tutorial/documentation to use oligo/affy for mta1.0 Affymetrix arrays
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iankoudinova ▴ 10
@iankoudinova-10860
Last seen 8.3 years ago

I want to run Bioconductor packages on mta1.0 affymetrix arrays. I see that there are pd.mta.1.0, mta10stprobeset.db and mta10sttranscriptcluster.db available. There is no workflow for this type of arrays yet availbale. I tried to use affy, and received the message that

The affy package is not designed for this array type.
Please use either the oligo or xps package.

Can anyone give me some instructions what should I use, what kinds of files should be present in the current directory? Do I need to upload something from Affymetrix? I do already have mta10 cdf environment.

I built cdf environment for this type of arrays and run the local QC script which requires simpleaffy, affyPLM, affyQCReport, arrayQualityMetrics. It does work fine with mta10cdf environment I provided.  It helps me to choose outliers  Now  I want to run differential expression analysis on the same CEL files of mta1.0 arrays. 

 

Thank you

mta10 affy analysis • 2.1k views
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@james-w-macdonald-5106
Last seen 13 hours ago
United States

It depends on what you intend to do with the MTA array. The main selling point for these arrays is that you can test for differential transcript abundance. If you want to do that sort of thing, then the only recourse I know of is to use Affy's software (Expression Console followed by Transcriptome Analysis Console).

If instead you want to use the array like a Gene ST array, and just summarize all probes for each transcript, then the workflow isn't different than any other Affy microarray.

library(oligo)
dat <- read.celfiles(list.celfiles()) 
## assuming you are running R in the dir with the celfiles
## otherwise you need to do
dat <- read.celfiles(filenames = <vector of file names with path>)
eset <- rma(dat)

Then make comparisons using something like limma.

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iankoudinova ▴ 10
@iankoudinova-10860
Last seen 8.3 years ago

Ok. Thank you. It is very helpful. 

Now is the question how to convert mta1.0 probe set ids to gene symbols and/or entrez?

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To annotate any microarray, you use the corresponding ChipDb package. In this case it's the mta10sttranscriptcluster.db package, and you would use the select function.

symbols <- select(mta10sttranscriptcluster.db, <vector of IDs>, "SYMBOL")

or perhaps mapIds

symbols <- mapIds(mta10sttranscriptcluster.db, <vector of IDs>, "SYMBOL", "PROBEID")

There are vignettes for the AnnotationDbi package that explain things, and I gave a workshop at BioC2016 that may be useful as well.

 

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