Ooops. Sorry for the question. I use to check CEL images and to further analyze quality with arrayQualityMetrics but yes, I didn't realize that the GeneFeatureSet was indicating the total number of probes in the array. Thank you again for your kind help, Best, Jose El ene 11, 2013, a las 6:46 p.m., James W. MacDonald escribi?: > Hi Jose, > > On 1/11/2013 12:05 PM, Jos? L?PEZ wrote: >> Hi, >> >> I have one more question. The GeneFeatureSet has 1102500 features >> while the vsn2 is done on 899636 features no matter whether target >> in pm is "core" (default method) or "probeset". Why vsn2 does not >> use all the features? Is that correct/normal? After sumarization, >> as expected, I have 35556 features. It is possible that the >> normalization on only part of the features can introduce some kind >> of bias in the summarization process (899636 in stead of 1102500)? > > I think you misunderstand a basic tenet of Affymetrix arrays. Not > all features on an Affy array are used to measure expression of > transcript. There are for instance thousands of features that go all > the way around the outside of the array (the oligo-dT features) that > are there only to help the scanner align itself to the chip. There > are also two big blocks of features in the middle that are not > measuring transcript either. > > You can see this if you do something like > > tmp <- log2(as.numeric(exprs(raw([,1])))) > geom <- geometry(getPD(raw)) > ## convert back to a matrix > tmp <- matrix(tmp, ncol = geom[1], nrow = geom[2]) > ## reorder because image() is weird > tmp <- as.matrix(rev(as.data.frame(tmp))) > image(tmp[1:100,1:100]) > > This shows the (still transposed) top left corner of the chip. The > checkerboard in the corner, and all the features along the top and > side are oligo-dT probes used to align. The chip name is made up of > oligo-dT features (and blanks) as well and there primarily I suppose > to look cool. > > If you just do image(tmp), you will see the big blocks in the middle > of the array. > > Does that help? > > Best, > > Jim > > > > >> >> I think the alternative to this option is i.e. make the CDF file >> and environment (to avoid the unofficial CDF) and make vsnrma in >> affy but, since oligo was designed ad hoc (to analyze Gene and Exon >> affymetrix arrays), I though it makes sense to try to find your >> help to combine vsn and oligo. >> >> Thank you for your answer, >> >> Jose >> >> El ene 11, 2013, a las 5:42 p.m., Jos? L?PEZ escribi?: >> >>> Yes, the exprs() did the job and it is allowing me to combine vsn >>> with oligo and Gene ST arrays. >>> >>> Thank you again for your kind help, >>> >>> Best, >>> >>> Jose >>> >>> >>> > library(limma) >>> > library(oligo) >>> > Data=read.celfiles(list.celfiles()) >>> Loading required package: pd.mogene.1.0.st.v1 >>> Loading required package: RSQLite >>> Loading required package: DBI >>> Platform design info loaded. >>> Reading in : ABRNA1.CEL >>> Reading in : ABRNA2.CEL >>> Reading in : ABRNA3.CEL >>> Reading in : ABRNA4.CEL >>> Reading in : ABRNA5.CEL >>> Reading in : ABRNA6.CEL >>> > Data >>> GeneFeatureSet (storageMode: lockedEnvironment) >>> assayData: 1102500 features, 6 samples >>> element names: exprs >>> protocolData >>> rowNames: ABRNA1.CEL ABRNA2.CEL ... ABRNA6.CEL (6 total) >>> varLabels: exprs dates >>> varMetadata: labelDescription channel >>> phenoData >>> rowNames: ABRNA1.CEL ABRNA2.CEL ... ABRNA6.CEL (6 total) >>> varLabels: index >>> varMetadata: labelDescription channel >>> featureData: none >>> experimentData: use 'experimentData(object)' >>> Annotation: pd.mogene.1.0.st.v1 >>> > class(Data) >>> [1] "GeneFeatureSet" >>> attr(,"package") >>> [1] "oligoClasses" >>> > raw=backgroundCorrect(Data,"rma") >>> Background correcting... OK >>> > pms=pm(raw) >>> > head(pms) >>> ABRNA1.CEL ABRNA2.CEL ABRNA3.CEL ABRNA4.CEL ABRNA5.CEL >>> ABRNA6.CEL >>> 2106 7.853059 7.635413 5.221570 5.160448 5.978796 >>> 5.767533 >>> 2107 5.990083 4.764031 4.659925 5.160448 7.067603 >>> 5.903628 >>> 2108 4.867173 4.587342 5.023095 4.762256 5.978796 >>> 6.045105 >>> 2109 10.657556 8.827158 7.679404 6.124607 11.523816 >>> 6.045105 >>> 2110 12.538396 13.906774 6.147958 5.860049 38.764281 >>> 6.843026 >>> 2111 10.241785 6.356910 4.836138 5.160448 7.067603 >>> 7.405633 >>> > class(pms) >>> [1] "matrix" >>> > pmsVSN=vsn::vsnMatrix(pms) >>> vsn2: 899636 x 6 matrix (1 stratum). Please use 'meanSdPlot' to >>> verify the fit. >>> > class(pmsVSN) >>> [1] "vsn" >>> attr(,"package") >>> [1] "vsn" >>> > pmsVSN >>> vsn object for n=899636 features and d=6 samples. >>> sigsq=0.1 >>> hx: 899636 x 6 matrix. >>> > pm(raw) <- exprs(pmsVSN) >>> > rm(pms, pmsVSN) >>> > ls() >>> [1] "Data" "raw" >>> > raw >>> GeneFeatureSet (storageMode: lockedEnvironment) >>> assayData: 1102500 features, 6 samples >>> element names: exprs >>> protocolData >>> rowNames: ABRNA1.CEL ABRNA2.CEL ... ABRNA6.CEL (6 total) >>> varLabels: exprs dates >>> varMetadata: labelDescription channel >>> phenoData >>> rowNames: ABRNA1.CEL ABRNA2.CEL ... ABRNA6.CEL (6 total) >>> varLabels: index >>> varMetadata: labelDescription channel >>> featureData: none >>> experimentData: use 'experimentData(object)' >>> Annotation: pd.mogene.1.0.st.v1 >>> > eset=rma(raw, background=FALSE,normalize=FALSE) >>> Calculating Expression >>> > eset >>> ExpressionSet (storageMode: lockedEnvironment) >>> assayData: 35556 features, 6 samples >>> element names: exprs >>> protocolData >>> rowNames: ABRNA1.CEL ABRNA2.CEL ... ABRNA6.CEL (6 total) >>> varLabels: exprs dates >>> varMetadata: labelDescription channel >>> phenoData >>> rowNames: ABRNA1.CEL ABRNA2.CEL ... ABRNA6.CEL (6 total) >>> varLabels: index >>> varMetadata: labelDescription channel >>> featureData: none >>> experimentData: use 'experimentData(object)' >>> Annotation: pd.mogene.1.0.st.v1 >>> >>> El ene 11, 2013, a las 5:07 p.m., James W. MacDonald escribi?: >>> >>>> Hi