Dear Bioconductor mailing list, I am in the process of trying to use your R/Bioconductor "aCGH" library to process my copy number data. In particular, I have copy number data (log2ratios) generated from analysis of Affymetrix Cytogenetics 2.7M arrays (http://media.affymetr ix.com/support/technical/datasheets/cytogenetics_research_solution.pdf ), which have ~2 million copy number probes, and ~400,000 SNP probes for detecting LOH. I have written a script in R to retrieve the ~2million copy number probe data in the form of log2ratios. These data are generated using apt-copynumber-cyto (part of Affymetrix Powertools) to produce .CYCHP.txt files. I have determined that the copy number log2ratios start from line 549 and continue for 2141465 rows in the aforementioned text files. Original object after parsing: > str(cnData) 'data.frame': 2141465 obs. of 23 variables: $ ProbeSetName: Factor w/ 2141465 levels "C-00IGZ","C-00IHI",..: 580623 580624 580625 580626 580627 580628 580629 1967674 580630 580631 ... $ Chromosome : Factor w/ 24 levels "1","10","11",..: 1 1 1 1 1 1 1 1 1 1 ... $ Position : int 712577 713263 714145 714635 718604 750062 752757 754192 755354 760401 ... $ 10T : num -0.268 -0.324 0.486 -0.672 -0.191 ... $ 13T : num -1.032 -0.522 0.414 -0.552 -0.901 ... $ 14T : num -0.917 -0.698 0.723 -1.475 -0.771 ... $ 15T : num -0.541 -0.161 0.248 -0.529 -0.859 ... $ 16T : num -0.469 -0.43 0.129 -0.317 -1.051 ... $ 23T : num -0.0257 0.0107 0.2888 0.3228 0.1635 ... $ 33T : num 0.071 0.959 0.422 -0.019 0.35 ... $ 34T : num -0.846 -0.471 0.48 -1.141 -0.466 ... $ 37T : num -1.014 -0.279 0.327 -0.796 -0.485 ... $ 3T : num -0.46 -0.221 0.117 0.423 -0.266 ... $ 41T : num -2.021 -0.7997 0.4713 -0.0937 -1.1054 ... $ 44T : num -0.7501 -0.2017 0.0135 -1.1092 -0.356 ... $ 4T : num 0.00255 -0.05183 0.09327 -0.2049 -0.07572 ... $ 55T : num -0.2161 -0.5777 0.1861 -0.0936 -0.1689 ... $ 56T : num 0.0622 0.1612 0.2907 0.3115 0.2649 ... $ 60T : num 0.0222 0.0937 -0.1307 0.3206 -0.0847 ... $ 61T : num 0.1707 -0.0255 0.2095 -0.0505 -0.1473 ... $ 63T : num 0.00136 -0.01699 -0.15279 -0.2546 0.06513 ... $ 8T : num -0.146 -0.101 0.389 -0.465 -0.357 ... $ IT : num -0.2524 0.2645 0.7298 -0.563 -0.0915 ... With regards to trying to use the aCGH library- I have attempted to subset my data in such a way to create a valid aCGH object through the create.aCGH() method which seems to have worked. The R statements I used were as follows: aCGH.object = create.aCGH(log2.ratios = cnData[4:23], clones.info = cnData[0:3]) colnames(aCGH.object$clones.info)[1] = "Clone" colnames(aCGH.object$clones.info)[2] = "Chrom" colnames(aCGH.object$clones.info)[3] = "kb" aCGH.object$clones.info$Chrom = as.integer(aCGH.object$clones.info$Chrom) The resultant object is as follows (each column in the $log2.ratios data-frame is a unique sample): > str(aCGH.object) List of 4 $ log2.ratios :'data.frame': 2141465 obs. of 20 variables: ..$ 10T: num [1:2141465] -0.268 -0.324 0.486 -0.672 -0.191 ... ..