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Public data and open source tools for multi-assay genomic investigation of disease
Molecular interrogation of a biological sample through DNA sequencing, RNA and microRNA profiling, proteomics and other assays, has the potential to provide a systems level approach to predicting treatment response and disease progression, and to developing precision therapies. Large publicly funded...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4945830/ https://www.ncbi.nlm.nih.gov/pubmed/26463000 http://dx.doi.org/10.1093/bib/bbv080 |
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author | Kannan, Lavanya Ramos, Marcel Re, Angela El-Hachem, Nehme Safikhani, Zhaleh Gendoo, Deena M.A. Davis, Sean Gomez-Cabrero, David Castelo, Robert Hansen, Kasper D. Carey, Vincent J. Morgan, Martin Culhane, Aedín C. Haibe-Kains, Benjamin Waldron, Levi |
author_facet | Kannan, Lavanya Ramos, Marcel Re, Angela El-Hachem, Nehme Safikhani, Zhaleh Gendoo, Deena M.A. Davis, Sean Gomez-Cabrero, David Castelo, Robert Hansen, Kasper D. Carey, Vincent J. Morgan, Martin Culhane, Aedín C. Haibe-Kains, Benjamin Waldron, Levi |
author_sort | Kannan, Lavanya |
collection | PubMed |
description | Molecular interrogation of a biological sample through DNA sequencing, RNA and microRNA profiling, proteomics and other assays, has the potential to provide a systems level approach to predicting treatment response and disease progression, and to developing precision therapies. Large publicly funded projects have generated extensive and freely available multi-assay data resources; however, bioinformatic and statistical methods for the analysis of such experiments are still nascent. We review multi-assay genomic data resources in the areas of clinical oncology, pharmacogenomics and other perturbation experiments, population genomics and regulatory genomics and other areas, and tools for data acquisition. Finally, we review bioinformatic tools that are explicitly geared toward integrative genomic data visualization and analysis. This review provides starting points for accessing publicly available data and tools to support development of needed integrative methods. |
format | Online Article Text |
id | pubmed-4945830 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-49458302016-07-19 Public data and open source tools for multi-assay genomic investigation of disease Kannan, Lavanya Ramos, Marcel Re, Angela El-Hachem, Nehme Safikhani, Zhaleh Gendoo, Deena M.A. Davis, Sean Gomez-Cabrero, David Castelo, Robert Hansen, Kasper D. Carey, Vincent J. Morgan, Martin Culhane, Aedín C. Haibe-Kains, Benjamin Waldron, Levi Brief Bioinform Special Issue continued: Computational Systems Biomedicine Papers Molecular interrogation of a biological sample through DNA sequencing, RNA and microRNA profiling, proteomics and other assays, has the potential to provide a systems level approach to predicting treatment response and disease progression, and to developing precision therapies. Large publicly funded projects have generated extensive and freely available multi-assay data resources; however, bioinformatic and statistical methods for the analysis of such experiments are still nascent. We review multi-assay genomic data resources in the areas of clinical oncology, pharmacogenomics and other perturbation experiments, population genomics and regulatory genomics and other areas, and tools for data acquisition. Finally, we review bioinformatic tools that are explicitly geared toward integrative genomic data visualization and analysis. This review provides starting points for accessing publicly available data and tools to support development of needed integrative methods. Oxford University Press 2016-07 2015-10-10 /pmc/articles/PMC4945830/ /pubmed/26463000 http://dx.doi.org/10.1093/bib/bbv080 Text en © The Author 2015. 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 | Special Issue continued: Computational Systems Biomedicine Papers Kannan, Lavanya Ramos, Marcel Re, Angela El-Hachem, Nehme Safikhani, Zhaleh Gendoo, Deena M.A. Davis, Sean Gomez-Cabrero, David Castelo, Robert Hansen, Kasper D. Carey, Vincent J. Morgan, Martin Culhane, Aedín C. Haibe-Kains, Benjamin Waldron, Levi Public data and open source tools for multi-assay genomic investigation of disease |
title | Public data and open source tools for multi-assay genomic investigation of disease |
title_full | Public data and open source tools for multi-assay genomic investigation of disease |
title_fullStr | Public data and open source tools for multi-assay genomic investigation of disease |
title_full_unstemmed | Public data and open source tools for multi-assay genomic investigation of disease |
title_short | Public data and open source tools for multi-assay genomic investigation of disease |
title_sort | public data and open source tools for multi-assay genomic investigation of disease |
topic | Special Issue continued: Computational Systems Biomedicine Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4945830/ https://www.ncbi.nlm.nih.gov/pubmed/26463000 http://dx.doi.org/10.1093/bib/bbv080 |
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