ERRORS IN LIWONG EXPRESSION VALUES.
2
0
Entering edit mode
@stephen-nyangoma-366
Last seen 9.7 years ago
Dear All, I want to obtain expression values based on my data using Li-Wong method. I gave the following command liwongexpre<-expresso(Data2,normalize.method="invariantset",bg.correct =FALSE, pmcorrect.method="pmonly",summary.method="liwong") It looks like I do not attain convergence. Is may call function ok? > Data2 AffyBatch object size of arrays=640x640 features (12803 kb) cdf=MG_U74Av2 (12488 affyids) number of samples=4 number of genes=12488 annotation=mgu74av2 > Data2<-ReadAffy(filenames=c("../M7SS02080619.CEL","../M7SS02080607.CEL ") > colnames(exprs(Data2))<- c("BXD5a","BXD9a") > liwongexpre<-expresso(Data2,normalize.method="invariantset",bg.correct =FALSE,pmcorrect.method="pmonly",summary.method="liwong") normalization: invariantset PM/MM correction : pmonly expression values: liwong normalizing...done. 12488 ids to be processed ......... There were 50 or more warnings (use warnings() to see the first 50) > warnings() Warning messages: 1: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 2: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 3: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 4: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 5: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 6: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 7: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 8: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 9: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 10: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 11: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 12: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 13: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 14: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 15: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 16: No convergence achieved, too many outliers in: fit.li.wong(probes, ...)
• 1.0k views
ADD COMMENT
0
Entering edit mode
@james-w-macdonald-5106
Last seen 2 days ago
United States
I think your function call is correct. Unfortunately, the implementation of Li and Wong's invariantset method in affy sometimes doesn't converge due to outliers (as mentioned in the warnings). I don't think there is anything you can do about it except: a.) Give up on liwong and use rma, which is a better method anyway b.) Use dChip, which doesn't have the convergence problems. Jim James W. MacDonald Affymetrix and cDNA Microarray Core University of Michigan Cancer Center 1500 E. Medical Center Drive 7410 CCGC Ann Arbor MI 48109 734-647-5623 >>> Stephen Nyangoma <s.nyangoma@cs.rug.nl> 08/21/03 07:51AM >>> Dear All, I want to obtain expression values based on my data using Li-Wong method. I gave the following command liwongexpre<-expresso(Data2,normalize.method="invariantset",bg.correct =FALSE, pmcorrect.method="pmonly",summary.method="liwong") It looks like I do not attain convergence. Is may call function ok? > Data2 AffyBatch object size of arrays=640x640 features (12803 kb) cdf=MG_U74Av2 (12488 affyids) number of samples=4 number of genes=12488 annotation=mgu74av2 > Data2<-ReadAffy(filenames=c("../M7SS02080619.CEL","../M7SS02080607.CEL ") > colnames(exprs(Data2))<- c("BXD5a","BXD9a") > liwongexpre<-expresso(Data2,normalize.method="invariantset",bg.correct =FALSE,pmcorrect.method="pmonly",summary.method="liwong") normalization: invariantset PM/MM correction : pmonly expression values: liwong normalizing...done. 12488 ids to be processed ......... There were 50 or more warnings (use warnings() to see the first 50) > warnings() Warning messages: 1: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 2: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 3: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 4: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 5: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 6: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 7: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 8: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 9: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 10: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 11: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 12: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 13: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 14: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 15: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) 16: No convergence achieved, too many outliers in: fit.li.wong(probes, ...) _______________________________________________ Bioconductor mailing list Bioconductor@stat.math.ethz.ch https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor
ADD COMMENT
0
Entering edit mode
Thanks Jim, for clarifying. I will ask for dChip if necessary. Otherwise I will use rma. Steve. On Thu, 2003-08-21 at 14:57, James MacDonald wrote: > I think your function call is correct. Unfortunately, the implementation > of Li and Wong's invariantset method in affy sometimes doesn't converge > due to outliers (as mentioned in the warnings). I don't think there is > anything you can do about it except: > > a.) Give up on liwong and use rma, which is a better method anyway > > b.) Use dChip, which doesn't have the convergence problems. > > Jim > > > > James W. MacDonald > Affymetrix and cDNA Microarray Core > University of Michigan Cancer Center > 1500 E. Medical Center Drive > 7410 CCGC > Ann Arbor MI 48109 > 734-647-5623 > > >>> Stephen Nyangoma <s.nyangoma@cs.rug.nl> 08/21/03 07:51AM >>> > Dear All, > I want to obtain expression values based on my data using Li-Wong > method. I gave the following command > > liwongexpre<-expresso(Data2,normalize.method="invariantset",bg.corre ct=FALSE, > pmcorrect.method="pmonly",summary.method="liwong") > > It looks like I do not attain convergence. Is may call function ok? > > > > Data2 > AffyBatch object > size of arrays=640x640 features (12803 kb) > cdf=MG_U74Av2 (12488 affyids) > number of samples=4 > number of genes=12488 > annotation=mgu74av2 > > > > > Data2<-ReadAffy(filenames=c("../M7SS02080619.CEL","../M7SS02080607.C EL") > > > colnames(exprs(Data2))<- c("BXD5a","BXD9a") > > > liwongexpre<-expresso(Data2,normalize.method="invariantset",bg.corre ct=FALSE,pmcorrect.method="pmonly",summary.method="liwong") > normalization: invariantset > PM/MM correction : pmonly > expression values: liwong > normalizing...done. > 12488 ids to be processed > ......... > There were 50 or more warnings (use warnings() to see the first 50) > > > > warnings() > Warning messages: > 1: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 2: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 3: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 4: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 5: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 6: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 7: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 8: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 9: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 10: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 11: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 12: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 13: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 14: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 15: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 16: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor
ADD REPLY
0
Entering edit mode
@rafael-a-irizarry-205
Last seen 9.7 years ago
i dont know how dChip deals with it (its not open source), but the algrotihm described in their paper doest always converge. its a mathematical reality not necessarily an error with bioconductor code. On Thu, 21 Aug 2003, Stephen Nyangoma wrote: > Dear All, > I want to obtain expression values based on my data using Li-Wong > method. I gave the following command > > liwongexpre<-expresso(Data2,normalize.method="invariantset",bg.corre ct=FALSE, > pmcorrect.method="pmonly",summary.method="liwong") > > It looks like I do not attain convergence. Is may call function ok? > > > > Data2 > AffyBatch object > size of arrays=640x640 features (12803 kb) > cdf=MG_U74Av2 (12488 affyids) > number of samples=4 > number of genes=12488 > annotation=mgu74av2 > > > > > Data2<-ReadAffy(filenames=c("../M7SS02080619.CEL","../M7SS02080607.C EL") > > > colnames(exprs(Data2))<- c("BXD5a","BXD9a") > > > liwongexpre<-expresso(Data2,normalize.method="invariantset",bg.corre ct=FALSE,pmcorrect.method="pmonly",summary.method="liwong") > normalization: invariantset > PM/MM correction : pmonly > expression values: liwong > normalizing...done. > 12488 ids to be processed > ......... > There were 50 or more warnings (use warnings() to see the first 50) > > > > warnings() > Warning messages: > 1: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 2: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 3: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 4: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 5: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 6: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 7: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 8: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 9: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 10: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 11: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 12: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 13: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 14: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 15: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > 16: No convergence achieved, too many outliers in: fit.li.wong(probes, > ...) > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor >
ADD COMMENT

Login before adding your answer.

Traffic: 513 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