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| #445 | Functional Analysis of Microarray Data Using Gene Set Enrichment Analysis Methods |
| Description: | |
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Gene Set Enrichment Analysis (GSEA) is a pioneering method in the analysis of genome-wide expression profiles that enhances biological interpretation and gains statistical power by examining expression values of sets of genes having known collective functions or properties. GSEA detects differentially regulated functional gene sets in a coherent manner to gain insight into biological mechanisms and eases the interpretation of large scale experiments by identifying relevant functional pathways and biological processes. In general, it is more sensitive in detecting significant modest correlated changes in members of a biological gene set than methods which operate by making decisions about the significance of changes for each individual gene. Course materials are available: Presentation. | |
| Objectives: | |
Topics to be covered include
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| Who should attend: | |
| NIH staff with an interest in microarray data analysis. Basic knowledge of statistics and R is desirable. | |
| Instructor(s): | |
| Alan E. Berger, Ph.D., Lowe Family Genomics Core, Johns Hopkins University School of Medicine | |
| Time Required: | |
| 3 hours | |
| Sections Available: | ||||
| -- Concluded -- | 445-09F | October 31 | 1:00 - 4:00 | Building 12A, Room B51 |
| NOTE: Although this course has already taken place, we'll put you on a waiting list for the next available session. |
Course Listing
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