How do I background correct an Illumina eset without using lumiB
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@gordon-smyth
Last seen 2 hours ago
WEHI, Melbourne, Australia
Dear Emma, Do you have detection p-values for each sample? If you do, then the neqc() function in the limma package can background correction the Illumina intensities by automatically reconstructing what the negative control values must have been for each array. See http://nar.oxfordjournals.org/content/38/22/e204 for a description of the neqc() method. Also see the Mammary Stem Cell case study in the limma User's Guide for an example of its use. (The published article and the case study assume that control probes are available, but the usage with detection p-values is similar.) Best wishes Gordon > Date: Wed, 22 May 2013 03:08:56 -0700 (PDT) > From: "Emma Bell [guest]" <guest at="" bioconductor.org=""> > To: bioconductor at r-project.org, e.bell12 at imperial.ac.uk > Cc: lumi Maintainer <dupan.mail at="" gmail.com=""> > Subject: [BioC] How do I background correct an Illumina eset without > using lumiB? > > Hello, > > I'm doing some work with publicly available microarray data sets that > I've downloaded from GEO. I'm having some trouble using the lumi package > to process Illumina BeadArray data. > > My understanding is that, normally when using the lumi package you would > use lumiR to convert your data to a lumiBatch object, which you could > then use lumiB on to background correct. I believe lumiR requires bead > standard errors in order to create a lumiBatch object, in their absence > it creates an expression set and that lumiB requires the input to be a > lumiBatch object. The data sets that I've downloaded only list mean > intensity values for each probe and in some cases an associated P-value. > Therefore I can't turn my data into lumiBatch object and thus can't > background correct with lumiB. > > The data sets that I'm trying to use are: > GSE31978 > GSE30670 > GSE22427 > GSE13674 > GSE20381 > > I've been using lumiR as follows: > >> library(lumi) >> GSEXXXXX.lumi <- lumiR("GSEXXXXX_Raw_Data.txt",lib.mapping="lumiHumanIDMapping") > > I would really appreciate any suggestions on how to background correct > these expression sets. Apologies if I've phrased this unhelpfully or > left out important information, I'm very new to both R and asking > questions to a mailing list like this. > > Thanks, > > Emma > > -- output of sessionInfo(): > >> sessionInfo() > R version 2.15.3 (2013-03-01) > Platform: x86_64-w64-mingw32/x64 (64-bit) > > locale: > [1] LC_COLLATE=English_United Kingdom.1252 > [2] LC_CTYPE=English_United Kingdom.1252 > [3] LC_MONETARY=English_United Kingdom.1252 > [4] LC_NUMERIC=C > [5] LC_TIME=English_United Kingdom.1252 > > attached base packages: > [1] stats graphics grDevices utils datasets methods base > > other attached packages: > [1] lumi_2.10.0 nleqslv_2.0 Biobase_2.18.0 BiocGenerics_0.4.0 > [5] limma_3.14.4 > > loaded via a namespace (and not attached): > [1] affy_1.36.1 affyio_1.26.0 annotate_1.36.0 > [4] AnnotationDbi_1.20.7 BiocInstaller_1.8.3 colorspace_1.2-2 > [7] DBI_0.2-5 grid_2.15.3 IRanges_1.16.6 > [10] KernSmooth_2.23-8 lattice_0.20-13 MASS_7.3-23 > [13] Matrix_1.0-11 methylumi_2.4.0 mgcv_1.7-22 > [16] nlme_3.1-108 parallel_2.15.3 preprocessCore_1.20.0 > [19] RSQLite_0.11.2 stats4_2.15.3 XML_3.96-1.1 > [22] xtable_1.7-1 zlibbioc_1.4.0 > ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}
Microarray probe limma PROcess convert beadarray lumi Microarray probe limma PROcess • 1.4k views
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