Clusternomics: Integrative context-dependent clustering for heterogeneous datasets
نویسندگان
چکیده
منابع مشابه
Clusternomics: Integrative context-dependent clustering for heterogeneous datasets
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 pr...
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ژورنال
عنوان ژورنال: PLOS Computational Biology
سال: 2017
ISSN: 1553-7358
DOI: 10.1371/journal.pcbi.1005781