how to import Agilent CGH custom design xml file into limma
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@sean-davis-490
Last seen 3 months ago
United States
On Thu, Oct 21, 2010 at 3:15 AM, Jarek Bryk <bryk@evolbio.mpg.de> wrote: > Hi Sean, > > and thanks a lot for the answer. I still need some clarification though. > > On 20 Oct 2010, at 18:31, Sean Davis wrote: > > You definitely DO NOT want to be loess-normalizing CGH data. There is an > expected positive correlation between average intensity and log- ratio; > loess-normalization will effectively eliminate that signal. > > Oops. Thanks. I got that idea from limma user guide (p. 24) - I assumed two > color normalization should be similar regardless of whether one measures > gene expression or CGH - is this where the trick is? How would you recommend > normalizing the data? Just to add some information, my custom design is > concentrated on some 1000 genic regions (genes+10kb up and downstream) > selected based on our previous experiment. These regions have very high > probe density (essentially like a tiling array - my average genomic probe > density is 170bp) Some of these regions may be copy-number-variable, but > some (majority probably) of them should not be. I have a standard set of > Agilent's 11k normalizing probes plus 5k replicated probes on the arrays as > well, but most of the genome is not covered with probes at all. > > You will need to look at your data to determine what normalization will work. In general and for future reference, when making custom designs like this, we always use a backbone of 20-30k genomic probes so that we can see a baseline. The main two issues to be concerned with are "centering" the data and removal of "wave" artifacts. There is a fair amount of literature on the latter and a bit on the former, but median-centering the data will likely not be too far off as a start. The latter may be difficult to apply to your data given the gene-centric nature of your design. > > This information is stored in the MA$Genes$SystematicName above. You > will need to split out the pieces (chromosome, position) and then use those > for the locations. You will also probably need to remove control probes. > > OK, I got the MA$genes: > > > head(MA$genes) > Row Col Start Sequence > ProbeUID ControlType > 1 1 1 0 > 0 1 > 2 1 2 0 > 1 1 > 3 1 3 0 > 1 1 > 4 1 4 0 > CCCATTCACTAATCTACATATTATCTCCATCCAACAAAAATTTCTTTCAGTAAGGTGTGG 3 > 0 > 5 1 5 0 > AAACAATCAGGTTTTCACTCTGACAGCCCAATAATGCATTTAGTTTGAAATTACACTTGG 5 > 0 > 6 1 6 0 > CTATTCTGTATCATATAGGGAGGATGCTGTCCTGGAATATCTCAAGATTGCTCAAGAC 7 > 0 > ProbeName GeneName SystematicName > 1 MmCGHBrightCorner MmCGHBrightCorner MmCGHBrightCorner > 2 DarkCorner DarkCorner DarkCorner > 3 DarkCorner DarkCorner DarkCorner > 4 A_67_P21917383 Msn chrX:93323379-93323438 > 5 A_67_P17120964 chr11:18773745-18773804 chr11:18773745-18773804 > 6 A_67_P21917619 Msn chrX:93350785-93350842 > > If I understand you correctly, I'd have to divide the content of > MA$genes$SystematicName so that it becomes something like: > > >test<-MA$genes[10:20,] # to avoid control probes in this example > >head(test) > Row Col Start > Sequence ProbeUID ControlType > 10 1 10 0 > GTTTTAAACCATCTCTGAGGTTAATGGATGGCTTTCTGGGCCAGCAG 15 0 > 11 1 11 0 > ACACAAAAGCAATTCTGGCTAGTCAAGACTTGAAAGAAACATATAAACGCACACACATTG 17 > 0 > 12 1 12 0 > GCTTCTGTGCACTCTTATTGGAAACAAGTTCTTCAGAAGAACAAATGCAGGATAAAACTT 19 > 0 > 13 1 13 0 > AAACATGAATACAGGACGGGGATGACAAATCCACGAGAAACAAAGTTAATTTCACTTC 21 > 0 > 14 1 14 0 > AACAACTATCGAGGTCTAATGAAAAGAGCATGCATTTGTCAAGGAACAGCAGGAAA 23 > 0 > 15 1 15 0 > CTCCCTCATTAGCCCATGTCGTGGAGGGTTGGCTGTGAGAAAAGT 25 0 > ProbeName GeneName SystematicName > 10 A_67_P11007835 Gm13547 chr2:29617549-29617595 > 11 A_67_P15475991 chr8:49310974-49311033 chr8:49310974-49311033 > 12 A_67_P08003555 Arl15 chr13:114808546-114808605 > 13 A_67_P01452405 Grin2b chr6:136111490-136111547 > 14 A_67_P06614048 AK042807 chr8:102166914-102166969 > 15 A_67_P21149931 Tshz1 chr18:84192155-84192199 > > > >test$Chr<-sapply(test$SystematicName,function(x){strsplit(x,":")[[1 ]][[1]]} > >test$Position<-sapply(test$SystematicName,function(x){strsplit(x,": ")[[1]][[2]]} > # there's probably an easier way of doing this... > >head(test) # but it gets the job done > Row Col Start > Sequence ProbeUID ControlType > 10 1 10 0 > GTTTTAAACCATCTCTGAGGTTAATGGATGGCTTTCTGGGCCAGCAG 15 0 > 11 1 11 0 > ACACAAAAGCAATTCTGGCTAGTCAAGACTTGAAAGAAACATATAAACGCACACACATTG 17 > 0 > 12 1 12 0 > GCTTCTGTGCACTCTTATTGGAAACAAGTTCTTCAGAAGAACAAATGCAGGATAAAACTT 19 > 0 > 13 1 13 0 > AAACATGAATACAGGACGGGGATGACAAATCCACGAGAAACAAAGTTAATTTCACTTC 21 > 0 > 14 1 14 0 > AACAACTATCGAGGTCTAATGAAAAGAGCATGCATTTGTCAAGGAACAGCAGGAAA 23 > 0 > 15 1 15 0 > CTCCCTCATTAGCCCATGTCGTGGAGGGTTGGCTGTGAGAAAAGT 25 0 > ProbeName GeneName SystematicName Chr > Position > 10 A_67_P11007835 Gm13547 chr2:29617549-29617595 chr2 > 29617549-29617595 > 11 A_67_P15475991 chr8:49310974-49311033 chr8:49310974-49311033 chr8 > 49310974-49311033 > 12 A_67_P08003555 Arl15 chr13:114808546-114808605 chr13 > 114808546-114808605 > 13 A_67_P01452405 Grin2b chr6:136111490-136111547 chr6 > 136111490-136111547 > 14 A_67_P06614048 AK042807 chr8:102166914-102166969 chr8 > 102166914-102166969 > 15 A_67_P21149931 Tshz1 chr18:84192155-84192199 chr18 > 84192155-84192199 > > That is most of the way there. The Position column needs to be numeric, so you'll want to do another split to get that down to a single number, I think. Sean > > Hope that helps. > > Thanks a lot! > cheers > jarek > > > > sessionInfo() > > R version 2.12.0 (2010-10-15) > > Platform: i386-apple-darwin9.8.0/i386 (32-bit) > > > > locale: > > [1] en_US.UTF-8/en_US.UTF-8/C/C/en_US.UTF-8/en_US.UTF-8 > > > > attached base packages: > > [1] splines stats graphics grDevices utils datasets methods > base > > > > other attached packages: > > [1] snapCGH_1.20.0 DNAcopy_1.24.0 limma_3.6.0 aCGH_1.28.0 > multtest_2.6.0 Biobase_2.10.0 > > [7] survival_2.35-8 cluster_1.13.1 GLAD_2.12.0 > > > > loaded via a namespace (and not attached): > > [1] affy_1.28.0 affyio_1.18.0 annotate_1.28.0 > AnnotationDbi_1.12.0 > > [5] DBI_0.2-5 genefilter_1.32.0 grid_2.12.0 > lattice_0.19-13 > > [9] MASS_7.3-8 preprocessCore_1.12.0 RColorBrewer_1.0-2 > RSQLite_0.9-2 > > [13] strucchange_1.4-2 tilingArray_1.28.0 tools_2.12.0 > vsn_3.18.0 > > [17] xtable_1.5-6 > > -- > Jarek Bryk | www.evolbio.mpg.de/~bryk > Max Planck Institute for Evolutionary Biology > August Thienemann Str. 2 | 24306 Plön, Germany > tel. +49 4522 763 287 | bryk@evolbio.mpg.de > > > [[alternative HTML version deleted]]
Normalization CGH probe limma Normalization CGH probe limma • 856 views
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