Computational protocol: Quality Visualization of Microarray Datasets Using Circos

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Protocol publication

[…] Microarray data handling was performed in R (2.15.0), using the latest version of Bioconductor []. Microarray raw data was obtained using the GEOquery package [] and batch processed using the affy package []. Additionally we used affy to calculate potential candidate arrays for RNA degradation. We performed quality control tests using the yaqcaffy package, which provides routines that are dedicated to Affymetrix arrays. We calculated all outliers in average background and average noise. Additionally we estimated outliers in both house-keeping probes (i.e., β-Actin and GADPH), as well as outliers in the internal spike-in probe calls and poly-A controls. Finally all microarrays were processed using quantile normalization of the RMA package without background adjustment []. Subsequently principal component analysis was performed using the pcaMethods package []. The scores of the mean centred first principal component were obtained for visualization. [...] All quality control analysis results were summarized using R and then all dedicated Circos input files were generated by use of the proposed method (R code and a demo are publicly available at: Inside an R command shell the proposed method can easily be executed, calling the following routine: > writeCircos.files(data, celNames, workdir, fileName, pathToCircos) Where data presents an affyBatch object containing the raw data, celNames denotes all Affymetrix cel-file names used in the analysis, workdir is the path to the current directory, filename names the resulting Circos QC plot and pathToCircos leads to the home directory of Circos. Circos [] version 0.6 and strawberry Perl ( version 5.1.16 was used to generate all circular quality plots. Note that the Circos method needs to be called by the Perl interpreter, i.e., > perl bin/circos –conf C:\Path\to\where\circosFiles\are\located\circosQCconfig.txt […]

Pipeline specifications