$ 13T: num [1:2141465] -1.032 -0.522 0.414 -0.552 -0.901 ... ..$ 14T: num [1:2141465] -0.917 -0.698 0.723 -1.475 -0.771 ... ..$ 15T: num [1:2141465] -0.541 -0.161 0.248 -0.529 -0.859 ... ..$ 16T: num [1:2141465] -0.469 -0.43 0.129 -0.317 -1.051 ... ..$ 23T: num [1:2141465] -0.0257 0.0107 0.2888 0.3228 0.1635 ... ..$ 33T: num [1:2141465] 0.071 0.959 0.422 -0.019 0.35 ... ..$ 34T: num [1:2141465] -0.846 -0.471 0.48 -1.141 -0.466 ... ..$ 37T: num [1:2141465] -1.014 -0.279 0.327 -0.796 -0.485 ... ..$ 3T : num [1:2141465] -0.46 -0.221 0.117 0.423 -0.266 ... ..$ 41T: num [1:2141465] -2.021 -0.7997 0.4713 -0.0937 -1.1054 ... ..$ 44T: num [1:2141465] -0.7501 -0.2017 0.0135 -1.1092 -0.356 ... ..$ 4T : num [1:2141465] 0.00255 -0.05183 0.09327 -0.2049 -0.07572 ... ..$ 55T: num [1:2141465] -0.2161 -0.5777 0.1861 -0.0936 -0.1689 ... ..$ 56T: num [1:2141465] 0.0622 0.1612 0.2907 0.3115 0.2649 ... ..$ 60T: num [1:2141465] 0.0222 0.0937 -0.1307 0.3206 -0.0847 ... ..$ 61T: num [1:2141465] 0.1707 -0.0255 0.2095 -0.0505 -0.1473 ... ..$ 63T: num [1:2141465] 0.00136 -0.01699 -0.15279 -0.2546 0.06513 ... ..$ 8T : num [1:2141465] -0.146 -0.101 0.389 -0.465 -0.357 ... ..$ IT : num [1:2141465] -0.2524 0.2645 0.7298 -0.563 -0.0915 ... $ clones.info :'data.frame': 2141465 obs. of 3 variables: ..$ Clone: Factor w/ 2141465 levels "C-00IGZ","C-00IHI",..: 580623 580624 580625 580626 580627 580628 580629 1967674 580630 580631 ... ..$ Chrom: int [1:2141465] 1 1 1 1 1 1 1 1 1 1 ... ..$ kb : int [1:2141465] 712577 713263 714145 714635 718604 750062 752757 754192 755354 760401 ... $ phenotype : NULL I have tried to make this object resemble the structure, and data types, as reported in the aCGH vignette example data sets. The only column I see missing is the aCGH.object$clones.info$Target column. I am unsure of what the latter is meant to detail. When I attempt to generate basic plots of my data, via: plot(aCGH.object), plotGenome(aCGH.object), or plotFreqStat(aCGH.object), then I get graphs that appear overly noisy, and in which the chromosomal markers appear not to be linked to the dataset correctly as they are all bunched towards the left-handside of the graphs. Copies of the graphs are here: https://www.dropbox.com/s/9z3n70arvxir2iu/aCGH.cn.plot.png https://www.dropbox.com/s/uzoont4mvratqsz/aCGH.cn.plotFreqStats.png https://www.dropbox.com/s/12fn3lwnfosaqpc/aCGH.cn.plotGenome.png As such, my question essentially is: Have I created the aCGH object correctly or am I missing something? Many thanks for your time and assistance. Yours sincerely, Ryan -- output of sessionInfo(): > sessionInfo() R version 2.15.2 (2012-10-26) Platform: x86_64-unknown-linux-gnu (64-bit) locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 [7] LC_PAPER=C LC_NAME=C [9] LC_ADDRESS=C LC_TELEPHONE=C [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C attached base packages: [1] stats graphics grDevices utils datasets methods base -- Sent via the guest posting facility at bioconductor.org.