Hello,

first of all, I have to apologize for this slight off topic posting ... - 
but I could not find a better place to ask this question ;-), well, it's 
not really a question but more of a brainstorming.

I was (unsuccessfully) looking for some literature that reports the 
comparison of classical gene-centric versus gene set enrichment or 
over-representation analysis (biological functions such as in GO, KEGG etc 
...). There are plenty of papers that describe specific tools and methods 
for finding potentially impacted biological functions in microarray 
experiments. However, I so far I couldn't find any literature that 
rigorously compares the classification performance (e.g. via some standard 
machine learning method) of lets say treated and healthy sample groups 
based on a matrix of gene expression values or a matrix of gene sets 
(either all gene sets that one think of or a subset of that was considered 
important by a certain method such as GSEA according to a cut-off). 
Obviously there'd be many variables to be explored, and factors that could 
impact such a comparison (classification method, number of variables, 
array pro/post processing, choice of gene set database etc ... ).

I don't have any doubts that gene set analysis helps understanding the 
effects of some treatment in a microarray experiment (I use it for looking 
at my data), but does it help in automated sample classification? Can a 
small subset of "biological functions" (grouped in a few gene sets) better 
discriminate between two sample groups than all genes (or a subset) on the 
chip (I assume that it is unlikely to choose exactly the same subset of 
genes in a gene-centric analysis than in a gene set centric approach)?

Well, of course this depends on the types of gene sets defines, and we are 
aiming to reduce the data complexity as much as possible without loosing 
important information and to reduce noise. 

What'd be the most rigorous and formal analysis that has been published on 
this (one that does not necessarily has a focus on selling a specific 
method)?

 
    thanks a lot for your input,
    +kind regards,

    Arne



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