On Dec 29, 2005, at 12:56 PM, kfbargad at ehu.es wrote: > Hi, sorry, I think I found the answer to my previous email. > > setdiff() will do the trick, right? Yes, although it will depend on how your list are structured since setdiff works on vectors. /Kasper > I also found the help for %in%, it was under ?'%in%' > > best, > > David > >> Hi, >> thanks for the clarification. Then it depends on whether you want > to >> use the union or the intersection of the probes you selected in the > two >> different ways. >> union and intersect, applied to geneNames(PinS) and geneNames of > PinC >> should get you somewhere close, you might also want to consider > match >> and %in%, depending on just how you want to select. >> After that, you will need to create a matrix with the combined >> expressions and use that as input in a call to >> new, the vignettes for Biobase should demonstrate how to make an >> exprSet from a matrix, but please ask if anything is not clear >> >> best wishes >> Robert >> >> kfbargad at ehu.es wrote: >>> Dear Seth and Robert, >>> >>> I apologise, but I didn?t make myself clear. >>> >>> PinS and PinC come from the same experiment, i.e. the same eset. > It is >>> just that I followed two different approaches to the analysis and > now >>> I want to continue working with the union of these two lists. So I > am >>> not intending to match across different arrays. >>> >>> Hope this explains my question >>> >>> David >>> >>> >>>> Hi, >>>> I think that the problem is that the arrays are not the same - > and >>>> then life is much harder. There are some papers on it (G. > Parmigiani >>> >>> et >>> >>>> al have produced MergeMaid, as one option). I have done some work > on >>>> this problem, with Wolfgang Huber and Markus Rauschaupt (you can >>> >>> find >>> >>>> the technical report under the Bioconductor publications link - I >>> >>> hope). >>> >>>> It is not so simple to match across different arrays, where >>> >>> different >>> >>>> probes were used (you can take the expedient of mapping to some >>> >>> common >>> >>>> set of IDs and matching on those, some code in packages GeneMeta > and >>>> GeneMetaEx, if I recall correctly), but just because they map to > the >>>> same Entrez gene id (for example) does not mean that the same > thing >>> >>> was >>> >>>> measured - whence MergeMaid and similar tools. >>>> >>>> And if this is correct, then combining them is contra-indicated >>> >>> and >>> >>>> some of the tools for synthesizing experiments, such as meta- >>> >>> analysis or >>> >>>> the more general random effects models will be needed. Just > because >>> >>> you >>> >>>> can jam, either the raw data or the processed data together, does >>> >>> not >>> >>>> mean that it is sensible to do so. >>>> >>>> And finally, even if the arrays are identical, unless they were > all >>>> essentially done at the same time under very similar conditions I >>> >>> would >>> >>>> still take the approach in the paragraph above and use a random >>> >>> effects >>> >>>> model. >>>> >>>> best wishes >>>> Robert >>>> >>>> >>>> Seth Falcon wrote: >>>> >>>>> On 26 Dec 2005, kfbargad at ehu.es wrote: >>>>> >>>>> >>>>> >>>>>> Dear list, >>>>>> >>>>>> I have two sets of genes from the same experiment, >>>>>> >>>>>> >>>>>> >>>>>>> PinC >>>>>> >>>>>> Expression Set (exprSet) with >>>>>> 1310 genes >>>>>> 8 samples >>>>>> phenoData object with 2 variables and 8 cases >>>>>> varLabels >>>>>> FileName: read from file >>>>>> Target: read from file >>>>>> >>>>>> >>>>>>> PinS >>>>>> >>>>>> Expression Set (exprSet) with >>>>>> 2891 genes >>>>>> 8 samples >>>>>> phenoData object with 2 variables and 8 cases >>>>>> varLabels >>>>>> FileName: read from file >>>>>> Target: read from file >>>>>> >>>>>> >>>>>> How can I merge these two sets? I tried union() on two vectors >>>>>> created from the probe IDs but failed. Any hints? >>>>> >>>>> >>>>> One approach would be to create a new exprSet object manually > using >>>>> the data from PinC and PinS. Basically, create a new phenoData >>> >>> object >>> >>>>> with the data for all 16 cases, and a new epxression matrix with > 16 >>>>> columns (assuming the two original exprSets represent disjoint >>> >>> sets of >>> >>>>> samples). >>>>> >>>>> Thinking out loud, is this a common enough operation to warrant a >>>>> method for exprSets? I could imagine c() being defined on > exprSets >>>>> such that if the phenoData columns are the same and the "sample >>> >>> ids" >>> >>>>> as given by the rownames of phenoData/colnames of exprs are >>> >>> disjoint, >>> >>>>> then do the obvious thing, else error. >>>>> >>>>> + seth >>>>> >>>>> _______________________________________________ >>>>> Bioconductor mailing list >>>>> Bioconductor at stat.math.ethz.ch >>>>> https://stat.ethz.ch/mailman/listinfo/bioconductor >>>>> >>>> >>>> -- >>>> 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 >>>> >>>> _______________________________________________ >>>> Bioconductor mailing list >>>> Bioconductor at stat.math.ethz.ch >>>> https://stat.ethz.ch/mailman/listinfo/bioconductor >>>> >>> >>> >>> >>> >> >> -- >> 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 >> > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor