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Visualizing multidimensional cancer genomics data

Cancer genomics projects employ high-throughput technologies to identify the complete catalog of somatic alterations that characterize the genome, transcriptome and epigenome of cohorts of tumor samples. Examples include projects carried out by the International Cancer Genome Consortium (ICGC) and T...

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Detalles Bibliográficos
Autores principales: Schroeder, Michael P, Gonzalez-Perez, Abel, Lopez-Bigas, Nuria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3706894/
https://www.ncbi.nlm.nih.gov/pubmed/23363777
http://dx.doi.org/10.1186/gm413
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author Schroeder, Michael P
Gonzalez-Perez, Abel
Lopez-Bigas, Nuria
author_facet Schroeder, Michael P
Gonzalez-Perez, Abel
Lopez-Bigas, Nuria
author_sort Schroeder, Michael P
collection PubMed
description Cancer genomics projects employ high-throughput technologies to identify the complete catalog of somatic alterations that characterize the genome, transcriptome and epigenome of cohorts of tumor samples. Examples include projects carried out by the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). A crucial step in the extraction of knowledge from the data is the exploration by experts of the different alterations, as well as the multiple relationships between them. To that end, the use of intuitive visualization tools that can integrate different types of alterations with clinical data is essential to the field of cancer genomics. Here, we review effective and common visualization techniques for exploring oncogenomics data and discuss a selection of tools that allow researchers to effectively visualize multidimensional oncogenomics datasets. The review covers visualization methods employed by tools such as Circos, Gitools, the Integrative Genomics Viewer, Cytoscape, Savant Genome Browser, StratomeX and platforms such as cBio Cancer Genomics Portal, IntOGen, the UCSC Cancer Genomics Browser, the Regulome Explorer and the Cancer Genome Workbench.
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spelling pubmed-37068942014-01-31 Visualizing multidimensional cancer genomics data Schroeder, Michael P Gonzalez-Perez, Abel Lopez-Bigas, Nuria Genome Med Review Cancer genomics projects employ high-throughput technologies to identify the complete catalog of somatic alterations that characterize the genome, transcriptome and epigenome of cohorts of tumor samples. Examples include projects carried out by the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). A crucial step in the extraction of knowledge from the data is the exploration by experts of the different alterations, as well as the multiple relationships between them. To that end, the use of intuitive visualization tools that can integrate different types of alterations with clinical data is essential to the field of cancer genomics. Here, we review effective and common visualization techniques for exploring oncogenomics data and discuss a selection of tools that allow researchers to effectively visualize multidimensional oncogenomics datasets. The review covers visualization methods employed by tools such as Circos, Gitools, the Integrative Genomics Viewer, Cytoscape, Savant Genome Browser, StratomeX and platforms such as cBio Cancer Genomics Portal, IntOGen, the UCSC Cancer Genomics Browser, the Regulome Explorer and the Cancer Genome Workbench. BioMed Central 2013-01-31 /pmc/articles/PMC3706894/ /pubmed/23363777 http://dx.doi.org/10.1186/gm413 Text en Copyright © 2013 BioMed Central Ltd
spellingShingle Review
Schroeder, Michael P
Gonzalez-Perez, Abel
Lopez-Bigas, Nuria
Visualizing multidimensional cancer genomics data
title Visualizing multidimensional cancer genomics data
title_full Visualizing multidimensional cancer genomics data
title_fullStr Visualizing multidimensional cancer genomics data
title_full_unstemmed Visualizing multidimensional cancer genomics data
title_short Visualizing multidimensional cancer genomics data
title_sort visualizing multidimensional cancer genomics data
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3706894/
https://www.ncbi.nlm.nih.gov/pubmed/23363777
http://dx.doi.org/10.1186/gm413
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