4.8 Article

ToppCluster: a multiple gene list feature analyzer for comparative enrichment clustering and network-based dissection of biological systems

期刊

NUCLEIC ACIDS RESEARCH
卷 38, 期 -, 页码 W96-W102

出版社

OXFORD UNIV PRESS
DOI: 10.1093/nar/gkq418

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资金

  1. National Institutes of Health/National Institute of Diabetes and Digestive and Kidney Diseases (NIH/NIDDK) [1U01 DK70219]
  2. PHS (Cincinnati Digestive Health Center) [P30 DK078392]
  3. CTSA: Cincinnati Center for Clinical and Translational Sciences [U54 RR025216]
  4. NIDCR (FACEBASE Consortium) [U01DE020049]
  5. National Institutes of Health

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ToppCluster is a web server application that lever-ages a powerful enrichment analysis and underlying data environment for comparative analyses of multiple gene lists. It generates heatmaps or connectivity networks that reveal functional features shared or specific to multiple gene lists. ToppCluster uses hypergeometric tests to obtain list-specific feature enrichment P-values for currently 17 categories of annotations of human-ortholog genes, and provides user-selectable cutoffs and multiple testing correction methods to control false discovery. Each nameable gene list represents a column input to a resulting matrix whose rows are overrepresented features, and individual cells per-list P-values and corresponding genes per feature. ToppCluster provides users with choices of tabular outputs, hierarchical clustering and heatmap generation, or the ability to interactively select features from the functional enrichment matrix to be transformed into XGMML or GEXF network format documents for use in Cytoscape or Gephi applications, respectively. Here, as example, we demonstrate the ability of ToppCluster to enable identification of list-specific phenotypic and regulatory element features (both cis-elements and 3'UTR microRNA binding sites) among tissue-specific gene lists. ToppCluster's functionalities enable the identification of specialized biological functions and regulatory networks and systems biology-based dissection of biological states. ToppCluster can be accessed freely at http://toppcluster.cchmc.org.

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