A latent class model with hidden Markov dependence for array CGH data.
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ABSTRACT:
SUBMITTER: DeSantis SM
PROVIDER: S-EPMC3052263 | biostudies-literature | 2009 Dec
REPOSITORIES: biostudies-literature
Publications
A latent class model with hidden Markov dependence for array CGH data.
DeSantis Stacia M SM Houseman E Andrés EA Coull Brent A BA Louis David N DN Mohapatra Gayatry G Betensky Rebecca A RA
Biometrics 20091201 4
Array CGH is a high-throughput technique designed to detect genomic alterations linked to the development and progression of cancer. The technique yields fluorescence ratios that characterize DNA copy number change in tumor versus healthy cells. Classification of tumors based on aCGH profiles is of scientific interest but the analysis of these data is complicated by the large number of highly correlated measures. In this article, we develop a supervised Bayesian latent class approach for classif ...[more]
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