Bayesian Hidden Markov Modeling of Array CGH Data
نویسندگان
چکیده
منابع مشابه
Bayesian Hidden Markov Modeling of Array CGH Data.
Genomic alterations have been linked to the development and progression of cancer. The technique of comparative genomic hybridization (CGH) yields data consisting of fluorescence intensity ratios of test and reference DNA samples. The intensity ratios provide information about the number of copies in DNA. Practical issues such as the contamination of tumor cells in tissue specimens and normaliz...
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The development of solid tumors is associated with acquisition of complex genetic alterations, indicating that failures in the mechanisms that maintain the integrity of the genome contribute to tumor evolution. Thus, one expects that the particular types of genomic alterations seen in tumors reflect underlying failures in maintenance of genetic stability, as well as selection for changes that p...
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1.1 The structure of the model when there are more than two states We now describe how BioHMM is used when there are more than two underlying states. Most of the components of the model can be extended in an obvious way using the framework described in the Approach section of the paper. Because of the constraints imposed upon the parameters in the transition matrix, its structure is slightly co...
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SUMMARY We have developed a new method (BioHMM) for segmenting array comparative genomic hybridization data into states with the same underlying copy number. By utilizing a heterogeneous hidden Markov model, BioHMM incorporates relevant biological factors (e.g. the distance between adjacent clones) in the segmentation process.
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ژورنال
عنوان ژورنال: Journal of the American Statistical Association
سال: 2008
ISSN: 0162-1459,1537-274X
DOI: 10.1198/016214507000000923