Question: QuasiSeq vs DSS
0
gravatar for Richard Friedman
6.5 years ago by
Richard Friedman2.0k wrote:
Dear List. The papers on DSS (included in Bioconductor): Wu H, Wang C, Wu Z. A new shrinkage estimator for dispersion improves differential expression detection in RNA-seq data. Biostatistics. 2013 Apr;14(2):232-43. and QuasiSeq (included in CRAN): Lund SP, Nettleton D, McCarthy DJ, Smyth GK. Detecting differential expression in RNA-sequence data using quasi-likelihood with shrunken dispersion estimates. Stat Appl Genet Mol Biol. 2012 both give evidence of superior performance to edgeR (if I understand them correctly). Have the two methods been compared? Can the 2 methods been combined (with DSS estimating the dispersion used in the quasi-negative bionomial disribution used in QuasiSeq)? I would appreciate any insight with respect to what is the overall best method for differential expression in RNASeq available at present. Thanks and best wishes, Rich Richard A. Friedman, PhD Associate Research Scientist, Biomedical Informatics Shared Resource Herbert Irving Comprehensive Cancer Center (HICCC) Lecturer, Department of Biomedical Informatics (DBMI) Educational Coordinator, Center for Computational Biology and Bioinformatics (C2B2)/ National Center for Multiscale Analysis of Genomic Networks (MAGNet)/ Columbia Initiative in Systems Biology Room 824 Irving Cancer Research Center Columbia University 1130 St. Nicholas Ave New York, NY 10032 (212)851-4765 (voice) friedman at cancercenter.columbia.edu http://cancercenter.columbia.edu/~friedman/ Fritz Lang. Didn't he do "Star Trek". -Rose Friedman, age 16
rnaseq cancer edger dss • 808 views
ADD COMMENTlink modified 6.5 years ago by Ryan C. Thompson7.3k • written 6.5 years ago by Richard Friedman2.0k
Answer: QuasiSeq vs DSS
0
gravatar for Ryan C. Thompson
6.5 years ago by
The Scripps Research Institute, La Jolla, CA
Ryan C. Thompson7.3k wrote:
Dear Rich, From what I can tell, it should be possible. The development version of DESeq2 implements the DSS "squeezing" method combined with edgeR's Cox-Reid dispersion estimation. You could use DESeq2 to estimate dispersions, and then copy those dispersion values into an edgeR DGEList object. Then you can use edgeR::glmQLFTest, which implements (approximately) the QuasiSeq method. I have not had time yet to investigate putting these packages together in this way, but it is something I plan to look at. I'm certain that the combination is technically possible, and I'm reasonably sure that the result would be statistically meaningful. -Ryan Thompson On Mar 12, 2013 7:06 AM, "Richard Friedman" <friedman@cancercenter.columbia.edu <mailto:friedman@cancercenter.columbia.edu="">> wrote: Dear List. The papers on DSS (included in Bioconductor): Wu H, Wang C, Wu Z. A new shrinkage estimator for dispersion improves differential expression detection in RNA-seq data. Biostatistics. 2013 Apr;14(2):232-43. and QuasiSeq (included in CRAN): Lund SP, Nettleton D, McCarthy DJ, Smyth GK. Detecting differential expression in RNA-sequence data using quasi-likelihood with shrunken dispersion estimates. Stat Appl Genet Mol Biol. 2012 both give evidence of superior performance to edgeR (if I understand them correctly). Have the two methods been compared? Can the 2 methods been combined (with DSS estimating the dispersion used in the quasi-negative bionomial disribution used in QuasiSeq)? I would appreciate any insight with respect to what is the overall best method for differential expression in RNASeq available at present. Thanks and best wishes, Rich Richard A. Friedman, PhD Associate Research Scientist, Biomedical Informatics Shared Resource Herbert Irving Comprehensive Cancer Center (HICCC) Lecturer, Department of Biomedical Informatics (DBMI) Educational Coordinator, Center for Computational Biology and Bioinformatics (C2B2)/ National Center for Multiscale Analysis of Genomic Networks (MAGNet)/ Columbia Initiative in Systems Biology Room 824 Irving Cancer Research Center Columbia University 1130 St. Nicholas Ave New York, NY 10032 (212)851-4765 (voice) friedman@cancercenter.columbia.edu <mailto:friedman@cancercenter.columbia.edu> http://cancercenter.columbia.edu/~friedman/ <http: cancercenter.columbia.edu="" %7efriedman=""/> Fritz Lang. Didn't he do "Star Trek". -Rose Friedman, age 16 _______________________________________________ Bioconductor mailing list Bioconductor@r-project.org <mailto:bioconductor@r-project.org> https://stat.ethz.ch/mailman/listinfo/bioconductor Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor [[alternative HTML version deleted]]
