Gene set analysis is  described in the paper
by Efron and Tibshirani (2006):
<br>
<a href="http://statistics.stanford.edu/~tibs/ftp/GSA.ps"> On testing the significance of sets of genes (ps file) </a>
<br>
<a href="http://statistics.stanford.edu/~tibs/ftp/GSA.pdf"> (pdf file) </a>


<br>
<br>
<li> 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
value.
<br>
<br>
<li>  Efron and Tibshirani shows that this is often more powerful
than the modified Kolmogorov-Smirnov statistic used in GSEA.
<br>
<br>
<li>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).
<br>
<br>
<li>GSA also can handle phenotypes other than two groups, such as
multiple classes, survival times and quantitative outcomes.