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- Title
Bayesian correlated clustering to integrate multiple datasets.
- Authors
Kirk, Paul; Griffin, Jim E; Savage, Richard S; Ghahramani, Zoubin; Wild, David L
- Abstract
The integration of multiple datasets remains a key challenge in systems biology and genomic medicine. Modern high-throughput technologies generate a broad array of different data types, providing distinct-but often complementary-information. We present a Bayesian method for the unsupervised integrative modelling of multiple datasets, which we refer to as MDI (Multiple Dataset Integration). MDI can integrate information from a wide range of different datasets and data types simultaneously (including the ability to model time series data explicitly using Gaussian processes). Each dataset is modelled using a Dirichlet-multinomial allocation (DMA) mixture model, with dependencies between these models captured through parameters that describe the agreement among the datasets.
- Publication
Bioinformatics (Oxford, England), 2012, Vol 28, Issue 24, p3290
- ISSN
1367-4811
- Publication type
Journal Article
- DOI
10.1093/bioinformatics/bts595