Hi Richard, Thank you so much for the helpful information. S-Score seems like very useful algorithm for microarray analysis currently. I suppose, it will be very useful when multivariate version comes out. Thank you again for your help and time, S --- Richard Kennedy <rkennedy at="" vcu.edu=""> wrote: > Saurin, > The S-Score is an algorithm for analyzing microarray > data, originally > developed in Michael Miles' laboratory at UCSF (by > Li Zhang, currently > at MD Anderson Cancer Center). Dr. Miles has since > relocated to our > institution, and we are working as a group on the > S-Score. > > As Adaikalavan notes, the S-Score has not been > heavily publicized, which > may account in part for the lack of widespread use. > However, since the > release of Dr. Miles' Journal of Neuroscience paper > (Kerns et al, J > Neurosci 2005, 25(9):2255-2266), we have been seeing > increasing > interest. The S-Score does have some rather > interesting features, with > the main one being that it performs tests of > hypotheses directly from > the probe level data. The usual steps in analysis > require that a probe > set summary measure be generated, and statistical > tests are performed on > the summaries. Under conditions of no differential > expression, the > S-Scores follow a standard normal distribution; this > means that > hypothesis testing can be done directly with the > S-Scores, without an > intermediate expression summary measure. > > There are, of course, some limitations with the > S-Score as well. The > software had previously been available only as a > compiled stand-alone > program for Windows (at > http:www.brainchip.vcu.edu/expressionda.html) so > it took a few steps to combine it with an > environment such as R. > However, we have been working on an R implementation > which, as Seth > noted, should be posted in the near future. This > initial release is > just a straight port of the Windows version to R; it > does not add any > new features, but does make it easier to interface > with the other > Bioconductor packages. Another principal limitation > of the S-Score is > that the software performs comparisons two chips at > a time. We are now > working on a multivariate version for direct > multi-chip comparisons, but > have not set a definite timeframe for its release. > > The main reference for the S-Score is Zhang et al, J > Mol Biol 2002, > 317:225-235 that describes some of the original > development; Dr. Miles > has also used the S-Score in several peer-reviewed > publications. We are > in the process of submitting an article on > additional validation studies > of the S-Score (which did rather well compared to > other methods) and an > applications note for the R implementation. > > Hope this has been helpful - we are definitely > interested in making the > S-Score more widely available. > > Richard Kennedy > Kellie J. Archer > Department of Biostatistics > Virginia Commonwealth University > > > > Saurin Jani wrote: > > >Dear BioC, > > > >Have any one used S-Score algorithm in order to > >analyze microarray data and extracted diff. > expressed > >genes ? Or is it useful to use use...RMA -> do > t-test > >get p-valule -> and do FDR (BH) --> extract diff. > >expressed genes? > > > >why S-score is not in much of use? like T-test > pvalue > >and BH FDR..which is OK to use? > > > >Thank you so much in advance, > >S > > > >_______________________________________________ > >Bioconductor mailing list > >Bioconductor at stat.math.ethz.ch > >https://stat.ethz.ch/mailman/listinfo/bioconductor > > >