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‘Multi-omic’ data analysis using O-miner
Innovations in -omics technologies have driven advances in biomedical research. However, integrating and analysing the large volumes of data generated from different high-throughput -omics technologies remain a significant challenge to basic and clinical scientists without bioinformatics skills or a...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6357557/ https://www.ncbi.nlm.nih.gov/pubmed/28981577 http://dx.doi.org/10.1093/bib/bbx080 |
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author | Sangaralingam, Ajanthah Dayem Ullah, Abu Z Marzec, Jacek Gadaleta, Emanuela Nagano, Ai Ross-Adams, Helen Wang, Jun Lemoine, Nicholas R Chelala, Claude |
author_facet | Sangaralingam, Ajanthah Dayem Ullah, Abu Z Marzec, Jacek Gadaleta, Emanuela Nagano, Ai Ross-Adams, Helen Wang, Jun Lemoine, Nicholas R Chelala, Claude |
author_sort | Sangaralingam, Ajanthah |
collection | PubMed |
description | Innovations in -omics technologies have driven advances in biomedical research. However, integrating and analysing the large volumes of data generated from different high-throughput -omics technologies remain a significant challenge to basic and clinical scientists without bioinformatics skills or access to bioinformatics support. To address this demand, we have significantly updated our previous O-miner analytical suite, to incorporate several new features and data types to provide an efficient and easy-to-use Web tool for the automated analysis of data from ‘-omics’ technologies. Created from a biologist’s perspective, this tool allows for the automated analysis of large and complex transcriptomic, genomic and methylomic data sets, together with biological/clinical information, to identify significantly altered pathways and prioritize novel biomarkers/targets for biological validation. Our resource can be used to analyse both in-house data and the huge amount of publicly available information from array and sequencing platforms. Multiple data sets can be easily combined, allowing for meta-analyses. Here, we describe the analytical pipelines currently available in O-miner and present examples of use to demonstrate its utility and relevance in maximizing research output. O-miner Web server is free to use and is available at http://www.o-miner.org. |
format | Online Article Text |
id | pubmed-6357557 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-63575572019-02-08 ‘Multi-omic’ data analysis using O-miner Sangaralingam, Ajanthah Dayem Ullah, Abu Z Marzec, Jacek Gadaleta, Emanuela Nagano, Ai Ross-Adams, Helen Wang, Jun Lemoine, Nicholas R Chelala, Claude Brief Bioinform Paper Innovations in -omics technologies have driven advances in biomedical research. However, integrating and analysing the large volumes of data generated from different high-throughput -omics technologies remain a significant challenge to basic and clinical scientists without bioinformatics skills or access to bioinformatics support. To address this demand, we have significantly updated our previous O-miner analytical suite, to incorporate several new features and data types to provide an efficient and easy-to-use Web tool for the automated analysis of data from ‘-omics’ technologies. Created from a biologist’s perspective, this tool allows for the automated analysis of large and complex transcriptomic, genomic and methylomic data sets, together with biological/clinical information, to identify significantly altered pathways and prioritize novel biomarkers/targets for biological validation. Our resource can be used to analyse both in-house data and the huge amount of publicly available information from array and sequencing platforms. Multiple data sets can be easily combined, allowing for meta-analyses. Here, we describe the analytical pipelines currently available in O-miner and present examples of use to demonstrate its utility and relevance in maximizing research output. O-miner Web server is free to use and is available at http://www.o-miner.org. Oxford University Press 2017-08-04 /pmc/articles/PMC6357557/ /pubmed/28981577 http://dx.doi.org/10.1093/bib/bbx080 Text en © The Author 2017. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Paper Sangaralingam, Ajanthah Dayem Ullah, Abu Z Marzec, Jacek Gadaleta, Emanuela Nagano, Ai Ross-Adams, Helen Wang, Jun Lemoine, Nicholas R Chelala, Claude ‘Multi-omic’ data analysis using O-miner |
title | ‘Multi-omic’ data analysis using O-miner |
title_full | ‘Multi-omic’ data analysis using O-miner |
title_fullStr | ‘Multi-omic’ data analysis using O-miner |
title_full_unstemmed | ‘Multi-omic’ data analysis using O-miner |
title_short | ‘Multi-omic’ data analysis using O-miner |
title_sort | ‘multi-omic’ data analysis using o-miner |
topic | Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6357557/ https://www.ncbi.nlm.nih.gov/pubmed/28981577 http://dx.doi.org/10.1093/bib/bbx080 |
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