Dear all,
I'm trying to process CEL file from Human gene2.0 ST array to make expression matrix file. While I tried to normalize signal using mas5 in affy package, I got following error message.
hoge<- read.celfiles(c("si cont.CEL", "si TREAT.CEL")) eset<- mas5(hoge) background correction: mas PM/MM correction : mas expression values: mas error in background correcting... (function (classes, fdef, mtable): unable to find an inherited method for function ‘bg.correct’ for signature ‘"GeneFeatureSet", "character"’
My condition is following.
sessionInfo() R version 3.2.3 (2015-12-10) Platform: x86_64-apple-darwin13.4.0 (64-bit) Running under: OS X 10.11.6 (El Capitan)
locale: [1] ja_JP.UTF-8/ja_JP.UTF-8/ja_JP.UTF-8/C/ja_JP.UTF-8/ja_JP.UTF-8
attached base packages: [1] stats4 parallel stats graphics grDevices utils datasets methods base
other attached packages:
[1] affy_1.48.0 pd.hugene.2.0.st_3.14.1 oligo_1.34.2 Biobase_2.30.0 oligoClasses_1.32.0
[6] RSQLite_1.0.0 DBI_0.5-1 Biostrings_2.38.4 XVector_0.10.0 IRanges_2.4.8
[11] S4Vectors_0.8.11 BiocGenerics_0.16.1
loaded via a namespace (and not attached):
[1] affxparser_1.42.0 GenomicRanges_1.22.4 splines_3.2.3 zlibbioc_1.16.0
[5] bit_1.1-12 foreach_1.4.3 GenomeInfoDb_1.6.3 tools_3.2.3
[9] SummarizedExperiment_1.0.2 ff_2.2-13 iterators_1.0.8 preprocessCore_1.32.0
[13] affyio_1.40.0 codetools_0.2-14 BiocInstaller_1.20.3
Could someone advise me? Best, Taiki
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written
by
ttsutsui1028 •
You might want to review this post:
Difference Between Mas5 And Rma Normalisation. Which Is More Appropriate When?
If you have HuGene arrays, you should use RMA (or GCRMA) normalization, since you don't have mismatch probes (although you have other types of control probes). You can either do this using the oligo package or affy power tools:
https://bioconductor.org/packages/release/bioc/html/oligo.html
Thank you Charles.
rma command works fine in the oligo package in my hand. However, It looks reasonable to use affy power tools rather than using R. I will try affy power tool, too. Thanks again, Taiki
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