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, <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE89353">GSE89353</a>, 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])


<a href="https://ibb.co/hUZkKp"><img src="https://preview.ibb.co/eX6bQU/j.png" alt="j" border="0"></a>

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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:

 - <a
   href="https://bioconductor.org/packages/release/bioc/vignettes/minfi/inst/doc/minfi.html">https://bioconductor.org/packages/release/bioc/vignettes/minfi/inst/doc/minfi.html</a>
 - <a
   href="http://bioconductor.org/packages/release/bioc/vignettes/missMethyl/inst/doc/missMethyl.html#reading-data-into-r">missMethyl</a>

Kevin
