Genomics and Bioinformatics Group Genomics and Bioinformatics Group Genomics and Bioinformatics Group
Genomics and Bioinformatics Group

2011 Publication

Genomics and Bioinformatics Group
   Home
  Publications
      2012
      2011
      2010
      2009
      2008
      2007
      2006
      2005
      2004
      2003
      2002
      2001
      2000
      1999
      Before 1999
      Selected
   Tools
   Data Sets
   Molec Maps
   μA Analysis
   Members
   Links
   Contact
   Search
   LMP Home
 

RedundancyMiner: De-replication of redundant GO categories in microarray and proteomics analysis.

Barry R Zeeberg, Hongfang Liu, Ari B Kahn, Martin Ehler, Vinodh N Rajapakse, Robert F Bonner, Jacob D Brown, Brian P Brooks, Vladimir L Larionov, William Reinhold, John N Weinstein and Yves G Pommier.

BMC Bioinformatics 2011, 12:52doi:10.1186/1471-2105-12-52

Read article in journal

Abstract:

Background

The Gene Ontology (GO) Consortium organizes genes into hierarchical categories based on biological process, molecular function and subcellular localization. Tools such as GoMiner can leverage GO to perform ontological analysis of microarray and proteomics studies, typically generating a list of significant functional categories. Two or more of the categories are often redundant, in the sense that identical or nearly-identical sets of genes map to the categories. The redundancy might typically inflate the report of significant categories by a factor of three-fold, create an illusion of an overly long list of significant categories, and obscure the relevant biological interpretation.

Results

We now introduce a new resource, RedundancyMiner, that de-replicates the redundant and nearly-redundant GO categories that had been determined by first running GoMiner. The main algorithm of RedundancyMiner, MultiClust, performs a novel form of cluster analysis in which a GO category might belong to several category clusters. Each category cluster follows a "complete linkage" paradigm. The metric is a similarity measure that captures the overlap in gene mapping between pairs of categories.

Conclusions

RedundancyMiner effectively eliminated redundancies from a set of GO categories. For illustration, we have applied it to the clarification of the results arising from two current studies: (1) assessment of the gene expression profiles obtained by laser capture microdissection (LCM) of serial cryosections of the retina at the site of final optic fissure closure in the mouse embryos at specific embryonic stages, and (2) analysis of a conceptual data set obtained by examining a list of genes deemed to be "kinetochore" genes.


Genomics and Bioinformatics Group Home Page Link to Center for Cancer Research Home Page Link to National Cancer Institute Home Page Link to National Institutes of Health Link to Department of Health & Human Services Home Page