期刊
BIOINFORMATICS
卷 30, 期 10, 页码 1370-1376出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btu064
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类别
资金
- Biomedical Advanced Research and Development Authority (BARDA)
- Office of Naval Research
A non-parametric Bayesian factor model is proposed for joint analysis of multi-platform genomics data. The approach is based on factorizing the latent space (feature space) into a shared component and a data-specific component with the dimensionality of these components (spaces) inferred via a beta-Bernoulli process. The proposed approach is demonstrated by jointly analyzing gene expression/copy number variations and gene expression/methylation data for ovarian cancer patients, showing that the proposed model can potentially uncover key drivers related to cancer.
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