Bussemaker reviews some current approaches.
Mootha et al published the first method (GSEA) in 2003.
Kim et al. published a method based on Normal theory. Think about what assumptions are implied by using Normal theory. Are these assumptions roughly true for gene sets? How might the method be extended to cover the case where genes within a set move in opposite directions?
Subramanian et al. published a revised version of the original GSEA method. What statistical theory inspires this method? How would you assess how good it is?
Kong et al introduced the idea of using the multivariate analogue of the t-test in order to identify significantly changed gene groups. This approach incorporates the covariance.
More papers at the Systems Biology course website