TY - JOUR
T1 - Pathway Distiller - multisource biological pathway consolidation.
AU - Doderer, Mark S.
AU - Anguiano, Zachry
AU - Suresh, Uthra
AU - Dashnamoorthy, Ravi
AU - Bishop, Alexander J.R.
AU - Chen, Yidong
N1 - Funding Information:
Based on “Multisource biological pathway consolidation”, by Mark S Doderer, Zachry Anguiano, Uthra Suresh, Ravi Dashnamoorthy, Alexander JR Bishop and Yidong Chen which appeared in Genomic Signal Processing and Statistics (GENSIPS), 2011 IEEE International Workshop on. © 2011 IEEE [30]. This work was supported by the NIEHS (K22-ES12264) and a Voelcker Fund Young Investigator Award from the Max and Minnie Tomerlin Voelcker Fund to A.J.R. Bishop; Y. Chen is supported by NIH/NCI cancer center grant (P30 CA054174-17), NIH/NCRR CTSA grant (1UL1RR025767), Cancer Prevention and Research Institute of Texas grant (CPRITRP101195-C04), and partially supported by a Voelcker Fund Young Investigator Award from the Max and Minnie Tomerlin Voelcker Fund; Both A.J.R. Bishop and Y. Chen are supported by NCI grant (1R01CA152063-02); MSD is supported by the Greehey Children Cancer Research Institute (GCCRI) intramural research fund; AZ is supported by GCCRI’s summer internship program. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. This article has been published as part of BMC Genomics Volume 13 Supplement 6, 2012: Selected articles from the IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS) 2011. The full contents of the supplement are available online at http://www. biomedcentral.com/bmcgenomics/supplements/13/S6.
PY - 2012
Y1 - 2012
N2 - One method to understand and evaluate an experiment that produces a large set of genes, such as a gene expression microarray analysis, is to identify overrepresentation or enrichment for biological pathways. Because pathways are able to functionally describe the set of genes, much effort has been made to collect curated biological pathways into publicly accessible databases. When combining disparate databases, highly related or redundant pathways exist, making their consolidation into pathway concepts essential. This will facilitate unbiased, comprehensive yet streamlined analysis of experiments that result in large gene sets. After gene set enrichment finds representative pathways for large gene sets, pathways are consolidated into representative pathway concepts. Three complementary, but different methods of pathway consolidation are explored. Enrichment Consolidation combines the set of the pathways enriched for the signature gene list through iterative combining of enriched pathways with other pathways with similar signature gene sets; Weighted Consolidation utilizes a Protein-Protein Interaction network based gene-weighting approach that finds clusters of both enriched and non-enriched pathways limited to the experiments' resultant gene list; and finally the de novo Consolidation method uses several measurements of pathway similarity, that finds static pathway clusters independent of any given experiment. We demonstrate that the three consolidation methods provide unified yet different functional insights of a resultant gene set derived from a genome-wide profiling experiment. Results from the methods are presented, demonstrating their applications in biological studies and comparing with a pathway web-based framework that also combines several pathway databases. Additionally a web-based consolidation framework that encompasses all three methods discussed in this paper, Pathway Distiller (http://cbbiweb.uthscsa.edu/PathwayDistiller), is established to allow researchers access to the methods and example microarray data described in this manuscript, and the ability to analyze their own gene list by using our unique consolidation methods. By combining several pathway systems, implementing different, but complementary pathway consolidation methods, and providing a user-friendly web-accessible tool, we have enabled users the ability to extract functional explanations of their genome wide experiments.
AB - One method to understand and evaluate an experiment that produces a large set of genes, such as a gene expression microarray analysis, is to identify overrepresentation or enrichment for biological pathways. Because pathways are able to functionally describe the set of genes, much effort has been made to collect curated biological pathways into publicly accessible databases. When combining disparate databases, highly related or redundant pathways exist, making their consolidation into pathway concepts essential. This will facilitate unbiased, comprehensive yet streamlined analysis of experiments that result in large gene sets. After gene set enrichment finds representative pathways for large gene sets, pathways are consolidated into representative pathway concepts. Three complementary, but different methods of pathway consolidation are explored. Enrichment Consolidation combines the set of the pathways enriched for the signature gene list through iterative combining of enriched pathways with other pathways with similar signature gene sets; Weighted Consolidation utilizes a Protein-Protein Interaction network based gene-weighting approach that finds clusters of both enriched and non-enriched pathways limited to the experiments' resultant gene list; and finally the de novo Consolidation method uses several measurements of pathway similarity, that finds static pathway clusters independent of any given experiment. We demonstrate that the three consolidation methods provide unified yet different functional insights of a resultant gene set derived from a genome-wide profiling experiment. Results from the methods are presented, demonstrating their applications in biological studies and comparing with a pathway web-based framework that also combines several pathway databases. Additionally a web-based consolidation framework that encompasses all three methods discussed in this paper, Pathway Distiller (http://cbbiweb.uthscsa.edu/PathwayDistiller), is established to allow researchers access to the methods and example microarray data described in this manuscript, and the ability to analyze their own gene list by using our unique consolidation methods. By combining several pathway systems, implementing different, but complementary pathway consolidation methods, and providing a user-friendly web-accessible tool, we have enabled users the ability to extract functional explanations of their genome wide experiments.
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U2 - 10.1186/1471-2164-13-s6-s18
DO - 10.1186/1471-2164-13-s6-s18
M3 - Article
C2 - 23134636
AN - SCOPUS:84876090381
SN - 1471-2164
VL - 13 Suppl 6
JO - BMC genomics
JF - BMC genomics
ER -