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Comparative genetic pathway analysis using structural equation Modeling

  • Xiao Wu
  • , Kathryn Sharpe
  • , Tianyi Zhang
  • , Hongyan Chen
  • , Wei Zhu
  • , Ellen Li
  • , Safiyh Taghavi
  • , Daniel Van Der Lelie
  • Stony Brook University
  • Brookhaven National Laboratory

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

In this work, we propose a novel genetic pathway discovery and comparison analysis framework integrating newly generated gene expression microarray data and existing biological pathway information. Starting with the significance analysis of microarray (SAM), a list of differentially expressed genes among groups is obtained. This gene list is then imported to the Ingenuity Pathway Analysis (IPA) to yield potentially relevant biological pathways. Finally, a newly-developed covariate structural equation modeling method is applied to evaluate gene-gene interactions and group difference. We illustrate this novel comparative pathway analysis pipeline using the whole human genome expression profiling data collected from a study of inflammatory bowel diseases (IBD) with 99 subjects from three phenotypic groups: ileal Crohn's disease (CD), ulcerative colitis (UC) and control non-IBD.

Original languageEnglish
Title of host publication2011 IEEE 1st International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2011
Pages190-195
Number of pages6
DOIs
StatePublished - 2011
Event1st IEEE International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2011 - Orlando, FL, United States
Duration: Feb 3 2011Feb 5 2011

Publication series

Name2011 IEEE 1st International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2011

Conference

Conference1st IEEE International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2011
Country/TerritoryUnited States
CityOrlando, FL
Period02/3/1102/5/11

Keywords

  • Covariate Structural Equation Modeling
  • Pathway Anlaysis
  • Significance Analysis of Microarrays

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