On 11/27/2012 09:32 AM, Tim Triche, Jr. wrote: > would it be the worst thing in the world to add rownames() and colnames() > support for eSet-derived objects in Biobase? > > setMethod("rownames", > signature=signature(x="eSet"), > function(x) featureNames(x)) > > setMethod("colnames", > signature=signature(x="eSet"), > function(x) sampleNames(x)) getters and setters, and for dimnames are now in devel 2.19.1. Martin > SummarizedExperiments already have these sort of "do what I mean" > semantics... one reason I like using them. > > > > On Tue, Nov 27, 2012 at 3:08 AM, Sean Davis <sdavis2 at="" mail.nih.gov=""> wrote: > >> On Mon, Nov 26, 2012 at 10:55 PM, McGee, Monnie <mmcgee at="" mail.smu.edu=""> >> wrote: >> >>> >>> Dear BioC Users, >>> >>> I would like to be able to subset a mass spectrometry data set by the >>> biomarkers that were chosen as >>> important biomarkers. I followed the code in the PROcess vignette to >>> obtain the biomarkers as follows: >>> >>> testNorm is a normalized matrix of m/z values from 253 samples >>>> bmkfile <- paste(getwd(), "testbiomarker.csv", sep = "/") >>>> testBio = pk2bmkr(peakfile, testNorm, bmkfile) >>>> mzs = as.numeric(rownames(testNorm)) >>>> bks = getMzs(testBio) ## Should be "important" biomarkers for the Mass >>> Spec data >>>> bks >>> [1] 308.497 350.487 378.092 396.084 676.031 3994.780 4597.540 >>> 7046.840 7965.760 8128.160 8351.810 9184.330 >>> >>> I created the expression set in the following way >>>> treat = ifelse(colnames(testNorm) < 300,"Control","Cancer") >>>> treatdf = as.data.frame(treat) >>>> rownames(treatdf)=colnames(testNorm) >>>> pdt = new("AnnotatedDataFrame",treatdf) >>>> mzdf = as.data.frame(rownames(testNorm)) >>>> rownames(mzdf)=rownames(testNorm) >>>> mzfeat = new("AnnotatedDataFrame",mzdf) >>>> testES = >>> new("ExpressionSet",exprs=testNorm,phenoData=pdt,featureData=mzfeat) >>>> varLabels(testES) >>> [1] "treat" >>>> table(pData(testES)) >>> Cancer Control >>> 162 91 >>>> featureData(testES) >>> An object of class "AnnotatedDataFrame" >>> featureNames: 300.033 300.356 ... 19995.5 (13297 total) >>> varLabels: V1 >>> varMetadata: labelDescription >>> >>> Figuring out how to obtain the eSet took at least an hour. By the way, >> the >>> purpose of the eSet is to obtain an object >>> that is an input into an MLearn function for classification purposes, >> such >>> as: >>> dldFS = MLearn(treat ~.,testES2,dldaI,)), where testES2 is the eset >>> containing only the information for the >>> important biomarkers. Clearly, I can't run MLearn (especially with CV) >>> with all 13K features in testES. Therefore, >>> I would like to run MLearn using the biomarkers to determine whether >> these >>> biomarkers actually discriminate between >>> the cancer and control samples. And, yes, this is the Petricoin ovarian >>> cancer data set, for those of you who know >>> your Mass Spec data. >>> >>> Now I have an eSet with the rows labeled by the mass to charge ratios and >>> the columns labeled by the samples >>> I would like to obtain a subset of testES using the 10 biomarkers (bks) >>> found above. Ideally, the following >>> would work: >>>> testES2 = testES[featureData(testES) == bks,] >>> >>> >> Hi, Monnie. >> >> Try using featureNames() instead of featureData(). The featureData() >> method returns an AnnotatedDataFrame. You just want a vector of names, it >> appears, so featureNames() is the method you should use. >> >> Sean >> >> >> >>> But I get the following error: >>> Error in testES[featureData(testES) == bks, ] : >>> error in evaluating the argument 'i' in selecting a method for function >>> '[': Error in featureData(testES) == bks : >>> comparison (1) is possible only for atomic and list types >>> >>> I tried making bks a character vector, but to no avail. I also tried the >>> following: >>>> testES2 = testES[featureData(testES) %in% bks,] ##(where bks is a >>> character vector or not) >>> Error in testES[featureData(testES) %in% bks, ] : >>> error in evaluating the argument 'i' in selecting a method for function >>> '[': Error in match(x, table, nomatch = 0L) : >>> 'match' requires vector arguments >>> >>> Part of the problem is (probably) that I am not using the correct syntax >>> for subsetting an eSet on the basis of featureData. Another part is that >> the >>> biomarkers do not have exact matches in featureData(testES) because they >>> were obtained using a peak finding >>> algorithm that is supposed to align peaks across all 253 samples. So, how >>> do I obtain the m/z ratios for the important features (the biomarkers) >> from >>> this eSet? >>> Is there another (saner) way to use the biomarkers in a classification >>> algorithm in order to determine the misclassification rate with this >>> particular >>> set of biomarkers? >>> >>> And, finally, the session Info: >>>> sessionInfo() >>> R version 2.15.1 (2012-06-22) >>> Platform: i386-apple-darwin9.8.0/i386 (32-bit) >>> >>> locale: >>> [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8 >>> >>> attached base packages: >>> [1] tools grid splines stats graphics grDevices utils >>> datasets methods base >>> >>> other attached packages: >>> [1] PROcess_1.32.0 Icens_1.28.0 survival_2.36-14 >>> flowStats_1.14.0 flowWorkspace_1.2.0 >>> [6] hexbin_1.26.0 IDPmisc_1.1.16 flowViz_1.20.0 >>> XML_3.95-0 RBGL_1.32.1 >>> [11] graph_1.34.0 Cairo_1.5-2 cluster_1.14.2 >>> mvoutlier_1.9.8 sgeostat_1.0-24 >>> [16] robCompositions_1.6.0 car_2.0-15 nnet_7.3-4 >>> compositions_1.20-1 energy_1.4-0 >>> [21] MASS_7.3-21 boot_1.3-5 tensorA_0.36 >>> rgl_0.92.892 fda_2.3.2 >>> [26] RCurl_1.95-0.1.2 bitops_1.0-4.1 Matrix_1.0-9 >>> lattice_0.20-10 zoo_1.7-9 >>> [31] flowCore_1.22.3 rrcov_1.3-02 pcaPP_1.9-48 >>> mvtnorm_0.9-9992 robustbase_0.9-4 >>> [36] Biobase_2.16.0 BiocGenerics_0.2.0 >>> >>> loaded via a namespace (and not attached): >>> [1] feature_1.2.8 KernSmooth_2.23-8 ks_1.8.10 >>> latticeExtra_0.6-24 RColorBrewer_1.0-5 >>> [6] stats4_2.15.1 >>> >>> >>> Thank you! >>> Monnie >>> >>> Monnie McGee, PhD >>> Associate Professor >>> Statistical Science >>> Southern Methodist University >>> Office: 214-768-2462 >>> Fax: 214-768-4035 >>> Website: http://faculty.smu.edu/mmcgee >>> _______________________________________________ >>> 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 >>> >> >> [[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 >> > > > -- Computational Biology / Fred Hutchinson Cancer Research Center 1100 Fairview Ave. N. 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