Hi, I am looking for modules that can analyse overlapping tiling arrays (Agilent) used for expression studies. In testing ACME, the example in the documentation fails with this error: [R 2.10.1, OSX 10.6.3] > library(ACME) > samps <- data.frame(SampleID = 1:3, Sample = paste("Sample", 1:3)) > dat <- matrix(rnorm(90000), nc = 3) > colnames(dat) <- 1:3 > pos <- rep(seq(1, 10000 * 100, 100), 3) > chrom <- rep(paste("chr", 1:3, sep = ""), each = 10000) > annot <- data.frame(Chromosome = chrom, Location = pos) > a <- new("aGFF", data = dat, annotation = annot, samples = samps) > calc <- do.aGFF.calc(a, window = 1000, thresh = 0.95) Error in function (classes, fdef, mtable) : unable to find an inherited method for function "chromosome", for signature "aGFF" Am I missing something? also are there any other modules in common use for Tiling array analysis? thanks for any help adam

The current version of Bioconductor uses R 2.11. Please update, installing current release of ACME, rerun and supply full output of sessionInfo() to get more help. On Tue, Jun 1, 2010 at 9:11 AM, adam_pgsql <adam_pgsql@witneyweb.org> wrote: > > Hi, > > I am looking for modules that can analyse overlapping tiling arrays > (Agilent) used for expression studies. In testing ACME, the example in the > documentation fails with this error: > > [R 2.10.1, OSX 10.6.3] > > > library(ACME) > > samps <- data.frame(SampleID = 1:3, Sample = paste("Sample", 1:3)) > > dat <- matrix(rnorm(90000), nc = 3) > > colnames(dat) <- 1:3 > > pos <- rep(seq(1, 10000 * 100, 100), 3) > > chrom <- rep(paste("chr", 1:3, sep = ""), each = 10000) > > annot <- data.frame(Chromosome = chrom, Location = pos) > > a <- new("aGFF", data = dat, annotation = annot, samples = samps) > > calc <- do.aGFF.calc(a, window = 1000, thresh = 0.95) > Error in function (classes, fdef, mtable) : > unable to find an inherited method for function "chromosome", for > signature "aGFF" > > Am I missing something? > > also are there any other modules in common use for Tiling array analysis? > > thanks for any help > > adam > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > [[alternative HTML version deleted]]

On Tue, Jun 1, 2010 at 9:11 AM, adam_pgsql <adam_pgsql@witneyweb.org> wrote: > > Hi, > > I am looking for modules that can analyse overlapping tiling arrays > (Agilent) used for expression studies. In testing ACME, the example in the > documentation fails with this error: > > [R 2.10.1, OSX 10.6.3] > > > library(ACME) > > samps <- data.frame(SampleID = 1:3, Sample = paste("Sample", 1:3)) > > dat <- matrix(rnorm(90000), nc = 3) > > colnames(dat) <- 1:3 > > pos <- rep(seq(1, 10000 * 100, 100), 3) > > chrom <- rep(paste("chr", 1:3, sep = ""), each = 10000) > > annot <- data.frame(Chromosome = chrom, Location = pos) > > a <- new("aGFF", data = dat, annotation = annot, samples = samps) > > calc <- do.aGFF.calc(a, window = 1000, thresh = 0.95) > Error in function (classes, fdef, mtable) : > unable to find an inherited method for function "chromosome", for > signature "aGFF" > > Am I missing something? > Yes, but that is my fault. As of the version of ACME that you are likely using (I can't tell because there is no sessionInfo()), the recommended data structure is the ACMESet rather than an aGFF. This data structure is what is used in the vignette. However, the do.aGFF.calc help is INCORRECT and the "x" argument should be an ACMESet object. So, working through your example (and thanks for the nice, reproducible example): samps <- data.frame(SampleID = 1:3, Sample = paste("Sample", 1:3),row.names=1:3) dat <- matrix(rnorm(90000), nc = 3) colnames(dat) <- 1:3 starts <- rep(seq(1, 10000 * 100, 100), 3) ends <- starts +50 # ACMESet needs ends, also, but could be equal to starts chrom <- rep(paste("chr", 1:3, sep = ""), each = 10000) a <- new("ACMESet",exprs=dat, phenoData=as(samps,"AnnotatedDataFrame"), featureData=as(data.frame(chromosome=chrom,start=starts,end=ends),"An notatedDataFrame")) calc = do.aGFF.calc(a,window = 1000, thresh = 0.95) I will fix the documentation to make things clearer. Sorry for the confusion. > > also are there any other modules in common use for Tiling array analysis? > > Not sure about common use, but check tilingArray, among others? Sean [[alternative HTML version deleted]]