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An application of gene set analysis for a comparison of two groups

  • Author / Creator
    Meng, Ya
  • Microarrays are biotechnological advancements measuring expressions of thousands of genes in a single assay. A two-group microarray study yields gene expression measurements for patients with a disease of interest and for healthy controls. Our objective is to apply the methods of microarray data analysis to kidney transplant patients. We apply Significance Analysis of Microarray (SAM) to explore genes differentially expressed between the two groups at the gene level but the results yield thousands of significant genes which are hard to interpret. Therefore, we then present the two top analysis methods at a gene set level, called Significance Analysis of Microarrays for Gene Sets (SAM-GS) and Multivariate Analysis of Variance for Gene Sets (MANOVA-GSA). False Discovery Rates are calculated to address multiple hypothesis testing. As a result, we found 957 significant genes with FDR values smaller than 5.71%. SAM-GS identified 58 pathways with p-value < 0.001.

  • Subjects / Keywords
  • Graduation date
    2011-11
  • Type of Item
    Thesis
  • Degree
    Master of Science
  • DOI
    https://doi.org/10.7939/R3088N
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Master's
  • Department
    • Department of Mathematical and Statistical Sciences
  • Supervisor / co-supervisor and their department(s)
    • Doug Wiens (Mathematical and Statistical Sciences)
  • Examining committee members and their departments
    • Giseon Heo (Dentistry)
    • Irina Dinu (Public Health)