ADD COMMENTlink written 6.5 years ago by Ryan C. Thompson7.3k
Dear Ryan, Thank you for your response. 3 questions: 1. If I had just a simple pairwise comparison is it known DSS or QuasiSeq better? 2. I was unaware that an approximate implementation of QuasiSeq was available in edgeR. If so, is it known hor it compare to the ordinairy EdgeR on the one hand and the full QuasiSeq on the other. 3. And I guess that the third question is for Gordon - Is using DSS and QuasiSeq (or EdgeR) together desireable and if so, are there plans to incorporate DSS into QuasiSeq (EdgeR). My note was planning ahead. I will still be in the microarray world for a more few weeks before I return to learning RNASeq. I wanted to know what the best practice is. If you (or anybody out there) develops a script to meld the two methods, I am sure that it would be interesting to the list. Best wishes, Rich On Mar 12, 2013, at 12:59 PM, Ryan C. Thompson wrote: > Dear Rich, > From what I can tell, it should be possible. The development version of DESeq2 implements the DSS "squeezing" method combined with edgeR's Cox-Reid dispersion estimation. You could use DESeq2 to estimate dispersions, and then copy those dispersion values into an edgeR DGEList object. Then you can use edgeR::glmQLFTest, which implements (approximately) the QuasiSeq method. > I have not had time yet to investigate putting these packages together in this way, but it is something I plan to look at. I'm certain that the combination is technically possible, and I'm reasonably sure that the result would be statistically meaningful. > -Ryan Thompson > On Mar 12, 2013 7:06 AM, "Richard Friedman" <friedman at="" cancercenter.columbia.edu=""> wrote: > Dear List. > > The papers on DSS (included in Bioconductor): > > Wu H, Wang C, Wu Z. A new shrinkage estimator for dispersion improves > differential expression detection in RNA-seq data. Biostatistics. 2013 > Apr;14(2):232-43. > > and QuasiSeq (included in CRAN): > > Lund SP, Nettleton D, McCarthy DJ, Smyth GK. Detecting differential expression > in RNA-sequence data using quasi-likelihood with shrunken dispersion estimates. > Stat Appl Genet Mol Biol. 2012 > > both give evidence of superior performance to edgeR (if I understand them correctly). > > Have the two methods been compared? > Can the 2 methods been combined (with DSS estimating the dispersion used in > the quasi-negative bionomial disribution used in QuasiSeq)? > > I would appreciate any insight with respect to what is the overall best > method for differential expression in RNASeq available at present. > > Thanks and best wishes, > Rich > > > Richard A. Friedman, PhD > Associate Research Scientist, > Biomedical Informatics Shared Resource > Herbert Irving Comprehensive Cancer Center (HICCC) > Lecturer, > Department of Biomedical Informatics (DBMI) > Educational Coordinator, > Center for Computational Biology and Bioinformatics (C2B2)/ > National Center for Multiscale Analysis of Genomic Networks (MAGNet)/ > Columbia Initiative in Systems Biology > Room 824 > Irving Cancer Research Center > Columbia University > 1130 St. Nicholas Ave > New York, NY 10032 > (212)851-4765 (voice) > friedman at cancercenter.columbia.edu > http://cancercenter.columbia.edu/~friedman/ > > Fritz Lang. Didn't he do "Star Trek". > -Rose Friedman, age 16 > > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor
ADD REPLYlink written 6.5 years ago by Richard Friedman2.0k
