Statistical methods for microarray-based gene set analysis

Sarah Song
University of Auckland

The analysis of gene sets has become a popular topic in recent times, with researchers attempting to improve the interpretability of their microarray analyses through the inclusion of supplementary biological information. While a number of options for gene set analysis exist, most do not incorporate inter-gene correlation information, despite the fact that such correlations are known to be biologically relevant. In this talk the characteristics of some of the most widely used gene set analysis methods will be examined, based on their performance in both simulated and real data sets. In particular the importance of incorporating correlation information into the analysis process will be investigated.

Session 3a, Statistical Genomics: 10:50 — 11:10, Room 445

Presentation Program