DESeq2
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@wolfgang-huber-3550
Last seen 18 days ago
EMBL European Molecular Biology Laborat…
Dear DESeq users, Mike Love, Simon Anders and I have been updating the DESeq package. This resulted in the package DESeq2, which is available from the development branch, and scheduled for the next release: http://www.bioconductor.org/packages/devel/bioc/html/DESeq2.html For several release cycles, the original package (DESeq) will be maintained at its current functionality, in order to not disrupt the workflows of DESeq users. For new projects, we recommend using DESeq2. Major innovations are: * Base class: SummarizedExperiment is used as the superclass for storing the data, rather than eSet. This allows closer integration with upstream workflows involving GRanges and summarizeOverlaps, and facilitates downstream analyses of the genomic regions of interest. * Simplified workflow: the wrapper function DESeq() performs all steps for a differential expression analysis. The individual steps are of course also accessible. * More powerful statistics: incorporation of prior distributions into the estimation of dispersions and fold changes (empirical-Bayes shrinkage). The dispersion shrinkage improves power compared to the old DESeq. The fold changes shrinkage help moderate the otherwise large spread in log fold changes for genes with low counts, while it has negligible effect on genes with high counts; it may be particularly useful for visualisation, clustering, classification, ordination (PCA, MDS), similar to the variance-stabilizing transformation in the old DESeq. A Wald test for significance is provided as the default inference method, with the chi-squared test of the previous version is also available. A manuscript is in preparation. * Normalization: it is possible to provide a matrix of sample- *and* gene-specific normalization factors, which allows the use of normalisation factors from Bioconductor packages such as cqn and EDASeq. Examples of usage are provided in the vignette, and more details are available in the manual pages (specifically, the DESeq function and estimateDispersions function). Enjoy - Mike, Simon, Wolfgang.
Normalization Classification Clustering DESeq cqn DESeq2 Normalization Classification cqn • 3.1k views
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@ryan-c-thompson-5618
Last seen 8 months ago
Scripps Research, La Jolla, CA
Hello, I noticed the addition of the DESeq2 package a few days ago and had a look at the new additions. Overall, it looks like an excellent package (and it runs a lot faster than DESeq 1, too). I have a few questions for clarification of exactly what methods DESeq2 is using. Specifically, I notice that the fold change shrinkage is performed in nbinomWaldTest but not in nbinomChisqTest. Is this just for reasons of backward-compatibility of results, or is the Chi-squared test logically incompatible with shrunken GLM coefficients? Secondly, is there any plan to extend the Wald test to testing contrasts of multiple coefficients or testing multiple coefficients/contrasts at once in an ANOVA-like test? Thanks, -Ryan Thompson On 03/12/2013 01:51 PM, Wolfgang Huber wrote: > Dear DESeq users, > > Mike Love, Simon Anders and I have been updating the DESeq package. This resulted in the package DESeq2, which is available from the development branch, and scheduled for the next release: http://www.bioconductor.org/packages/devel/bioc/html/DESeq2.html > > For several release cycles, the original package (DESeq) will be maintained at its current functionality, in order to not disrupt the workflows of DESeq users. For new projects, we recommend using DESeq2. Major innovations are: > > * Base class: SummarizedExperiment is used as the superclass for storing the data, rather than eSet. This allows closer integration with upstream workflows involving GRanges and summarizeOverlaps, and facilitates downstream analyses of the genomic