Dear group, I have 15 gene expression studies. I have raw data for these (some are GEO datasets). I could make esets for these datasets. i want to create expression data packages, so that my peers can also use these datasets for their analysis. I have the following components for each dataset: 1.phenoData 2.expression data matrix 3. detailed annotations including clinical variables embeded into phenoData. I could make an eset for these: eset <- new('exprSet',data = exp.mat, phenoData=pheno) from now on how can I go ahead and make expression data library. Is there any step-by-step procedure to create a experimental data library. could any one pls. help me. thanks srini

Srinivas Iyyer wrote: > Dear group, > I have 15 gene expression studies. I have raw data > for these (some are GEO datasets). > > I could make esets for these datasets. > > i want to create expression data packages, so that my > peers can also use these datasets for their analysis. > > I have the following components for each dataset: > 1.phenoData > 2.expression data matrix > 3. detailed annotations including clinical variables > embeded into phenoData. > > I could make an eset for these: > > eset <- new('exprSet',data = exp.mat, phenoData=pheno) > > from now on how can I go ahead and make expression > data library. Srini, You can simply save the eset like: save(eset,file='eset1.Rda') Then, your colleagues can do: load('eset1.Rda') Is that what you had in mind? Sean

Hi, If you want to create a package, then some of the operations are detailed in Section 1 of the Writing R Extensions Manual (that came with R). In particular you might find the function package.skeleton helpful. Creating a package is a bit more work than just creating separate files you can pass around, but it is also a bit more useful, as you can create manual pages, and there is a simple way to version it (in case you update the data, or add data) etc. I would create each of the different data sets, as you have described below, but instead of giving them names like eset, you should give them names that are more meaningful and would help to identify the data. Then you can save these, (using save), copy the resulting objects into the data director/folder of your package. For each object you should create a manual page (prompt can help a bit), and put the resulting .Rd file into the man directory. Building, is done with R CMD build, checking with R CMD check (on Unix). On Windows you need to do a lot more work (as you will need to install most of the tools needed to build packages etc). best wishes Robert Srinivas Iyyer wrote: > Dear group, > I have 15 gene expression studies. I have raw data > for these (some are GEO datasets). > > I could make esets for these datasets. > > i want to create expression data packages, so that my > peers can also use these datasets for their analysis. > > I have the following components for each dataset: > 1.phenoData > 2.expression data matrix > 3. detailed annotations including clinical variables > embeded into phenoData. > > I could make an eset for these: > > eset <- new('exprSet',data = exp.mat, phenoData=pheno) > > from now on how can I go ahead and make expression > data library. > > Is there any step-by-step procedure to create a > experimental data library. > > could any one pls. help me. > > thanks > srini > > _______________________________________________ > 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 > -- Robert Gentleman, PhD Program in Computational Biology Division of Public Health Sciences Fred Hutchinson Cancer Research Center 1100 Fairview Ave. N, M2-B876 PO Box 19024 Seattle, Washington 98109-1024 206-667-7700 rgentlem at fhcrc.org