Bayesian Hidden Markov Modeling of Array CGH Data

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Bayesian Hidden Markov Modeling of Array CGH Data.

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for “ BioHMM : a heterogeneous hidden Markov model for segmenting array CGH data

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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BioHMM: a heterogeneous hidden Markov model for segmenting array CGH data

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