Document Detail

Analysis of array CGH data: from signal ratio to gain and loss of DNA regions.
MedLine Citation:
PMID:  15381628     Owner:  NLM     Status:  MEDLINE    
MOTIVATION: Genomic DNA regions are frequently lost or gained during tumor progression. Array Comparative Genomic Hybridization (array CGH) technology makes it possible to assess these changes in DNA in cancers, by comparison with a normal reference. The identification of systematically deleted or amplified genomic regions in a set of tumors enables biologists to identify genes involved in cancer progression because tumor suppressor genes are thought to be located in lost genomic regions and oncogenes, in gained regions. Array CGH profiles should also improve the classification of tumors. The achievement of these goals requires a methodology for detecting the breakpoints delimiting altered regions in genomic patterns and assigning a status (normal, gained or lost) to each chromosomal region. RESULTS: We have developed a methodology for the automatic detection of breakpoints from array CGH profile, and the assignment of a status to each chromosomal region. The breakpoint detection step is based on the Adaptive Weights Smoothing (AWS) procedure and provides highly convincing results: our algorithm detects 97, 100 and 94% of breakpoints in simulated data, karyotyping results and manually analyzed profiles, respectively. The percentage of correctly assigned statuses ranges from 98.9 to 99.8% for simulated data and is 100% for karyotyping results. Our algorithm also outperforms other solutions on a public reference dataset. AVAILABILITY: The R package GLAD (Gain and Loss Analysis of DNA) is available upon request.
Philippe Hupé; Nicolas Stransky; Jean-Paul Thiery; François Radvanyi; Emmanuel Barillot
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Publication Detail:
Type:  Comparative Study; Evaluation Studies; Journal Article; Research Support, Non-U.S. Gov't; Validation Studies     Date:  2004-09-20
Journal Detail:
Title:  Bioinformatics (Oxford, England)     Volume:  20     ISSN:  1367-4803     ISO Abbreviation:  Bioinformatics     Publication Date:  2004 Dec 
Date Detail:
Created Date:  2004-12-13     Completed Date:  2005-05-04     Revised Date:  2008-11-21    
Medline Journal Info:
Nlm Unique ID:  9808944     Medline TA:  Bioinformatics     Country:  England    
Other Details:
Languages:  eng     Pagination:  3413-22     Citation Subset:  IM    
Service Bioinformatique, UMR 144 CNRS/Institut Curie, 26, rue d'Ulm, Paris, 75248 cedex 05, France. <>
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MeSH Terms
Chromosome Mapping / methods*
DNA Mutational Analysis / methods*
Gene Dosage
Genetic Variation
In Situ Hybridization / methods*
Models, Genetic
Models, Statistical
Oligonucleotide Array Sequence Analysis / methods*
Reproducibility of Results
Sensitivity and Specificity
Sequence Analysis, DNA / methods*
Stochastic Processes
Urinary Bladder Neoplasms / diagnosis,  genetics

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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