Integrative pathway enrichment analysis of multivariate omics data

Multi-omics datasets pose major challenges to data interpretation and hypothesis generation owing to their high-dimensional molecular profiles. Here, the authors develop ActivePathways method, which uses data fusion techniques for integrative pathway analysis of multi-omics data and candidate gene d...

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Autores principales:	Marta Paczkowska, Jonathan Barenboim, Nardnisa Sintupisut, Natalie S. Fox, Helen Zhu, Diala Abd-Rabbo, Miles W. Mee, Paul C. Boutros, PCAWG Drivers and Functional Interpretation Working Group, Jüri Reimand, PCAWG Consortium
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/0e1be01e74114d78838f12db1d7166ab
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spelling	oai:doaj.org-article:0e1be01e74114d78838f12db1d7166ab2021-12-02T14:40:50ZIntegrative pathway enrichment analysis of multivariate omics data10.1038/s41467-019-13983-92041-1723https://doaj.org/article/0e1be01e74114d78838f12db1d7166ab2020-02-01T00:00:00Zhttps://doi.org/10.1038/s41467-019-13983-9https://doaj.org/toc/2041-1723Multi-omics datasets pose major challenges to data interpretation and hypothesis generation owing to their high-dimensional molecular profiles. Here, the authors develop ActivePathways method, which uses data fusion techniques for integrative pathway analysis of multi-omics data and candidate gene discovery.Marta PaczkowskaJonathan BarenboimNardnisa SintupisutNatalie S. FoxHelen ZhuDiala Abd-RabboMiles W. MeePaul C. BoutrosPCAWG Drivers and Functional Interpretation Working GroupJüri ReimandPCAWG ConsortiumNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-16 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Marta Paczkowska Jonathan Barenboim Nardnisa Sintupisut Natalie S. Fox Helen Zhu Diala Abd-Rabbo Miles W. Mee Paul C. Boutros PCAWG Drivers and Functional Interpretation Working Group Jüri Reimand PCAWG Consortium Integrative pathway enrichment analysis of multivariate omics data
description	Multi-omics datasets pose major challenges to data interpretation and hypothesis generation owing to their high-dimensional molecular profiles. Here, the authors develop ActivePathways method, which uses data fusion techniques for integrative pathway analysis of multi-omics data and candidate gene discovery.
format	article
author	Marta Paczkowska Jonathan Barenboim Nardnisa Sintupisut Natalie S. Fox Helen Zhu Diala Abd-Rabbo Miles W. Mee Paul C. Boutros PCAWG Drivers and Functional Interpretation Working Group Jüri Reimand PCAWG Consortium
author_facet	Marta Paczkowska Jonathan Barenboim Nardnisa Sintupisut Natalie S. Fox Helen Zhu Diala Abd-Rabbo Miles W. Mee Paul C. Boutros PCAWG Drivers and Functional Interpretation Working Group Jüri Reimand PCAWG Consortium
author_sort	Marta Paczkowska
title	Integrative pathway enrichment analysis of multivariate omics data
title_short	Integrative pathway enrichment analysis of multivariate omics data
title_full	Integrative pathway enrichment analysis of multivariate omics data
title_fullStr	Integrative pathway enrichment analysis of multivariate omics data
title_full_unstemmed	Integrative pathway enrichment analysis of multivariate omics data
title_sort	integrative pathway enrichment analysis of multivariate omics data
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/0e1be01e74114d78838f12db1d7166ab
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Integrative pathway enrichment analysis of multivariate omics data

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