regions of interest. > > * Simplified workflow: the wrapper function DESeq() performs all steps for a differential expression analysis. The individual steps are of course also accessible. > > * More powerful statistics: incorporation of prior distributions into the estimation of dispersions and fold changes (empirical-Bayes shrinkage). The dispersion shrinkage improves power compared to the old DESeq. The fold changes shrinkage help moderate the otherwise large spread in log fold changes for genes with low counts, while it has negligible effect on genes with high counts; it may be particularly useful for visualisation, clustering, classification, ordination (PCA, MDS), similar to the variance-stabilizing transformation in the old DESeq. A Wald test for significance is provided as the default inference method, with the chi-squared test of the previous version is also available. A manuscript is in preparation. > > * Normalization: it is possible to provide a matrix of sample- *and* gene-specific normalization factors, which allows the use of normalisation factors from Bioconductor packages such as cqn and EDASeq. > > Examples of usage are provided in the vignette, and more details are available in the manual pages (specifically, the DESeq function and estimateDispersions function). > > Enjoy - > > Mike, Simon, Wolfgang. > > _______________________________________________ > 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
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hi Ryan, Thanks for the comments. On 03/13/13 08:59, Ryan C. Thompson wrote: > Hello, > > I noticed the addition of the DESeq2 package a few days ago and had a > look at the new additions. Overall, it looks like an excellent package > (and it runs a lot faster than DESeq 1, too). I have a few questions > for clarification of exactly what methods DESeq2 is using. > Specifically, I notice that the fold change shrinkage is performed in > nbinomWaldTest but not in nbinomChisqTest. Is this just for reasons of > backward-compatibility of results, or is the Chi-squared test > logically incompatible with shrunken GLM coefficients? The latter was our reason. With shrunken coefficients, the differences in deviances are no longer distributed as a chi-square. For example, with simulated null data (non-intercept betas equal to zero), the differences in deviances will pile up near zero and the resulting p-values will not be uniformly distributed. > Secondly, is there any plan to extend the Wald test to testing > contrasts of multiple coefficients or testing multiple > coefficients/contrasts at once in an ANOVA-like test? > Yes, we are looking into a convenient interface for this. best, Mike > Thanks, > > -Ryan Thompson > > On 03/12/2013 01:51 PM, Wolfgang Huber wrote: >> Dear DESeq users, >> >> Mike Love, Simon Anders and I have been updating the DESeq package. >> This resulted in the package DESeq2, which is available from the >> development branch, and scheduled for the next release: >> http://www.bioconductor.org/packages/devel/bioc/html/DESeq2.html >> >> For several release cycles, the original package (DESeq) will be >> maintained at its current functionality, in order to not disrupt the >> workflows of DESeq users. For new projects, we recommend using >> DESeq2. Major innovations are: >> >> * Base class: SummarizedExperiment is used as the superclass for >> storing the data, rather than eSet. This allows closer integration >> with upstream workflows involving GRanges and summarizeOverlaps, and >> facilitates downstream analyses of the genomic regions of interest. >> >> * Simplified workflow: the wrapper function DESeq() performs all >> steps for a differential expression analysis. The individual steps >> are of course also accessible. >> >> * More powerful statistics: incorporation of prior distributions into >> the estimation of dispersions and fold changes (empirical-Bayes >> shrinkage). The dispersion shrinkage improves power compared