Jose, >>>> >>>> On 1/11/2013 10:31 AM, Jos? L?PEZ wrote: >>>>> Dear Jim, >>>>> >>>>> Thank you for the advise on the background correction step. >>>>> I already tryed before the whole Benilton's code but it doesn't >>>>> work at the following step. >>>>> >>>>>> pm(raw)<- pmVSN >>>>> Error: object 'pmVSN' not found >>>>> >>>>> May I ask you what this step is doing? Does it replace the pm >>>>> matrix in the raw ExpressionFeatureSet by the normalized one? >>>> >>>> Exactly. But the 'pm <-' function expects to be fed a matrix, >>>> and the pmsVSN isn't a matrix. Instead, it is a 'vsn' object, >>>> which is related to an ExpressionSet object. So you can extract >>>> the matrix of normalized data as usual, with exprs(): >>>> >>>> pm(raw) <- exprs(pmsVSN) >>>> >>>> and there was another error in my code, as summarize() won't work >>>> on a GeneFeatureSet object. Instead, you want to use rma(): >>>> >>>> eset <- rma(raw, normalize = FALSE, background = FALSE) >>>> >>>> Best, >>>> >>>> Jim >>>> >>>> >>>> >>>>> >>>>> Thank you in advance for your time and your kind help, >>>>> >>>>> Jose >>>>> >>>>>> library(limma) >>>>>> library(oligo) >>>>>> Data=read.celfiles(list.celfiles()) >>>>> Loading required package: pd.mogene.1.0.st.v1 >>>>> Loading required package: RSQLite >>>>> Loading required package: DBI >>>>> Platform design info loaded. >>>>> Reading in : ABRNA1.CEL >>>>> Reading in : ABRNA2.CEL >>>>> Reading in : ABRNA3.CEL >>>>> Reading in : ABRNA4.CEL >>>>> Reading in : ABRNA5.CEL >>>>> Reading in : ABRNA6.CEL >>>>>> pms=pm(Data) >>>>>> raw=backgroundCorrect(Data,"rma") >>>>> Background correcting... OK >>>>>> pms=pm(raw) >>>>>> pmsVSN=vsn::vsnMatrix(pms) >>>>> vsn2: 899636 x 6 matrix (1 stratum). Please use 'meanSdPlot' to >>>>> verify the fit. >>>>>> pm(raw)<- pmVSN >>>>> Error: object 'pmVSN' not found >>>>>> pm(raw)<- pmsVSN >>>>> Error in function (classes, fdef, mtable) : >>>>> unable to find an inherited method for function ?pm<-? for >>>>> signature ?"GeneFeatureSet", "missing", "missing", "vsn"? >>>>>> pmsVSN >>>>> vsn object for n=899636 features and d=6 samples. >>>>> sigsq=0.1 >>>>> hx: 899636 x 6 matrix. >>>>>> head(pms) >>>>> ABRNA1.CEL ABRNA2.CEL ABRNA3.CEL ABRNA4.CEL ABRNA5.CEL >>>>> ABRNA6.CEL >>>>> 2106 7.853059 7.635413 5.221570 5.160448 5.978796 >>>>> 5.767533 >>>>> 2107 5.990083 4.764031 4.659925 5.160448 7.067603 >>>>> 5.903628 >>>>> 2108 4.867173 4.587342 5.023095 4.762256 5.978796 >>>>> 6.045105 >>>>> 2109 10.657556 8.827158 7.679404 6.124607 11.523816 >>>>> 6.045105 >>>>> 2110 12.538396 13.906774 6.147958 5.860049 38.764281 >>>>> 6.843026 >>>>> 2111 10.241785 6.356910 4.836138 5.160448 7.067603 >>>>> 7.405633 >>>>>> class(pms) >>>>> [1] "matrix" >>>>>> ls() >>>>> [1] "Data" "pms" "pmsVSN" "raw" >>>>> >>>>>> sessionInfo() >>>>> R version 2.15.2 (2012-10-26) >>>>> Platform: x86_64-apple-darwin9.8.0/x86_64 (64-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] stats graphics grDevices