Zhang, Baohong Comput Struct Biotechnol J Research Article With advances in NGS technologies, transcriptional profiling of human tissue across many diseases is becoming more routine, leading to the generation of petabytes of data deposited in public repositories. There is a need for bench scientists with little computational expertise to be able to access and mine this data to understand disease pathology, identify robust biomarkers of disease and the effect of interventions (in vivo or in vitro). To this end we release an open source analytics and visualization platform for expression data called OmicsView, http://omicsview.org. This platform comes preloaded with 1000 s of samples across many disease areas and normal tissue, including the GTEx database, all processed with a harmonized pipeline. We demonstrate the power and ease-of-use of the platform by means of a Crohn’s disease data mining exercise where we can quickly uncover disease pathology and identify strong biomarkers of disease and response to treatment. Research Network of Computational and Structural Biotechnology 2022-03-10 /pmc/articles/PMC8924308/ /pubmed/35356547 http://dx.doi.org/10.1016/j.csbj.2022.02.022 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Casey, Fergal Negi, Soumya Zhu, Jing Sun, Yu H. Zavodszky, Maria Cheng, Derrick Lin, Dongdong John, Sally Penny, Michelle A. Sexton, David Zhang, Baohong OmicsView: Omics data analysis through interactive visual analytics |
title | OmicsView: Omics data analysis through interactive visual analytics |
title_full | OmicsView: Omics data analysis through interactive visual analytics |
title_fullStr | OmicsView: Omics data analysis through interactive visual analytics |
title_full_unstemmed | OmicsView: Omics data analysis through interactive visual analytics |
title_short | OmicsView: Omics data analysis through interactive visual analytics |
title_sort | omicsview: omics data analysis through interactive visual analytics |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8924308/ https://www.ncbi.nlm.nih.gov/pubmed/35356547 http://dx.doi.org/10.1016/j.csbj.2022.02.022 |
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