to the >> old DESeq. The fold changes shrinkage help moderate the otherwise >> large spread in log fold changes for genes with low counts, while it >> has negligible effect on genes with high counts; it may be >> particularly useful for visualisation, clustering, classification, >> ordination (PCA, MDS), similar to the variance-stabilizing >> transformation in the old DESeq. A Wald test for significance is >> provided as the default inference method, with the chi-squared test >> of the previous version is also available. A manuscript is in >> preparation. >> >> * Normalization: it is possible to provide a matrix of sample- *and* >> gene-specific normalization factors, which allows the use of >> normalisation factors from Bioconductor packages such as cqn and EDASeq. >> >> Examples of usage are provided in the vignette, and more details are >> available in the manual pages (specifically, the DESeq function and >> estimateDispersions function). >> >> Enjoy - >> >> Mike, Simon, Wolfgang. >> >> _______________________________________________ >> 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 > > _______________________________________________ > 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
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@mariana-boroni-5838
Last seen 6.8 years ago
Hi, I've installed R-devel (R-3.0) and now I'm attempting to install the DESeq2 package with this command: source("http://bioconductor.org/biocLite.R") biocLite("DESeq2") But I get the following error: > biocLite("DESeq2") BioC_mirror: http://bioconductor.org Using Bioconductor version 2.12 (BiocInstaller 1.9.8), R version 3.0.0. Installing package(s) 'DESeq2' package ‘DESeq2’ is available as a source package but not as a binary Mensagens de aviso perdidas: package ‘DESeq2’ is not available (for R version 3.0.0 alpha) But in the DESeq2 viginete they use R 3.0.0 Session Info R version 3.0.0 alpha (2013-03-09 r62188), x86_64-unknown-linux-gnu Locale: LC_CTYPE=en_US.UTF-8, LC_NUMERIC=C, LC_TIME=en_US.UTF-8, LC_COLLATE=C, LC_MONETARY=en_US.UTF-8, LC_MESSAGES=en_US.UTF-8, LC_PAPER=C, LC_NAME=C, LC_ADDRESS=C, LC_TELEPHONE=C, LC_MEASUREMENT=en_US.UTF-8, LC_IDENTIFICATION=C Base packages: base, datasets, grDevices, graphics, grid, methods, parallel, stats, utils Other packages: Biobase 2.19.3, BiocGenerics 0.5.6, DESeq2 0.99.16, DEXSeq 1.5.9, GenomicRanges 1.11.35, IRanges 1.17.36, KernSmooth 2.23-9, MASS 7.3-24, RColorBrewer 1.0-5, Rcpp 0.10.2, RcppArmadillo 0.3.800.0, caTools 1.14, gdata 2.12.0, gplots 2.11.0, gtools 2.7.0, lattice 0.20-13, locfit 1.5-8, parathyroidSE 0.99.1, vsn 3.27.2 Loaded via a namespace (and not attached): AnnotationDbi 1.21.13, BiocInstaller 1.9.7, Biostrings 2.27.11, DBI 0.2-5, DESeq 1.11.6, RCurl 1.95-4.1, RSQLite 0.11.2, Rsamtools 1.11.21, XML 3.95-0.2, affy 1.37.4, affyio 1.27.1 My > sessionInfo() R version 3.0.0 alpha (2013-03-18 r62312) Platform: x86_64-apple-darwin10.8.0 (64-bit) locale: [1] pt_BR.UTF-8/pt_BR.UTF-8/pt_BR.UTF-8/C/pt_BR.UTF-8/pt_BR.UTF-8 attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] BiocInstaller_1.9.8 loaded via a namespace (and not attached): [1] tools_3.0.0 Any help? Thanks ______________________________ Mariana Boroni Doutoranda em Bioinformática Laboratório de Genética Bioquímica Universidade Federal de Minas Gerais Tel: +55 31 3409-2628 +55 31 9413-4242 [[alternative HTML version deleted]]
