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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| Format: | Journal article |
| Language: | English |
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2012
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| _version_ | 1797085290771251200 |
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| author | Cazier, J Holmes, C Broxholme, J |
| author_facet | Cazier, J Holmes, C Broxholme, J |
| author_sort | Cazier, J |
| collection | OXFORD |
| 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). |
| first_indexed | 2024-03-07T02:06:50Z |
| format | Journal article |
| id | oxford-uuid:9f498348-f1ec-484d-bc3d-8449211805f8 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T02:06:50Z |
| publishDate | 2012 |
| record_format | dspace |
| spelling | oxford-uuid:9f498348-f1ec-484d-bc3d-8449211805f82022-03-27T00:56:25ZGREVE: Genomic Recurrent Event ViEwer to assist the identification of patterns across individual cancer samples.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:9f498348-f1ec-484d-bc3d-8449211805f8EnglishSymplectic Elements at Oxford2012Cazier, JHolmes, CBroxholme, JSUMMARY: 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). |
| spellingShingle | Cazier, J Holmes, C Broxholme, J 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 |
| work_keys_str_mv | AT cazierj grevegenomicrecurrenteventviewertoassisttheidentificationofpatternsacrossindividualcancersamples AT holmesc grevegenomicrecurrenteventviewertoassisttheidentificationofpatternsacrossindividualcancersamples AT broxholmej grevegenomicrecurrenteventviewertoassisttheidentificationofpatternsacrossindividualcancersamples |