Hi all,
I want to normalize the Illumina Infinium methylation microarray data by lima, or by minfi or other programs you would recommend.
The online available GEO... has: *family.soft data, matrix file, and RAW data like: v1.1.bpm, v1.2.bpm, *.csv, manifest/header_descripton.xls. and RAW data with: TargetID Proband393_mother.Signal_A Proband393_mother.Signal_B Proband393_mother.Detection Pval Proband393_father.Signal_A Proband393_father.Signal_B Proband393_father.Detection Pval and so on....
I checked the lumi tutorial and the package required IDAT data.
Could anyone tell me what data should I use to the normalization? I want to get the Methylation fractions (of Beta value) and the genomic locations of them.
I would be very grateful for help. I am new in epigenetics and still learning.
Dorota
Dear Dorota,
The normalised values for your project of interest, GSE89353, can be obtained by running this code:
library(Biobase)
library(GEOquery)
gset <- getGEO("GSE89353", GSEMatrix =TRUE, getGPL=FALSE)
if (length(gset) > 1) idx <- grep("GPL13534", attr(gset, "names")) else idx <- 1
gset <- gset[[idx]]
boxplot(exprs(gset)[,1:50])
You can then do further tests with this data using standard R functions, e.g., difference in mean between different groups, or use other packages like:
Kevin
Hi Kevin. I also noticed this problem. Can I just consider the fetched gset object(or series_matrix) as preprocessed/normalized expression value(beta value)?
In this case, the data is almost certainly normalised, as judged by the boxplot. With the above code, I obtain the Series Matrix File, which is more than likely the normalised data for whatever GEO dataset you want. However, GEO state that they cannot guarantee that every Series Matrix File is normalised. So, one has to check each time.
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Kevin, you are the best!!!! Thank you thank you thank you!!!!
If I need more help can I type to you?
Thank you again, very much Dorota
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Sure, contact me any time!