Affy Normalization!
3
0
Entering edit mode
Puhong Gao ▴ 140
@puhong-gao-116
Last seen 9.7 years ago
Hi, all, To reduce the data size before quantile normalization, I am thinking to take PM intensity only (to solve memory problem). Is there a way to separate pm and mm data while the affybatch format is still perserved? If yes, is it appropriate to normalize the data based on the PM values only? Thanks in advance for your inputs. Data: from 150 u34a chips Computer: Windows XP pro with 2 GB of RAM Regards, Puhong Gao, PhD Dev. Psychobiology NYSPI, Unit# 40 1051 Riverside Dr. New York, NY 10032 (212) 543-5710 [[alternate HTML version deleted]]
Normalization Normalization • 867 views
ADD COMMENT
0
Entering edit mode
@rafael-a-irizarry-205
Last seen 9.7 years ago
thats what quantile normalization does by default. to get the pms use the method: pm the function justRMA uses only pms and takes advantage of this to save on memory. you can look at the code for some hints. On Tue, 10 Jun 2003, Puhong Gao wrote: > Hi, all, > > To reduce the data size before quantile normalization, I am thinking to take PM intensity only (to solve memory problem). Is there a way to separate pm and mm data while the affybatch format is still perserved? If yes, is it appropriate to normalize the data based on the PM values only? Thanks in advance for your inputs. > > Data: from 150 u34a chips Computer: Windows XP pro with 2 GB of RAM > > Regards, > > Puhong Gao, PhD > Dev. Psychobiology > NYSPI, Unit# 40 > 1051 Riverside Dr. > New York, NY 10032 > (212) 543-5710 > [[alternate HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor >
ADD COMMENT
0
Entering edit mode
Puhong Gao ▴ 140
@puhong-gao-116
Last seen 9.7 years ago
Rafael, Thank you very much for your input. I thought that, though quantile nomalization only uses pm values by default, it will read in both pm and mm values. I would love to test justRMA. But here is my dilemma. justRMA function is available in R; but I have tried unsuccessfully to get the 150 cel files into R. I managed to get the 150 cel files read into S-Plus ArrayAnalyzer (no problem); but justRMA is not included in the ArrayAnalyzer. Any suggestions? Is it possible to somehow port justRMA function to S-plus? Thanks. Regards, Puhong ----- Original Message ----- From: "Rafael A. Irizarry" <ririzarr@jhsph.edu> To: "Puhong Gao" <pgao@hunter.cuny.edu> Cc: <bioconductor@stat.math.ethz.ch> Sent: Tuesday, June 10, 2003 1:45 PM Subject: Re: [BioC] Affy Normalization! > thats what quantile normalization does by default. to get the pms use the > method: pm > > the function justRMA uses only pms and takes advantage of this to save on > memory. you can look at the code for some hints. > > On Tue, 10 Jun 2003, Puhong > Gao wrote: > > > Hi, all, > > > > To reduce the data size before quantile normalization, I am thinking to > take PM intensity only (to solve memory problem). Is there a way to > separate pm and mm data while the affybatch format is still perserved? If > yes, is it appropriate to normalize the data based on the PM values only? > Thanks in advance for your inputs. > > > > Data: from 150 u34a chips Computer: Windows XP pro with 2 GB of RAM > > > > Regards, > > > > Puhong Gao, PhD > > Dev. Psychobiology > > NYSPI, Unit# 40 > > 1051 Riverside Dr. > > New York, NY 10032 > > (212) 543-5710 > > [[alternate HTML version deleted]] > > > > _______________________________________________ > > Bioconductor mailing list > > Bioconductor@stat.math.ethz.ch > > https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor > > >
ADD COMMENT
0
Entering edit mode
you might want to try it again avoiding the use of ReadAffy or read.affybatch. by never creating an AffyBatch and reading only a pm matrix you make a smaller object. as pointed out by james, this is what justRMA does. if you want RMA values and dont necesarily want to work within R/Bioconductor you might consider using: http://stat-www.berkeley.edu/users/bolstad/RMAExpress/RMAExpress.html On Tue, 10 Jun 2003, Puhong Gao wrote: > Rafael, > > Thank you very much for your input. I thought that, though quantile > nomalization only uses pm values by default, it will read in both pm and mm > values. > > I would love to test justRMA. But here is my dilemma. justRMA function is > available in R; but I have tried unsuccessfully to get the 150 cel files > into R. I managed to get the 150 cel files read into S-Plus ArrayAnalyzer > (no problem); but justRMA is not included in the ArrayAnalyzer. Any > suggestions? Is it possible to somehow port justRMA function to S-plus? > Thanks. > > Regards, > > Puhong > > ----- Original Message ----- > From: "Rafael A. Irizarry" <ririzarr@jhsph.edu> > To: "Puhong Gao" <pgao@hunter.cuny.edu> > Cc: <bioconductor@stat.math.ethz.ch> > Sent: Tuesday, June 10, 2003 1:45 PM > Subject: Re: [BioC] Affy Normalization! > > > > thats what quantile normalization does by default. to get the pms use the > > method: pm > > > > the function justRMA uses only pms and takes advantage of this to save on > > memory. you can look at the code for some hints. > > > > On Tue, 10 Jun 2003, Puhong > > Gao wrote: > > > > > Hi, all, > > > > > > To reduce the data size before quantile normalization, I am thinking to > > take PM intensity only (to solve memory problem). Is there a way to > > separate pm and mm data while the affybatch format is still perserved? If > > yes, is it appropriate to normalize the data based on the PM values only? > > Thanks in advance for your inputs. > > > > > > Data: from 150 u34a chips Computer: Windows XP pro with 2 GB of RAM > > > > > > Regards, > > > > > > Puhong Gao, PhD > > > Dev. Psychobiology > > > NYSPI, Unit# 40 > > > 1051 Riverside Dr. > > > New York, NY 10032 > > > (212) 543-5710 > > > [[alternate HTML version deleted]] > > > > > > _______________________________________________ > > > Bioconductor mailing list > > > Bioconductor@stat.math.ethz.ch > > > https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor > > > > > > >
ADD REPLY
0
Entering edit mode
Puhong Gao ▴ 140
@puhong-gao-116
Last seen 9.7 years ago
Rafael, Thank you very much for your help. Puhong
ADD COMMENT

Login before adding your answer.

Traffic: 604 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