ToppCluster: a multiple gene list feature analyzer for comparative enrichment clustering and network-based dissection of biological systems.
ToppCluster is a web server application that leverages 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.
Kaimal
Vivek
V
Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Bardes
Eric E
EE
Tabar
Scott C
SC
Jegga
Anil G
AG
Aronow
Bruce J
BJ
D000818:Animals; D016000:Cluster Analysis; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D005796:Genes; D006801:Humans; D020407:Internet; D007668:Kidney / Q000378:metabolism; D008099:Liver / Q000378:metabolism; D051379:Mice; D035683:MicroRNAs / Q000378:metabolism; D010641:Phenotype; D012984:Software; D014157:Transcription Factors / Q000378:metabolism
D035683:MicroRNAs; D014157:Transcription Factors