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clusterMaker: a multi-algorithm clustering plugin for Cytoscape

BACKGROUND: In the post-genomic era, the rapid increase in high-throughput data calls for computational tools capable of integrating data of diverse types and facilitating recognition of biologically meaningful patterns within them. For example, protein-protein interaction data sets have been cluste...

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Autores principales: Morris, John H, Apeltsin, Leonard, Newman, Aaron M, Baumbach, Jan, Wittkop, Tobias, Su, Gang, Bader, Gary D, Ferrin, Thomas E
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3262844/
https://www.ncbi.nlm.nih.gov/pubmed/22070249
http://dx.doi.org/10.1186/1471-2105-12-436
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author Morris, John H
Apeltsin, Leonard
Newman, Aaron M
Baumbach, Jan
Wittkop, Tobias
Su, Gang
Bader, Gary D
Ferrin, Thomas E
author_facet Morris, John H
Apeltsin, Leonard
Newman, Aaron M
Baumbach, Jan
Wittkop, Tobias
Su, Gang
Bader, Gary D
Ferrin, Thomas E
author_sort Morris, John H
collection PubMed
description BACKGROUND: In the post-genomic era, the rapid increase in high-throughput data calls for computational tools capable of integrating data of diverse types and facilitating recognition of biologically meaningful patterns within them. For example, protein-protein interaction data sets have been clustered to identify stable complexes, but scientists lack easily accessible tools to facilitate combined analyses of multiple data sets from different types of experiments. Here we present clusterMaker, a Cytoscape plugin that implements several clustering algorithms and provides network, dendrogram, and heat map views of the results. The Cytoscape network is linked to all of the other views, so that a selection in one is immediately reflected in the others. clusterMaker is the first Cytoscape plugin to implement such a wide variety of clustering algorithms and visualizations, including the only implementations of hierarchical clustering, dendrogram plus heat map visualization (tree view), k-means, k-medoid, SCPS, AutoSOME, and native (Java) MCL. RESULTS: Results are presented in the form of three scenarios of use: analysis of protein expression data using a recently published mouse interactome and a mouse microarray data set of nearly one hundred diverse cell/tissue types; the identification of protein complexes in the yeast Saccharomyces cerevisiae; and the cluster analysis of the vicinal oxygen chelate (VOC) enzyme superfamily. For scenario one, we explore functionally enriched mouse interactomes specific to particular cellular phenotypes and apply fuzzy clustering. For scenario two, we explore the prefoldin complex in detail using both physical and genetic interaction clusters. For scenario three, we explore the possible annotation of a protein as a methylmalonyl-CoA epimerase within the VOC superfamily. Cytoscape session files for all three scenarios are provided in the Additional Files section. CONCLUSIONS: The Cytoscape plugin clusterMaker provides a number of clustering algorithms and visualizations that can be used independently or in combination for analysis and visualization of biological data sets, and for confirming or generating hypotheses about biological function. Several of these visualizations and algorithms are only available to Cytoscape users through the clusterMaker plugin. clusterMaker is available via the Cytoscape plugin manager.
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spelling pubmed-32628442012-01-21 clusterMaker: a multi-algorithm clustering plugin for Cytoscape Morris, John H Apeltsin, Leonard Newman, Aaron M Baumbach, Jan Wittkop, Tobias Su, Gang Bader, Gary D Ferrin, Thomas E BMC Bioinformatics Software BACKGROUND: In the post-genomic era, the rapid increase in high-throughput data calls for computational tools capable of integrating data of diverse types and facilitating recognition of biologically meaningful patterns within them. For example, protein-protein interaction data sets have been clustered to identify stable complexes, but scientists lack easily accessible tools to facilitate combined analyses of multiple data sets from different types of experiments. Here we present clusterMaker, a Cytoscape plugin that implements several clustering algorithms and provides network, dendrogram, and heat map views of the results. The Cytoscape network is linked to all of the other views, so that a selection in one is immediately reflected in the others. clusterMaker is the first Cytoscape plugin to implement such a wide variety of clustering algorithms and visualizations, including the only implementations of hierarchical clustering, dendrogram plus heat map visualization (tree view), k-means, k-medoid, SCPS, AutoSOME, and native (Java) MCL. RESULTS: Results are presented in the form of three scenarios of use: analysis of protein expression data using a recently published mouse interactome and a mouse microarray data set of nearly one hundred diverse cell/tissue types; the identification of protein complexes in the yeast Saccharomyces cerevisiae; and the cluster analysis of the vicinal oxygen chelate (VOC) enzyme superfamily. For scenario one, we explore functionally enriched mouse interactomes specific to particular cellular phenotypes and apply fuzzy clustering. For scenario two, we explore the prefoldin complex in detail using both physical and genetic interaction clusters. For scenario three, we explore the possible annotation of a protein as a methylmalonyl-CoA epimerase within the VOC superfamily. Cytoscape session files for all three scenarios are provided in the Additional Files section. CONCLUSIONS: The Cytoscape plugin clusterMaker provides a number of clustering algorithms and visualizations that can be used independently or in combination for analysis and visualization of biological data sets, and for confirming or generating hypotheses about biological function. Several of these visualizations and algorithms are only available to Cytoscape users through the clusterMaker plugin. clusterMaker is available via the Cytoscape plugin manager. BioMed Central 2011-11-09 /pmc/articles/PMC3262844/ /pubmed/22070249 http://dx.doi.org/10.1186/1471-2105-12-436 Text en Copyright © 2011 Morris et al; licensee BioMed Central Ltd. https://creativecommons.org/licenses/by/2.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0 (https://creativecommons.org/licenses/by/2.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software
Morris, John H
Apeltsin, Leonard
Newman, Aaron M
Baumbach, Jan
Wittkop, Tobias
Su, Gang
Bader, Gary D
Ferrin, Thomas E
clusterMaker: a multi-algorithm clustering plugin for Cytoscape
title clusterMaker: a multi-algorithm clustering plugin for Cytoscape
title_full clusterMaker: a multi-algorithm clustering plugin for Cytoscape
title_fullStr clusterMaker: a multi-algorithm clustering plugin for Cytoscape
title_full_unstemmed clusterMaker: a multi-algorithm clustering plugin for Cytoscape
title_short clusterMaker: a multi-algorithm clustering plugin for Cytoscape
title_sort clustermaker: a multi-algorithm clustering plugin for cytoscape
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3262844/
https://www.ncbi.nlm.nih.gov/pubmed/22070249
http://dx.doi.org/10.1186/1471-2105-12-436
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