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Tutorial Details: Gene Set Analysis

Date: Tuesday, March 29, 2011, 01:00 pm - 03:00 pm
Location: 575 Walter
Instructor(s): Haoyu Yu, MSI, Dr. Michael S. Steinbach,

Analyzing the differential expression of genes, the annotation of groups of genes, or the significance of SNPs requires careful analysis in order to ensure that the resulting conclusions represent real biological phenomena and are not an artifact of random chance or a superficial statistical analysis. In this tutorial, we provide an introduction and extensive discussion of how to find functionally important groups of genes using the recently developed approach of Gene Set Enrichment Analysis (GSEA) or related techniques. An important part of this approach is a careful consideration of multiple hypothesis testing, and thus, we also discuss statistical techniques for this task, including the Bonferroni correction and false discovery rate (FDR). In addition to giving a basic conceptual introduction to these topics, we will identify the appropriate software, including MATLAB and R routines, to use to perform this type of analysis for real applications.

Prerequisites: This course requires some knowledge of SNP and microarray analysis, as well as a good understanding of basic statistical concepts. However, since the goal of the course is to give users a practical introduction in how to apply these techniques, an advanced statistical background is not necessary. Some knowledge of either MATLAB or R would be helpful.

Level:
Prerequisites: See prerequisites in description above