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rdf:type |
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lifeskim:mentions |
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pubmed:dateCreated |
2005-2-24
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pubmed:abstractText |
Microarray-CGH experiments are used to detect and map chromosomal imbalances, by hybridizing targets of genomic DNA from a test and a reference sample to sequences immobilized on a slide. These probes are genomic DNA sequences (BACs) that are mapped on the genome. The signal has a spatial coherence that can be handled by specific statistical tools. Segmentation methods seem to be a natural framework for this purpose. A CGH profile can be viewed as a succession of segments that represent homogeneous regions in the genome whose BACs share the same relative copy number on average. We model a CGH profile by a random Gaussian process whose distribution parameters are affected by abrupt changes at unknown coordinates. Two major problems arise: to determine which parameters are affected by the abrupt changes (the mean and the variance, or the mean only), and the selection of the number of segments in the profile.
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pubmed:grant |
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pubmed:commentsCorrections |
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pubmed:language |
eng
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pubmed:journal |
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pubmed:citationSubset |
IM
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pubmed:chemical |
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pubmed:status |
MEDLINE
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pubmed:issn |
1471-2105
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pubmed:author |
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pubmed:issnType |
Electronic
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pubmed:volume |
6
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pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
27
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pubmed:dateRevised |
2009-11-18
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pubmed:meshHeading |
pubmed-meshheading:15705208-Algorithms,
pubmed-meshheading:15705208-Chromosome Aberrations,
pubmed-meshheading:15705208-Chromosome Mapping,
pubmed-meshheading:15705208-Chromosomes, Artificial, Bacterial,
pubmed-meshheading:15705208-Computational Biology,
pubmed-meshheading:15705208-Computer Graphics,
pubmed-meshheading:15705208-Computer Simulation,
pubmed-meshheading:15705208-DNA,
pubmed-meshheading:15705208-Data Interpretation, Statistical,
pubmed-meshheading:15705208-Database Management Systems,
pubmed-meshheading:15705208-Gene Dosage,
pubmed-meshheading:15705208-Gene Expression Profiling,
pubmed-meshheading:15705208-Genetic Markers,
pubmed-meshheading:15705208-Genome,
pubmed-meshheading:15705208-Genome, Human,
pubmed-meshheading:15705208-Humans,
pubmed-meshheading:15705208-Models, Genetic,
pubmed-meshheading:15705208-Models, Statistical,
pubmed-meshheading:15705208-Normal Distribution,
pubmed-meshheading:15705208-Nucleic Acid Conformation,
pubmed-meshheading:15705208-Nucleic Acid Hybridization,
pubmed-meshheading:15705208-Oligonucleotide Array Sequence Analysis,
pubmed-meshheading:15705208-Oligonucleotide Probes,
pubmed-meshheading:15705208-Software,
pubmed-meshheading:15705208-User-Computer Interface
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pubmed:year |
2005
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pubmed:articleTitle |
A statistical approach for array CGH data analysis.
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pubmed:affiliation |
Institut National Agronomique Paris-Grignon, UMR INAPG/ENGREF/INRA MIA 518, Paris, France. picard@inapg.fr
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pubmed:publicationType |
Journal Article,
Research Support, U.S. Gov't, P.H.S.,
Research Support, N.I.H., Extramural
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