Imitating Affy's own steps
1
0
Entering edit mode
Timothy Wu ▴ 120
@timothy-wu-3964
Last seen 10.3 years ago
Hi, If I want to replicate as close as possible (or exactly, is it possible?) the steps of Affy's software using Bioconductor packages, from background subtraction, normalization, summarization to finding differential gene expression. What's the best way to go about doing that? I've never used Affy's own software (I'm learning microarray processing through documents for bioconductor itself), but I want to make sure I'm doing things right by taking raw data from GEO and compare to author's own published result using Affy's standard methods before I switch to GCRMA, quantile, and median polish. For data preprocessing, I notice that in Affy's package there are these options: mas for background methods mas5 for normalization mas for PM correct method mas for summarization methods So are these the steps I should take? How about for differential gene comparison? Which package should I use? Any pointer would be appreciated, thanks. :) Timothy [[alternative HTML version deleted]]
Microarray Normalization GO Preprocessing gcrma Microarray Normalization GO Preprocessing • 1.6k views
ADD COMMENT
0
Entering edit mode
@james-w-macdonald-5106
Last seen 4 hours ago
United States
Hi Timothy, AFAIK, you have two choices. Using the affy package, you can use mas5() and mas5calls(). You can also use justMAS() from the simpleaffy package. I don't believe either one will give you exactly the same results. For the affy package see http://bmbolstad.com/misc/MAS5diff/Mas5difference.html for an explanation of the differences. Best, Jim Timothy Wu wrote: > Hi, > > If I want to replicate as close as possible (or exactly, is it possible?) > the steps of Affy's software using Bioconductor packages, from background > subtraction, normalization, summarization to finding differential gene > expression. What's the best way to go about doing that? I've never used > Affy's own software (I'm learning microarray processing through documents > for bioconductor itself), but I want to make sure I'm doing things right by > taking raw data from GEO and compare to author's own published result using > Affy's standard methods before I switch to GCRMA, quantile, and median > polish. > > For data preprocessing, I notice that in Affy's package there are these > options: > mas for background methods > mas5 for normalization > mas for PM correct method > mas for summarization methods > > So are these the steps I should take? > > How about for differential gene comparison? Which package should I use? Any > pointer would be appreciated, thanks. :) > > Timothy > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor -- James W. MacDonald, M.S. Biostatistician Douglas Lab University of Michigan Department of Human Genetics 5912 Buhl 1241 E. Catherine St. Ann Arbor MI 48109-5618 734-615-7826 ********************************************************** Electronic Mail is not secure, may not be read every day, and should not be used for urgent or sensitive issues
ADD COMMENT
0
Entering edit mode
On Mon, Apr 5, 2010 at 10:24 PM, James W. MacDonald <jmacdon@med.umich.edu>wrote: > Hi Timothy, > > AFAIK, you have two choices. Using the affy package, you can use mas5() and > mas5calls(). You can also use justMAS() from the simpleaffy package. > > I don't believe either one will give you exactly the same results. For the > affy package see > > http://bmbolstad.com/misc/MAS5diff/Mas5difference.html > > for an explanation of the differences. > > Best, > > Jim > > Thanks for the reply. It looks pretty close. So is the expresso() command listed on the page * eset <- expresso(Data, bgcorrect.method="mas",normalize=FALSE,pmcorrect.method="mas",summary. method="mas") * be the same as the justMAS()? Thanks in advance. Timothy [[alternative HTML version deleted]]
ADD REPLY
0
Entering edit mode
Timothy Wu wrote: > On Mon, Apr 5, 2010 at 10:24 PM, James W. MacDonald > <jmacdon at="" med.umich.edu="">wrote: > >> Hi Timothy, >> >> AFAIK, you have two choices. Using the affy package, you can use mas5() and >> mas5calls(). You can also use justMAS() from the simpleaffy package. >> >> I don't believe either one will give you exactly the same results. For the >> affy package see >> >> http://bmbolstad.com/misc/MAS5diff/Mas5difference.html >> >> for an explanation of the differences. >> >> Best, >> >> Jim >> >> > Thanks for the reply. It looks pretty close. > > So is the expresso() command listed on the page > * > eset <- expresso(Data, > bgcorrect.method="mas",normalize=FALSE,pmcorrect.method="mas",summar y.method="mas") > * > > be the same as the justMAS()? Well, the intent is the same, but the implementation is different, so I wouldn't be surprised if there were differences there as well. Best, Jim > > Thanks in advance. > > Timothy > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor -- James W. MacDonald, M.S. Biostatistician Douglas Lab University of Michigan Department of Human Genetics 5912 Buhl 1241 E. Catherine St. Ann Arbor MI 48109-5618 734-615-7826 ********************************************************** Electronic Mail is not secure, may not be read every day, and should not be used for urgent or sensitive issues
