Journal
NATURE PROTOCOLS
Volume 6, Issue 3, Pages -Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/nprot.2010.197
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Funding
- German Research Foundation (DFG)
- Cluster of Excellence for Multimodal Computing and Interaction
- German National Genome Research Network
- NIH [NIH R01 LM009722]
- Buck Trust
- German Academic Exchange Service (DAAD)
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Transitivity Clustering is a method for the partitioning of biological data into groups of similar objects, such as genes, for instance. It provides integrated access to various functions addressing each step of a typical cluster analysis. To facilitate this, Transitivity Clustering is accessible online and offers three user-friendly interfaces: a powerful stand-alone version, a web interface, and a collection of Cytoscape plug-ins. In this paper, we describe three major workflows: (i) protein (super) family detection with Cytoscape, (ii) protein homology detection with incomplete gold standards and (iii) clustering of gene expression data. This protocol guides the user through the most important features of Transitivity Clustering and takes similar to 1 h to complete.
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