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      clusterProfiler: an R Package for Comparing Biological Themes Among Gene Clusters

      Author(s): 1 , 2 , 1 , 1
      Publication date Created:
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      Journal: OMICS: A Journal of Integrative Biology
      Publisher: Mary Ann Liebert Inc

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          Abstract

          Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.

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          Gene Ontology: tool for the unification of biology

          Michael Ashburner, Catherine A. Ball, Judith Blake … (2002)
          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks

            Gabriela Bindea, Bernhard Mlecnik, Hubert Hackl … (2009)
            Summary: We have developed ClueGO, an easy to use Cytoscape plug-in that strongly improves biological interpretation of large lists of genes. ClueGO integrates Gene Ontology (GO) terms as well as KEGG/BioCarta pathways and creates a functionally organized GO/pathway term network. It can analyze one or compare two lists of genes and comprehensively visualizes functionally grouped terms. A one-click update option allows ClueGO to automatically download the most recent GO/KEGG release at any time. ClueGO provides an intuitive representation of the analysis results and can be optionally used in conjunction with the GOlorize plug-in. Availability: http://www.ici.upmc.fr/cluego/cluegoDownload.shtml Contact: jerome.galon@crc.jussieu.fr Supplementary information: Supplementary data are available at Bioinformatics online.
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              A direct approach to false discovery rates

              John D. Storey (2002)
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                Author and article information

                Journal
                Title: OMICS: A Journal of Integrative Biology
                Abbreviated Title: OMICS: A Journal of Integrative Biology
                Publisher: Mary Ann Liebert Inc
                ISSN (Print): 1536-2310
                ISSN (Electronic): 1557-8100
                Publication date Created: May 2012
                Publication date (Print): May 2012
                Volume: 16
                Issue: 5
                Pages: 284-287
                Affiliations
                [1 ]Institute of Life and Health Engineering, Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes, Jinan University, Guangzhou, People's Republic of China.
                [2 ]Guangdong Information Center, Guangzhou, People's Republic of China.
                Article
                DOI: 10.1089/omi.2011.0118
                PMC ID: 3339379
                PubMed ID: 22455463
                SO-VID: b21fe860-1553-40be-a528-1bb59cec42ca
                Copyright © © 2012
                License:

                http://www.liebertpub.com/nv/resources-tools/text-and-data-mining-policy/121/

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