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A user guide for the online exploration and visualization of PCAWG data
The Pan-Cancer Analysis of Whole Genomes (PCAWG) project generated a vast amount of whole-genome cancer sequencing resource data. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor ty...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7340791/ https://www.ncbi.nlm.nih.gov/pubmed/32636365 http://dx.doi.org/10.1038/s41467-020-16785-6 |
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author | Goldman, Mary J. Zhang, Junjun Fonseca, Nuno A. Cortés-Ciriano, Isidro Xiang, Qian Craft, Brian Piñeiro-Yáñez, Elena O’Connor, Brian D. Bazant, Wojciech Barrera, Elisabet Muñoz-Pomer, Alfonso Petryszak, Robert Füllgrabe, Anja Al-Shahrour, Fatima Keays, Maria Haussler, David Weinstein, John N. Huber, Wolfgang Valencia, Alfonso Park, Peter J. Papatheodorou, Irene Zhu, Jingchun Ferretti, Vincent Vazquez, Miguel |
author_facet | Goldman, Mary J. Zhang, Junjun Fonseca, Nuno A. Cortés-Ciriano, Isidro Xiang, Qian Craft, Brian Piñeiro-Yáñez, Elena O’Connor, Brian D. Bazant, Wojciech Barrera, Elisabet Muñoz-Pomer, Alfonso Petryszak, Robert Füllgrabe, Anja Al-Shahrour, Fatima Keays, Maria Haussler, David Weinstein, John N. Huber, Wolfgang Valencia, Alfonso Park, Peter J. Papatheodorou, Irene Zhu, Jingchun Ferretti, Vincent Vazquez, Miguel |
author_sort | Goldman, Mary J. |
collection | PubMed |
description | The Pan-Cancer Analysis of Whole Genomes (PCAWG) project generated a vast amount of whole-genome cancer sequencing resource data. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we provide a user’s guide to the five publicly available online data exploration and visualization tools introduced in the PCAWG marker paper. These tools are ICGC Data Portal, UCSC Xena, Chromothripsis Explorer, Expression Atlas, and PCAWG-Scout. We detail use cases and analyses for each tool, show how they incorporate outside resources from the larger genomics ecosystem, and demonstrate how the tools can be used together to understand the biology of cancers more deeply. Together, the tools enable researchers to query the complex genomic PCAWG data dynamically and integrate external information, enabling and enhancing interpretation. |
format | Online Article Text |
id | pubmed-7340791 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-73407912020-07-09 A user guide for the online exploration and visualization of PCAWG data Goldman, Mary J. Zhang, Junjun Fonseca, Nuno A. Cortés-Ciriano, Isidro Xiang, Qian Craft, Brian Piñeiro-Yáñez, Elena O’Connor, Brian D. Bazant, Wojciech Barrera, Elisabet Muñoz-Pomer, Alfonso Petryszak, Robert Füllgrabe, Anja Al-Shahrour, Fatima Keays, Maria Haussler, David Weinstein, John N. Huber, Wolfgang Valencia, Alfonso Park, Peter J. Papatheodorou, Irene Zhu, Jingchun Ferretti, Vincent Vazquez, Miguel Nat Commun Article The Pan-Cancer Analysis of Whole Genomes (PCAWG) project generated a vast amount of whole-genome cancer sequencing resource data. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we provide a user’s guide to the five publicly available online data exploration and visualization tools introduced in the PCAWG marker paper. These tools are ICGC Data Portal, UCSC Xena, Chromothripsis Explorer, Expression Atlas, and PCAWG-Scout. We detail use cases and analyses for each tool, show how they incorporate outside resources from the larger genomics ecosystem, and demonstrate how the tools can be used together to understand the biology of cancers more deeply. Together, the tools enable researchers to query the complex genomic PCAWG data dynamically and integrate external information, enabling and enhancing interpretation. Nature Publishing Group UK 2020-07-07 /pmc/articles/PMC7340791/ /pubmed/32636365 http://dx.doi.org/10.1038/s41467-020-16785-6 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Goldman, Mary J. Zhang, Junjun Fonseca, Nuno A. Cortés-Ciriano, Isidro Xiang, Qian Craft, Brian Piñeiro-Yáñez, Elena O’Connor, Brian D. Bazant, Wojciech Barrera, Elisabet Muñoz-Pomer, Alfonso Petryszak, Robert Füllgrabe, Anja Al-Shahrour, Fatima Keays, Maria Haussler, David Weinstein, John N. Huber, Wolfgang Valencia, Alfonso Park, Peter J. Papatheodorou, Irene Zhu, Jingchun Ferretti, Vincent Vazquez, Miguel A user guide for the online exploration and visualization of PCAWG data |
title | A user guide for the online exploration and visualization of PCAWG data |
title_full | A user guide for the online exploration and visualization of PCAWG data |
title_fullStr | A user guide for the online exploration and visualization of PCAWG data |
title_full_unstemmed | A user guide for the online exploration and visualization of PCAWG data |
title_short | A user guide for the online exploration and visualization of PCAWG data |
title_sort | user guide for the online exploration and visualization of pcawg data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7340791/ https://www.ncbi.nlm.nih.gov/pubmed/32636365 http://dx.doi.org/10.1038/s41467-020-16785-6 |
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