Good morning, First of all, thanks for answering so fast. Its really helpful to be able to talk with the main creator of the library.
Going back to the topic, sorry I didn't express myself properly. I "have no idea" what the CEL files contain so, the idea is to analyze the microarrays using, the FreqB, LRR and genotypes. Some of them can are tumoral but I can't know. I will use the genotype to classify the probes in AA, Ab and BB in order to study the FreqB compared with LRR and use an external program called MAD. So, you said CRLMM is not implemented for GenomeWideSNP 6.0, may I can contribute implementing it? Anyway, thank you to share with us the aroma.affymetrix suite. El viernes, 22 de marzo de 2013 19:31:10 UTC+1, Henrik Bengtsson escribió: > > Hi Carles, > > the quick answer it that aroma.affymetrix only implements the CRLMM > method for the 100K (Mapping50K_Xba142 and Mapping50K_Hind142) and > 500K (Mapping250K_Nsp and Mapping250K_Sty) chip types. For newer > methods you need to turn to the Bioconductor 'oligo' package. > > However, what are you going to use the genotypes for? I'm asking > because it is rather common, and according to me incorrect, to try to > call genotypes in tumor samples. Genotypes are really only defined in > normal/germline genomes and most (all?) genotype methods assume that > the samples are such. Calling "genotypes" in tumors is rather a > problem of inferring parent-specific CNs (PSCNs) - not at the > SNP-by-SNP level but in segments along the genome. Contrary to normal > PSCNs ("genotypes"), tumor PSCNs may not take discrete levels due > clonality and normal contamination. In other words, if you do indeed > have tumors, it does not make sense to use CRLMM on them. Instead you > want to to PSCN segmentation/calling. > > Hope this helps > > Henrik > > > On Fri, Mar 22, 2013 at 7:47 AM, Carles Hernández > <kurag...@gmail.com<javascript:>> > wrote: > > Good afternoon, > > > > I am trying to analyse a set of CEL files from Affymetrix GenomeWideSNP > 6.0 > > and get its LRR, FreqB and genotype (for all individuals and for all > > chromosomes). > > > > I have started with the vignettes "CRMA (v1): Total copy number analysis > > using CRMA v1 (10K, 100K, 500K)" and "CRMA (v2): Estimation of total > copy > > numbers using the CRMA v2 method (10K-CytoScanHD)" since I am new in > this > > world of microarrays analysis. > > > > But I didn't fine any way to retrieve the genotype I moved to "CRLMM > > genotyping (100K and 500K)". > > > > So, from both methods I can get the LRR and FreqB with extactCNT of with > > extractTotalAndFraqB but only from the second one (CRLMM) I can use the > > extractGenotypes (becouse the chiptype's crlmm model is required). On > the > > other hand when I try to create the crlmm model for GenomeWideSNP 6.0 > the > > following error succeed: > > > > > > Exception: Cannot fit CRLMM model: Model fitting for this chip type is > not > > supported/implemented: GenomeWideSNP_6 > > at #02. CrlmmModel(ces, tags = "*,oligo") > > - CrlmmModel() is in environment 'aroma.affymetrix' > > at #01. process_dataset("GenomeWideSNP_6", "gal", verbose = TRUE) > > - process_dataset() is in environment 'R_GlobalEnv' > > Error: Cannot fit CRLMM model: Model fitting for this chip type is not > > supported/implemented: GenomeWideSNP_6 > > > > > > So... Am I doing something wrong? If no, is there some way to get the > full > > set of data I need (sample's name, sample's position, chromosome, LRR, > FraqB > > and genotype) using a single method? > > > > My full code-snippet: > > > > library( 'aroma.affymetrix' ) > > > > > > write_table <- function( dataset, file_name ) { > > [...] > > } > > > > process_dataset <- function( dataset_name chip_type ) { > > cdf <- AffymetrixCdfFile$byChipType( chip_type ); > > csR <- AffymetrixCelSet$byName( dataset_name, cdf=cdf ); > > ces <- justSNPRMA( csR, normalizeToHapmap=TRUE, returnESet=FALSE ); > > crlmm <- CrlmmModel( ces, tags="*,oligo" ); > > units <- fit( crlmm, ram="oligo" ); > > callSet <- getCallSet( crlmm ); > > > > > > gi <- getGenomeInformation( cdf ); > > > > > > for( array in 1:length( csR ) ) { > > ds <- NULL; > > ce <- getFile( ces, array ); > > for( chr in chr_list ) { > > chrunits <- getUnitsOnChromosome( gi, chromosome=chr ); > > chrnames <- getUnitNames( cdf, units=chrunits ) > > pos <- getPositions( gi, units=chrunits ); # / 1e6; > > cf <- getFile( callSet, array ); > > calls <- extractGenotypes( cf, units=chrunits ); > > dta <- extractTotalAndFreqB( ce, units=chrunits ); > > theta <- dta[,"total"]; > > > > ceR <- getAverageFile( ces ); > > dataR <- extractTotalAndFreqB( ceR, units=chrunits ); > > thetaR <- dataR[,"total"]; > > > > l2r <- log2(theta/thetaR); > > ds <- add_to_ds( chrnames, rep( chr, length( chrnames ) > ), > > pos, l2r, dta[,"FreqB"], calls ); > > } > > colnames( ds ) <- c( "Name", "Chr", "Position", > "Log.R.Ratio", > > "B.Allele.Freq", "GType" ); > > write_table( ds, paste0( getName( ce ), ".txt" ) ) > > } > > } > > } > > > > process_dataset( "GenomeWideSNP_6", "gal" ) > > > > -- > > -- > > When reporting problems on aroma.affymetrix, make sure 1) to run the > latest > > version of the package, 2) to report the output of sessionInfo() and > > traceback(), and 3) to post a complete code example. > > > > > > You received this message because you are subscribed to the Google > Groups > > "aroma.affymetrix" group with website http://www.aroma-project.org/. > > To post to this group, send email to > > aroma-af...@googlegroups.com<javascript:> > > To unsubscribe and other options, go to > http://www.aroma-project.org/forum/ > > > > --- > > You received this message because you are subscribed to the Google > Groups > > "aroma.affymetrix" group. > > To unsubscribe from this group and stop receiving emails from it, send > an > > email to aroma-affymetr...@googlegroups.com <javascript:>. > > For more options, visit https://groups.google.com/groups/opt_out. > > > > > -- -- When reporting problems on aroma.affymetrix, make sure 1) to run the latest version of the package, 2) to report the output of sessionInfo() and traceback(), and 3) to post a complete code example. 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