Gene set analysis is described in the paper
by Efron and Tibshirani (2006):
It differs from a Gene Set Enrichment Analysis
(Subramanian et al 2006)
in its use of the "maxmean" statistic: this is the mean of the positive or
negative part of gene scores in the gene set, whichever is larger in absolute
On testing the significance of sets of genes (ps file)
Efron and Tibshirani shows that this is often more powerful
than the modified Kolmogorov-Smirnov statistic used in GSEA.
GSA also uses a somewhat different null distribution for estimation
of false discovery rates: it does "restandardization" of the genes (rows), in addition of the
permutation of columns (done in GSEA),
unlike GSEA (currently).
GSA also can handle phenotypes other than two groups, such as
multiple classes, survival times and quantitative outcomes.