For the genome-wide 6.0 array, a direct link is, and save the decompressed files to the lib/ directory. Note that the genotyping calling requires lots of CEL files.īefore performing this step, we need to download the library files from. This step uses the apt-probeset-genotype program in Affymetrix Power Tools (APT) to generate genotyping calls from the raw CEL files using the Birdseed algorithm (for genome-wide 6.0 array) or BRLMM-P (for genome-wide 5.0 array) algorithm. Substep 1.1 Generate genotyping calls from CEL files We need to log into the website to download the software (the registration is free). Next download the Affymetrix Power Tools (APT) software package from. There will be a lib/ directory that contains some PennCNV-specific library files for genome-wide 6.0 array in addition, the library files for the genome-wide 5.0 arrays and Mapping 500K arrays are in the libgw5/ and gw6/, lib500k/ directories, respectively.
These files are required for signal pre-processing and also for CNV calling. Next download the PennCNV-Affy programs and library files and uncompress the file. We need to download the PennCNV software and uncompress the file. We will try to write output files to the apt/ directory. Under this directory, there are several sub-directories: a CEL/ directory that stores the raw CEL files for each genotyped sample, a lib/ directory that stores library and annotation files provided by Affymetrix and by PennCNV-Affy. Suppose all the files from a genotyping project is stored in a directory called gw6/. The goal of the first step is to generate the cross-marker normalized signal intensity data from an Affymetrix genotyping project to a text file, so that it can be analyzed subsequently by the PennCNV software. Generate the signal intensity data based on raw CEL files If the user has only a few CEL files, then it is necessary to use the default canonical clustering file in the PennCNV-Affy package, but in this case the CNV calls may not be reliable. For this protocol to work, one need to use at least 100 CEL files to generate a reasonably good clustering file. The procedure below outlines how to process raw CEL files and generates canonical genotype clusters, then convert signal intensity for each sample to LRR/BAF values, then generates CNV calls.
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