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On Wed, Mar 20, 2013 at 3:56 PM, Mariana Boroni <marianaboroni at="" gmail.com=""> wrote: > Hi, > I've installed R-devel (R-3.0) and now I'm attempting to install the DESeq2 package with this command: > > source("http://bioconductor.org/biocLite.R") > biocLite("DESeq2") > But I get the following error: > >> biocLite("DESeq2") > BioC_mirror: http://bioconductor.org > Using Bioconductor version 2.12 (BiocInstaller 1.9.8), R version 3.0.0. > Installing package(s) 'DESeq2' > > package ?DESeq2? is available as a source package but not as a binary > > Mensagens de aviso perdidas: > package ?DESeq2? is not available (for R version 3.0.0 alpha) > > But in the DESeq2 viginete they use R 3.0.0 > Session Info > > R version 3.0.0 alpha (2013-03-09 r62188), x86_64-unknown-linux-gnu > > Locale: LC_CTYPE=en_US.UTF-8, LC_NUMERIC=C, LC_TIME=en_US.UTF-8, LC_COLLATE=C, LC_MONETARY=en_US.UTF-8, LC_MESSAGES=en_US.UTF-8, LC_PAPER=C, LC_NAME=C, LC_ADDRESS=C, LC_TELEPHONE=C, LC_MEASUREMENT=en_US.UTF-8, LC_IDENTIFICATION=C > > Base packages: base, datasets, grDevices, graphics, grid, methods, parallel, stats, utils > > Other packages: Biobase 2.19.3, BiocGenerics 0.5.6, DESeq2 0.99.16, DEXSeq 1.5.9, GenomicRanges 1.11.35, IRanges 1.17.36, KernSmooth 2.23-9, MASS 7.3-24, RColorBrewer 1.0-5, Rcpp 0.10.2, RcppArmadillo 0.3.800.0, caTools 1.14, gdata 2.12.0, gplots 2.11.0, gtools 2.7.0, lattice 0.20-13, > locfit 1.5-8, parathyroidSE 0.99.1, vsn 3.27.2 > > Loaded via a namespace (and not attached): AnnotationDbi 1.21.13, BiocInstaller 1.9.7, Biostrings 2.27.11, DBI 0.2-5, DESeq 1.11.6, RCurl 1.95-4.1, RSQLite 0.11.2, Rsamtools 1.11.21, XML 3.95-0.2, affy 1.37.4, affyio 1.27.1 > > > My >> sessionInfo() > R version 3.0.0 alpha (2013-03-18 r62312) > Platform: x86_64-apple-darwin10.8.0 (64-bit) > > locale: > [1] pt_BR.UTF-8/pt_BR.UTF-8/pt_BR.UTF-8/C/pt_BR.UTF-8/pt_BR.UTF-8 > > attached base packages: > [1] stats graphics grDevices utils datasets methods base > > other attached packages: > [1] BiocInstaller_1.9.8 > > loaded via a namespace (and not attached): > [1] tools_3.0.0 > > > Any help? For the time being, there are no Mac binary packages available for R 3.0 alpha and beta (but there are for earlier versions of R-3.0). Because of upcoming changes to Mac support in R-3.0, detailed here: https://stat.ethz.ch/pipermail/r-sig-mac/2013-March/010003.html ...we are still testing our new Mac builds. You can work around this by installing the package as follows: source("http://bioconductor.org/biocLite.R") biocLite("DESeq2", type="source") This will require that you have XCode installed (be sure you also install the "command line tools" download that is optional with Mountain Lion). Dan > > Thanks > ______________________________ > Mariana Boroni > Doutoranda em Bioinform?tica > Laborat?rio de Gen?tica Bioqu?mica > Universidade Federal de Minas Gerais > Tel: +55 31 3409-2628 > +55 31 9413-4242 > > > [[alternative HTML version deleted]] > > > _______________________________________________ > 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
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@mikelove
Last seen 11 hours ago
United States
hi Mariana, Let's continue this on the list. I'm not sure, but I would first try to install the dependencies separately first. akima, locfit and RcppArmadillo are CRAN packages, and genefilter is a Bioconductor package. So try install.packages for the CRAN packages and biocLite with type="source" for genefilter. Mike On Thu, Mar 21, 2013 at 7:00 PM, Mariana Boroni <marianaboroni@gmail.com>wrote: > Hi I tried Dan's tip but I still stuck on the DESeq2 package instalattion: > > source("http://bioconductor.org/biocLite.R") > biocLite("DESeq2", type="source") > > > I have this error: > > 1: In install.packages(pkgs = pkgs, lib = lib, repos = repos, ...) : > installation of package ‘akima’ had non-zero exit status > 2: In install.packages(pkgs = pkgs, lib = lib, repos = repos, ...) : > installation of package ‘RcppArmadillo’ had non-zero exit status > 3: In install.packages(pkgs = pkgs, lib = lib, repos = repos, ...) : > installation of package ‘genefilter’ had non-zero exit status > 4: In install.packages(pkgs = pkgs, lib = lib, repos = repos, ...) : > installation of package ‘locfit’ had non-zero exit status > 5: In install.packages(pkgs = pkgs, lib = lib, repos = repos, ...) : > installation of package ‘DESeq2’ had non-zero exit status > > My > > sessionInfo() > > R version 3.0.0 alpha (2013-03-18 r62312) > > Platform: x86_64-apple-darwin10.8.0 (64-bit) > > > locale: > > [1] pt_BR.UTF-8/pt_BR.UTF-8/pt_BR.UTF-8/C/pt_BR.UTF-8/pt_BR.UTF-8 > > > attached base packages: > > [1] stats graphics grDevices utils datasets methods base > > > other attached packages: > > [1] BiocInstaller_1.9.8 > > > loaded via a namespace (and not attached): > > [1] tools_3.0.0 > > > > Could you please help me to install the package? > > thanks, > > Mariana > ______________________________ > *Mariana Boroni * > Doutoranda em Bioinformática > Laboratório de Genética Bioquímica > Universidade Federal de Minas Gerais > Tel: +55 31 3409-2628 > +55 31 9413-4242 > > Em 21/03/2013, às 02:52, Dan Tenenbaum escreveu: > > On Wed, Mar 20, 2013 at 3:56 PM, Mariana Boroni <marianaboroni@gmail.com> > wrote: > > Hi, > > I've installed R-devel (R-3.0) and now I'm attempting to install the > DESeq2 package with this command: > > > source("http://bioconductor.org/biocLite.R") > > biocLite("DESeq2") > > But I get the following error: > > > biocLite("DESeq2") > > BioC_mirror: http://bioconductor.org > > Using Bioconductor version 2.12 (BiocInstaller 1.9.8), R version 3.0.0. > > Installing package(s) 'DESeq2' > > > package ‘DESeq2’ is available as a source package but not as a binary > > > Mensagens de aviso perdidas: > > package ‘DESeq2’ is not available (for R version 3.0.0 alpha) > > > But in the DESeq2 viginete they use R 3.0.0 > > Session Info > > > R version 3.0.0 alpha (2013-03-09 r62188), x86_64-unknown-linux-gnu > > > Locale: LC_CTYPE=en_US.UTF-8, LC_NUMERIC=C, LC_TIME=en_US.UTF-8, > LC_COLLATE=C, LC_MONETARY=en_US.UTF-8, LC_MESSAGES=en_US.UTF-8, LC_PAPER=C, > LC_NAME=C, LC_ADDRESS=C, LC_TELEPHONE=C, LC_MEASUREMENT=en_US.UTF-8, > LC_IDENTIFICATION=C > > > Base packages: base, datasets, grDevices, graphics, grid, methods, > parallel, stats, utils > > > Other packages: Biobase 2.19.3, BiocGenerics 0.5.6, DESeq2 0.99.16, DEXSeq > 1.5.9, GenomicRanges 1.11.35, IRanges 1.17.36, KernSmooth 2.23-9, MASS > 7.3-24, RColorBrewer 1.0-5, Rcpp 0.10.2, RcppArmadillo 0.3.800.0, caTools > 1.14, gdata 2.12.0, gplots 2.11.0, gtools 2.7.0, lattice 0.20-13, > > locfit 1.5-8, parathyroidSE 0.99.1, vsn 3.27.2 > > > Loaded via a namespace (and not attached): AnnotationDbi 1.21.13, > BiocInstaller 1.9.7, Biostrings 2.27.11, DBI 0.2-5, DESeq 1.11.6, RCurl > 1.95-4.1, RSQLite 0.11.2, Rsamtools 1.11.21, XML 3.95-0.2, affy 1.37.4, > affyio 1.27.1 > > > > My > > sessionInfo() > > R version 3.0.0 alpha (2013-03-18 r62312) > > Platform: x86_64-apple-darwin10.8.0 (64-bit) > > > locale: > > [1] pt_BR.UTF-8/pt_BR.UTF-8/pt_BR.UTF-8/C/pt_BR.UTF-8/pt_BR.UTF-8 > > > attached base packages: > > [1] stats graphics grDevices utils datasets methods base > > > other attached packages: > > [1] BiocInstaller_1.9.8 > > > loaded via a namespace (and not attached): > > [1] tools_3.0.0 > > > > Any help? > > > > For the time being, there are no Mac binary packages available for R > 3.0 alpha and beta (but there are for earlier versions of R-3.0). > > Because of upcoming changes to Mac support in R-3.0, detailed here: > https://stat.ethz.ch/pipermail/r-sig-mac/2013-March/010003.html > > ...we are still testing our new Mac builds. > > You can work around this by installing the package as follows: > > source("http://bioconductor.org/biocLite.R") > biocLite("DESeq2", type="source") > > This will require that you have XCode installed (be sure you also > install the "command line tools" download that is optional with > Mountain Lion). > > Dan > > > > Thanks > > ______________________________ > > Mariana Boroni > > Doutoranda em Bioinformática > > Laboratório de Genética Bioquímica > > Universidade Federal de Minas Gerais > > Tel: +55 31 3409-2628 > > +55 31 9413-4242 > > > > [[alternative HTML version deleted]] > > > > _______________________________________________ > > Bioconductor mailing list > > 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]]
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