how to create an affybatch
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@venkat-sundar-3560
Last seen 10.3 years ago
Dear Users, I applied different technical regression LOESS normalization methods ( using GC counts, Tm values, XY position etc.,) on HGU133A data set. Later i mapped back the X,Y positions of the probe sequences onto the 712 x 712 intensity matrix. The "pm" values later extracted (247965) from the above mapped datais in accordance with those "pm" values actually obtained by using pm function on the affybatch object. ( Just to confirm that i did right) Now, I am really having tough time to proceed further in creating an affybatch, summarization methods etc., I tried to construct manually, but lacking proper direction and basics. Can you suggest me for the same to get an initial start. Meanwhile, i tried the following trick to create an Affybatch. pm(cel.data)<-mynormpm # replacing the "pm values" in the actual affybatch object created by using ReadAffy function, with those of the normalized "pm values" obtained by # applying different normalization methods mentioned above But i still wish to learn creating an affybatch, and performing RMA summarization manually. with regards, Sundar [[alternative HTML version deleted]]
Normalization Regression hgu133a probe Normalization Regression hgu133a probe • 2.0k views
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Entering edit mode
@venkat-sundar-3560
Last seen 10.3 years ago
Dear Users, I applied different technical regression LOESS normalization methods ( using GC counts, Tm values, XY position etc.,) on HGU133A data set. Later i mapped back the X,Y positions of the probe sequences onto the 712 x 712 intensity matrix. The "pm" values later extracted (247965) from the above mapped datais in accordance with those "pm" values actually obtained by using pm function on the affybatch object. ( Just to confirm that i did right) Now, I am really having tough time to proceed further in creating an affybatch, summarization methods etc., I tried to construct manually, but lacking proper direction and basics. Can you suggest me for the same to get an initial start. Meanwhile, i tried the following trick to create an Affybatch. pm(cel.data)<-mynormpm # replacing the "pm values" in the actual affybatch object created by using ReadAffy function, with those of the normalized "pm values" obtained by # applying different normalization methods mentioned above. But i still wish to learn creating an affybatch, and performing RMA summarization manually. with regards, Sundar [[alternative HTML version deleted]]
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Hi Sundar, Venkat Sundar wrote: > Dear Users, > > I applied different technical regression LOESS normalization methods ( using GC counts, Tm values, > XY position etc.,) on HGU133A data set. > Later i mapped back the X,Y > positions of the probe sequences onto the 712 x 712 intensity matrix. > The > "pm" values later extracted (247965) from the above mapped datais in accordance with those "pm" values actually obtained by using pm function on the affybatch object. ( Just to confirm that i did right) > > Now, I am really having tough time to proceed further in creating an affybatch, summarization methods etc., > I tried to construct manually, but lacking proper direction and basics. Can you suggest me for the same to get an initial start. Sure, look at some code that creates an AffyBatch and emulate that. I would suggest read.affybatch(). Best, Jim > > Meanwhile, i tried the following trick to create an Affybatch. > > pm(cel.data)<-mynormpm > # replacing the "pm values" in the actual affybatch object created by > using ReadAffy function, with those of the normalized "pm values" > obtained by > # applying different normalization methods mentioned above. > > But i still wish to learn creating an affybatch, and performing RMA summarization manually. > > with regards, > Sundar > > > > [[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
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