utils datasets methods >>>>> base >>>>> >>>>> other attached packages: >>>>> [1] pd.mogene.1.0.st.v1_3.8.0 RSQLite_0.11.2 >>>>> DBI_0.2-5 oligo_1.22.0 >>>>> [5] Biobase_2.18.0 oligoClasses_1.20.0 >>>>> BiocGenerics_0.4.0 limma_3.14.3 >>>>> >>>>> loaded via a namespace (and not attached): >>>>> [1] affxparser_1.30.0 affy_1.36.0 >>>>> affyio_1.26.0 BiocInstaller_1.8.3 Biostrings_2.26.2 >>>>> [6] bit_1.1-9 codetools_0.2-8 >>>>> ff_2.2-10 foreach_1.4.0 GenomicRanges_1.10.5 >>>>> [11] grid_2.15.2 IRanges_1.16.4 >>>>> iterators_1.0.6 lattice_0.20-10 parallel_2.15.2 >>>>> [16] preprocessCore_1.20.0 splines_2.15.2 >>>>> stats4_2.15.2 vsn_3.26.0 zlibbioc_1.4.0 >>>>> >>>>> >>>>> ***************************************************** >>>>> Jos? P. L?PEZ-ATAYALA >>>>> Instituto de Neurociencias >>>>> CSIC - UMH >>>>> Avda. D. Santiago Ram?n y Cajal, S/N >>>>> E-03550, Sant Joan d'Alacant >>>>> Alicante, Spain >>>>> jose.lopez at umh.es <mailto:jose.lopez at="" umh.es=""> >>>>> http://in.umh.es/grupos-detalle.aspx?grupo=30 >>>>> (34) 965 919 531 >>>>> >>>>> El ene 11, 2013, a las 3:59 p.m., James W. MacDonald escribi?: >>>>> >>>>>> Hi Jose, >>>>>> >>>>>> Let's say you followed Benilton's code from https://stat.ethz.ch/pipermail/bioconductor/2010-June/033936.html >>>>>> >>>>>> library(oligo) >>>>>> cels = list.celfiles() >>>>>> raw = read.celfiles(cels) >>>>>> raw = backgroundCorrect(raw, "rma") ## I added this - you might >>>>>> want BG correction >>>>>> pms = pm(raw) >>>>>> pmsVSN = vsn::vsnMatrix(pms) >>>>>> pm(raw)<- pmVSN >>>>>> rm(pms, pmsVSN) >>>>>> >>>>>> you now have an ExpressionFeatureSet with normalized data that >>>>>> you want to summarize. You can then >>>>>> >>>>>> eset<- summarize(raw, method = "medianpolish") >>>>>> >>>>>> See >>>>>> >>>>>> ?summarizationMethods >>>>>> >>>>>> for more information. >>>>>> >>>>>> Best, >>>>>> >>>>>> Jim >>>>>> >>>>>> >>>>>> On 1/11/2013 6:17 AM, Jos? L?PEZ wrote: >>>>>>> Dear Benilton, >>>>>>> >>>>>>> I am using oligo for Mouse Gene 1.0ST arrays. In addition to >>>>>>> RMA, I would also like to pre-process with vsn. I have seen >>>>>>> previous threads related to this question in the past, (https://stat.ethz.ch/pipermail/bioconductor/2010-January/031100.html >>>>>>> , https://stat.ethz.ch/pipermail/bioconductor/2010-June/033936.html) >>>>>>> , but unfortunately, I am not bioinformatician and, although I >>>>>>> read oligo and vsn manuals, it is not easy to me to follow up >>>>>>> to summarize the vsn object. >>>>>>> May you (or someone else) please, give me some additional clue >>>>>>> to sumarize the vsn object using the oligo package. >>>>>>> >>>>>>> Thank you very much in advance for your time and your kind help, >>>>>>> >>>>>>> Jose LOPEZ >>>>>>> >>>>>>> ************************** >>>>>>> >>>>>>>> list.files() >>>>>>> [1] "ABRNA1.CEL" >>>>>>> "ABRNA2.CEL" "ABRNA3.CEL" >>>>>>> [4] "ABRNA4.CEL" >>>>>>> "ABRNA5.CEL" "ABRNA6.CEL" >>>>>>> [7] "Limma_FilterBefore_H2BGFP_jla_vsn.R" >>>>>>>> library(limma) >>>>>>>> library(oligo) >>>>>>> Loading