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GREVE: Genomic Recurrent Event ViEwer to assist the identification of patterns across individual cancer samples

Summary: GREVE has been developed to assist with the identification of recurrent genomic aberrations across cancer samples. The exact characterization of such aberrations remains a challenge despite the availability of increasing amount of data, from SNParray to next-generation sequencing. Furthermo...

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Detalles Bibliográficos
Autores principales: Cazier, Jean-Baptiste, Holmes, Chris C., Broxholme, John
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3496338/
https://www.ncbi.nlm.nih.gov/pubmed/22962342
http://dx.doi.org/10.1093/bioinformatics/bts547
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author Cazier, Jean-Baptiste
Holmes, Chris C.
Broxholme, John
author_facet Cazier, Jean-Baptiste
Holmes, Chris C.
Broxholme, John
author_sort Cazier, Jean-Baptiste
collection PubMed
description Summary: GREVE has been developed to assist with the identification of recurrent genomic aberrations across cancer samples. The exact characterization of such aberrations remains a challenge despite the availability of increasing amount of data, from SNParray to next-generation sequencing. Furthermore, genomic aberrations in cancer are especially difficult to handle because they are, by nature, unique to the patients. However, their recurrence in specific regions of the genome has been shown to reflect their relevance in the development of tumors. GREVE makes use of previously characterized events to identify such regions and focus any further analysis. Availability: GREVE is available through a web interface and open-source application (http://www.well.ox.ac.uk/GREVE).
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spelling pubmed-34963382012-12-12 GREVE: Genomic Recurrent Event ViEwer to assist the identification of patterns across individual cancer samples Cazier, Jean-Baptiste Holmes, Chris C. Broxholme, John Bioinformatics Applications Note Summary: GREVE has been developed to assist with the identification of recurrent genomic aberrations across cancer samples. The exact characterization of such aberrations remains a challenge despite the availability of increasing amount of data, from SNParray to next-generation sequencing. Furthermore, genomic aberrations in cancer are especially difficult to handle because they are, by nature, unique to the patients. However, their recurrence in specific regions of the genome has been shown to reflect their relevance in the development of tumors. GREVE makes use of previously characterized events to identify such regions and focus any further analysis. Availability: GREVE is available through a web interface and open-source application (http://www.well.ox.ac.uk/GREVE). Oxford University Press 2012-11-15 2012-09-06 /pmc/articles/PMC3496338/ /pubmed/22962342 http://dx.doi.org/10.1093/bioinformatics/bts547 Text en © The Author 2012. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Note
Cazier, Jean-Baptiste
Holmes, Chris C.
Broxholme, John
GREVE: Genomic Recurrent Event ViEwer to assist the identification of patterns across individual cancer samples
title GREVE: Genomic Recurrent Event ViEwer to assist the identification of patterns across individual cancer samples
title_full GREVE: Genomic Recurrent Event ViEwer to assist the identification of patterns across individual cancer samples
title_fullStr GREVE: Genomic Recurrent Event ViEwer to assist the identification of patterns across individual cancer samples
title_full_unstemmed GREVE: Genomic Recurrent Event ViEwer to assist the identification of patterns across individual cancer samples
title_short GREVE: Genomic Recurrent Event ViEwer to assist the identification of patterns across individual cancer samples
title_sort greve: genomic recurrent event viewer to assist the identification of patterns across individual cancer samples
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3496338/
https://www.ncbi.nlm.nih.gov/pubmed/22962342
http://dx.doi.org/10.1093/bioinformatics/bts547
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