Article

Clusternomics: Integrative Context-Dependent Clustering for Heterogeneous Datasets

2017-05-17

Abstract excerpt

Integrative clustering is used to identify groups of samples by jointly analysing multiple datasets describing the same set of biological samples, such as gene expression, copy number, methylation etc. Most existing algorithms for integrative clustering assume that there is a shared consistent set of clusters across all datasets, and most of the data samples follow this structure. However in practice, the structur...

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Literature Corpus work: b3229f80-2687-53a8-8c4d-489738e99bf4
DOI: 10.1101/139071

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