required package: BiocGenerics >>>>>>> >>>>>>> Attaching package: ?BiocGenerics? >>>>>>> >>>>>>> The following object(s) are masked from ?package:stats?: >>>>>>> >>>>>>> xtabs >>>>>>> >>>>>>> The following object(s) are masked from ?package:base?: >>>>>>> >>>>>>> anyDuplicated, cbind, colnames, duplicated, eval, Filter, >>>>>>> Find, get, intersect, lapply, Map, mapply, >>>>>>> mget, order, paste, pmax, pmax.int, pmin, pmin.int, >>>>>>> Position, rbind, Reduce, rep.int, rownames, sapply, >>>>>>> setdiff, table, tapply, union, unique >>>>>>> >>>>>>> Loading required package: oligoClasses >>>>>>> Loading package bit 1.1-9 >>>>>>> package:bit (c) 2008-2012 Jens Oehlschlaegel (GPL-2) >>>>>>> creators: bit bitwhich >>>>>>> coercion: as.logical as.integer as.bit as.bitwhich which >>>>>>> operator: !& | xor != == >>>>>>> querying: print length any all min max range sum summary >>>>>>> bit access: length<- [ [<- [[ [[<- >>>>>>> for more help type ?bit >>>>>>> Loading package ff2.2-10 >>>>>>> - getOption("fftempdir")=="/var/folders/U+/U >>>>>>> +SFMmqcEbKkSysJQ3OYbk+++TQ/-Tmp-//RtmpKgQzWD" >>>>>>> >>>>>>> - getOption("ffextension")=="ff" >>>>>>> >>>>>>> - getOption("ffdrop")==TRUE >>>>>>> >>>>>>> - getOption("fffinonexit")==TRUE >>>>>>> >>>>>>> - getOption("ffpagesize")==65536 >>>>>>> >>>>>>> - getOption("ffcaching")=="mmnoflush" -- consider >>>>>>> "ffeachflush" if your system stalls on large writes >>>>>>> >>>>>>> - getOption("ffbatchbytes")==16777216 -- consider a different >>>>>>> value for tuning your system >>>>>>> >>>>>>> - getOption("ffmaxbytes")==536870912 -- consider a different >>>>>>> value for tuning your system >>>>>>> >>>>>>> Welcome to oligoClasses version 1.20.0 >>>>>>> Loading required package: Biobase >>>>>>> Welcome to Bioconductor >>>>>>> >>>>>>> Vignettes contain introductory material; view with >>>>>>> 'browseVignettes()'. To cite Bioconductor, see >>>>>>> 'citation("Biobase")', and for packages >>>>>>> 'citation("pkgname")'. >>>>>>> >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> ================================================================ >>>>>>> Welcome to oligo version 1.22.0 >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> = >>>>>>> ================================================================ >>>>>>> >>>>>>> Attaching package: ?oligo? >>>>>>> >>>>>>> The following object(s) are masked from ?package:limma?: >>>>>>> >>>>>>> backgroundCorrect >>>>>>> >>>>>>>> Data=read.celfiles(list.celfiles()) >>>>>>> Loading required package: pd.mogene.1.0.st.v1 >>>>>>> Loading required package: RSQLite >>>>>>> Loading required package: DBI >>>>>>> Platform design info loaded. >>>>>>> Reading in : ABRNA1.CEL >>>>>>> Reading in : ABRNA2.CEL >>>>>>> Reading in : ABRNA3.CEL >>>>>>> Reading in : ABRNA4.CEL >>>>>>> Reading in : ABRNA5.CEL >>>>>>> Reading in : ABRNA6.CEL >>>>>>>> pms=pm(Data) >>>>>>>> class(pms) >>>>>>> [1] "matrix" >>>>>>>> head(pms) >>>>>>> ABRNA1.CEL ABRNA2.CEL ABRNA3.CEL ABRNA4.CEL ABRNA5.CEL >>>>>>> ABRNA6.CEL >>>>>>> 2106 46 43 36 36 >>>>>>> 37 33 >>>>>>> 2107 38 32 33 36 >>>>>>> 43 34 >>>>>>> 2108 31 31 35 34 >>>>>>> 37 35 >>>>>>> 2109 54 46 45 40 >>>>>>> 58 35 >>>>>>> 2110 58 55 40 39 >>>>>>> 94 40 >>>>>>> 2111 53 39 34 36 >>>>>>> 43 43 >>>>>>>> pmsVSN=vsn::vsnMatrix(pms) >>>>>>> vsn2: 899636 x 6 matrix (1 stratum). Please use 'meanSdPlot' >>>>>>> to verify the fit. >>>>>>>> class(pmsVSN) >>>>>>> [1] "vsn" >>>>>>> attr(,"package") >>>>>>> [1] "vsn" >>>>>>>> pmsVSN >>>>>>> vsn object for n=899636 features and d=6 samples. >>>>>>> sigsq=0.026 >>>>>>> hx: 899636 x 6 matrix. >>>>>>>> eset=rma(pmsVSN, background=FALSE,normalize=FALSE) >>>>>>> Error in function (classes, fdef, mtable) : >>>>>>> unable to find an inherited method for function ?rma? for >>>>>>> signature ?"vsn"? >>>>>>> >>>>>>>> library(vsn) >>>>>>>> meanSdPlot(pmsVSN) >>>>>>> KernSmooth 2.23 loaded >>>>>>> Copyright M. P. Wand 1997-2009 >>>>>>> >>>>>>>> sessionInfo() >>>>>>> R version 2.15.2 (2012-10-26) >>>>>>> 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] stats graphics grDevices utils datasets >>>>>>> methods base >>>>>>> >>>>>>> other attached packages: >>>>>>> [1] vsn_3.26.0 pd.mogene.1.0.st.v1_3.8.0 >>>>>>> RSQLite_0.11.2 DBI_0.2-5 >>>>>>> [5] oligo_1.22.0 Biobase_2.18.0 >>>>>>> oligoClasses_1.20.0 BiocGenerics_0.4.0 >>>>>>> [9] limma_3.14.3 >>>>>>> >>>>>>> loaded via a namespace (and not attached): >>>>>>> [1] affxparser_1.30.0 affy_1.36.0 >>>>>>> affyio_1.26.0 BiocInstaller_1.8.3 Biostrings_2.26.2 >>>>>>> [6] bit_1.1-9 codetools_0.2-8 >>>>>>> ff_2.2-10 foreach_1.4.0 GenomicRanges_1.10.5 >>>>>>> [11] grid_2.15.2 IRanges_1.16.4 >>>>>>> iterators_1.0.6 KernSmooth_2.23-8 lattice_0.20-10 >>>>>>> [16] parallel_2.15.2 preprocessCore_1.20.0 >>>>>>> splines_2.15.2 stats4_2.15.2 tools_2.15.2 >>>>>>> [21] zlibbioc_1.4.0 >>>>>>> >>>>>>> >>>>>>> [[alternative HTML version deleted]] >>>>>>> >>>>>>> >>>>>>> >>>>>>> _______________________________________________ >>>>>>> Bioconductor mailing list >>>>>>> Bioconductor at r-project.org <mailto:bioconductor at="" r-project.org=""> >>>>>>> https://stat.ethz.ch/mailman/listinfo/bioconductor >>>>>>> Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor >>>>>> -- >>>>>> James W. MacDonald, M.S. >>>>>> Biostatistician >>>>>> University of Washington >>>>>> Environmental and Occupational Health Sciences >>>>>> 4225 Roosevelt Way NE, # 100 >>>>>> Seattle WA 98105-6099 >>>>>> >>>> >>>> -- >>>> James W. MacDonald, M.S. >>>> Biostatistician >>>> University of Washington >>>> Environmental and Occupational Health Sciences >>>> 4225 Roosevelt Way NE, # 100 >>>> Seattle WA 98105-6099 >>>> >>> >> > > -- > James W. MacDonald, M.S. > Biostatistician > University of Washington > Environmental and Occupational Health Sciences > 4225 Roosevelt Way NE, # 100 > Seattle WA 98105-6099 >