Here is a quote from Gordon Smyth a few months ago in response to a question of mine, which I think neatly summarizes the relationship between QuasiSeq and edgeR::glmQLFTest: > glmQLFTest() and QuasiSeq were developed independently with the same > idea, hence we got together to write the paper. If you use common > dispersion to fit the linear model, then glmQLFTest() is like > NegBinQLShrink. If you use trended dispersion to fit the linear model > (recommended), then glmQLFTest() is like NegBinQLSpline. They are not > quite identical however. glmQLTest() leverages the functionality of > the edgeR and limma packages, whereas QuasiSeq has used its own > implementations of everything. The latter are described in the paper. (Gordon, I hope you don't mind me posting this publically. Hopefully it saves you the trouble of rewriting it.) -Ryan On Tue 12 Mar 2013 10:11:25 AM PDT, Richard Friedman wrote: > > Dear Ryan, > > Thank you for your response. > 3 questions: > 1. If I had just a simple pairwise comparison is it known DSS or > QuasiSeq better? > 2. I was unaware that an approximate implementation of QuasiSeq was > available in > edgeR. If so, is it known hor it compare to the ordinairy EdgeR on the > one hand and the > full QuasiSeq on the other. > 3. And I guess that the third question is for Gordon - Is using DSS > and QuasiSeq (or EdgeR) together > desireable and if so, are there plans to incorporate DSS into QuasiSeq > (EdgeR). > > My note was planning ahead. I will still be in the microarray world > for a more few weeks > before I return to learning RNASeq. I wanted to know what the best > practice is. > If you (or anybody out there) develops a script to meld the two > methods, I am sure that > it would be interesting to the list. > > Best wishes, > Rich > > > > > > On Mar 12, 2013, at 12:59 PM, Ryan C. Thompson wrote: > >> >> Dear Rich, >> From what I can tell, it should be possible. The development version >> of DESeq2 implements the DSS "squeezing" method combined with edgeR's >> Cox-Reid dispersion estimation. You could use DESeq2 to estimate >> dispersions, and then copy those dispersion values into an edgeR >> DGEList object. Then you can use edgeR::glmQLFTest, which implements >> (approximately) the QuasiSeq method. >> I have not had time yet to investigate putting these packages >> together in this way, but it is something I plan to look at. I'm >> certain that the combination is technically possible, and I'm >> reasonably sure that the result would be statistically meaningful. >> -Ryan Thompson >> On Mar 12, 2013 7:06 AM, "Richard Friedman" >> <friedman at="" cancercenter.columbia.edu=""> wrote: >> Dear List. >> >> The papers on DSS (included in Bioconductor): >> >> Wu H, Wang C, Wu Z. A new shrinkage estimator for dispersion improves >> differential expression detection in RNA-seq data. Biostatistics. 2013 >> Apr;14(2):232-43. >> >> and QuasiSeq (included in CRAN): >> >> Lund SP, Nettleton D, McCarthy DJ, Smyth GK. Detecting differential >> expression >> in RNA-sequence data using quasi-likelihood with shrunken dispersion >> estimates. >> Stat Appl Genet Mol Biol. 2012 >> >> both give evidence of superior performance to edgeR (if I understand >> them correctly). >> >> Have the two methods been compared? >> Can the 2 methods been combined (with DSS estimating the dispersion >> used in >> the quasi-negative bionomial disribution used in QuasiSeq)? >> >> I would appreciate any insight with respect to what is the overall best >> method for differential expression in RNASeq available at present. >> >> Thanks and best wishes, >> Rich >> >> >> Richard A. Friedman, PhD >> Associate Research Scientist, >> Biomedical Informatics Shared Resource >> Herbert Irving Comprehensive Cancer Center (HICCC) >> Lecturer, >> Department of Biomedical Informatics (DBMI) >> Educational Coordinator, >> Center for Computational Biology and Bioinformatics (C2B2)/ >> National Center for Multiscale Analysis of Genomic Networks (MAGNet)/ >> Columbia Initiative in Systems Biology >> Room 824 >> Irving Cancer Research Center >> Columbia University >> 1130 St. Nicholas Ave >> New York, NY 10032 >> (212)851-4765 (voice) >> friedman at cancercenter.columbia.edu >> http://cancercenter.columbia.edu/~friedman/ >> >> Fritz Lang. Didn't he do "Star Trek". >> -Rose Friedman, age 16 >> >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor at r-project.org >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: >> http://news.gmane.org/gmane.science.biology.informatics.conductor >
ADD REPLYlink written 6.5 years ago by Ryan C. Thompson7.3k
Please log in to add an answer.

Help
Access

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 16.09
Traffic: 89 users visited in the last hour