ADD REPLY
0
Entering edit mode
I won't answer you question, because I don't know the answer, but I'd like to add that there are a few methods out there with the same names/labels. I don't know of many carefully done studies showing that the are numerically or near-numerically reproducible. If any know of such, please share them here. Though I recently discovered: Christian Stratowa, Introduction to the xps Package: Comparison to A ffymetrix Power Tools (APT), April, 2010 (vignette of the xps package) which seems to do a quite serious assessment of the methods implemented in the xps package - it includes a comparison of Affymetrix's MAS5.0 implementation with that of the xps package and the affy package. /Henrik On Mon, Apr 12, 2010 at 9:22 AM, Timothy Wu <2huggie at gmail.com> wrote: > On Mon, Apr 5, 2010 at 10:24 PM, James W. MacDonald > <jmacdon at="" med.umich.edu="">wrote: > >> Hi Timothy, >> >> AFAIK, you have two choices. Using the affy package, you can use mas5() and >> mas5calls(). You can also use justMAS() from the simpleaffy package. >> >> I don't believe either one will give you exactly the same results. For the >> affy package see >> >> http://bmbolstad.com/misc/MAS5diff/Mas5difference.html >> >> for an explanation of the differences. >> >> Best, >> >> Jim >> >> > Thanks for the reply. It looks pretty close. > > So is the expresso() command listed on the page > * > eset <- expresso(Data, > bgcorrect.method="mas",normalize=FALSE,pmcorrect.method="mas",summar y.method="mas") > * > > be the same as the justMAS()? > > Thanks in advance. > > Timothy > > ? ? ? ?[[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor >
ADD REPLY
0
Entering edit mode
Since Henrik has kindly mentioned the comparisons I did between affy, APT and xps let me make some comments, too: If you want to replicate as close as possible the results obtained with the Affymetrix software, i.e. the original "GCOS" software or the newer "Expression Console", respectively, then you need to use the command line tool APT, which you can freely download from Affymetrix. As Figure 4 of my vignette shows, the results obtained with APT are almost identical to GCOS, while both affy and xps give slightly different results for a couple of probesets. Although the reason for the difference between xps and APT is not completely clear to me there are three known differences: 1, Looking at the source code of APT you will see that all computation is done using "float", i.e. 32 bit, while in xps all computation is done using "double", i.e. 64 bit. 2, Some CEL-files contain [MASKS] and [OUTLIERS] sections which list probes to be excluded from further calculation. These probes are not excluded in xps. 3, For background computation a 4x4 grid is used. The center for each zone is determined slightly different in APT and xps. BTW, you can find the code used to obtain Fig.4 in xps/examples/script4xps2apt.R. Best regards Christian Henrik Bengtsson wrote: > I won't answer you question, because I don't know the answer, but I'd > like to add that there are a few methods out there with the same > names/labels. I don't know of many carefully done studies showing > that the are numerically or near-numerically reproducible. If any > know of such, please share them here. Though I recently discovered: > > Christian Stratowa, Introduction to the xps Package: Comparison to > A ffymetrix Power Tools (APT), April, 2010 (vignette of the xps > package) > > which seems to do a quite serious assessment of the methods > implemented in the xps package - it includes a comparison of > Affymetrix's MAS5.0 implementation with that of the xps package and > the affy package. > > /Henrik > > On Mon, Apr 12, 2010 at 9:22 AM, Timothy Wu <2huggie at gmail.com> wrote: > >> On Mon, Apr 5, 2010 at 10:24 PM, James W. MacDonald >> <jmacdon at="" med.umich.edu="">wrote: >> >> >>> Hi Timothy, >>> >>> AFAIK, you have two choices. Using the affy package, you can use mas5() and >>> mas5calls(). You can also use justMAS() from the simpleaffy package. >>> >>> I don't believe either one will give you exactly the same results. For the >>> affy package see >>> >>> http://bmbolstad.com/misc/MAS5diff/Mas5difference.html >>> >>> for an explanation of the differences. >>> >>> Best, >>> >>> Jim >>> >>> >>> >> Thanks for the reply. It looks pretty close. >> >> So is the expresso() command listed on the page >> * >> eset <- expresso(Data, >> bgcorrect.method="mas",normalize=FALSE,pmcorrect.method="mas",summa ry.method="mas") >> * >> >> be the same as the justMAS()? >> >> Thanks in advance. >> >> Timothy >> >> [[alternative HTML version deleted]] >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor at stat.math.ethz.ch >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor >> >> > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor > >
ADD REPLY

Login before adding your answer.

Traffic: 623 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6