I know this is (very) late but I should point out that the manifest file (that is, the annotation list stored in the GSEnnnnnn_RAW.tar) was not annotated anywhere nearly as clearly as one would expect. There is a supplemental table in the manifest file that identifies all control probe_IDs, and many were not indicated as "ILMN_Controls" in annot$source as Kevin had observed.

If you load the manifest file into either RStudio or MS Excel, GPL10558_HumanHT-12_V4_0_R1_15002873_B.txt into either RStudio or MS Excel and scroll to the very bottom of the data frame (just above the column label legend), you can find a complete list of all possible control probes and the corresponding probe IDs. It's incredibly easy to miss but there is a bracketed header labeled as ' [Controls] ' that identifies the list, located at row 47242. I used MS Excel this time because I'm just too sleep deprived to reformat the file to accommodate RStudio's phobia of duplicate row names right now.

Tl;dr the manifest file contains control probe_IDs. you still may be able to query your dataset's probe_ID list and filter accordingly prior to normalization.

Hey,

Like many other Illumina studies on GEO, this study (GSE119600) does not contain the original raw data IDAT files, which is unfortunate.

GSE119600_RAW.tar just contains the probe annotations for GPL10558 Human HT-12 v4 R1 and R2 (2 separate files). GSE119600_non-normalized.txt.gz just contains a single table of expression values. i am not sure that these are suitable for lumi, but you are welcome to try.

As a beginner, the easiest option for you is to use GEO2R to obtain the expression data as an ExpressionSet object. From the main accession page ( https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE119600 ), click on the Analyze with GEO2R button.

Then, click on the R script tab, which will generate R code that you can use to obtain the data.

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Alternatively, you can adapt a previous answer of mine such that you can still use this raw data with limma:

• A: illumina Arrays Illumina HumanHT-12 V3.0 expression beadchip reading data

In this case, the annot object should be one of those annotation files in the GSE119600_RAW.tar file. The targetinfo object you will have to create yourself.

Kevin

The GSE119600 Illumina Beadchip data can be read and processed in a straightforward manner using limma package functions.

Read expression data and detection p-values:

> library(limma)
> x <- read.ilmn("GSE119600_non-normalized.txt.gz",probeid="ID_REF")
Reading file GSE119600_non-normalized.txt.gz ... ...

Background correct and quantile normalize using detection p-values. Note that limma does not require the control probe expression values because it is able to infer the mean and variance of the control probes from the detection p-values (functionality that was added to the neqc function in October 2010).

> y <- neqc(x)
Note: inferring mean and variance of negative control probe intensities from the detection p-values.

Parse the sample annotation out of the series matrix file.

> SampleInfo <- sampleInfoFromGEO("GSE119600_series_matrix.txt.gz")$SampleInfo
> Group <- SampleInfo[,"source_name_ch1"]
> table(Group)
Group
                       Control, adult                Crohn’s disease, adult 
                                   47                                    48 
               Crohn’s disease, child    Primary biliary cholangitis, adult 
                                   47                                    90 
Primary sclerosing cholangitis, adult             Ulcerative colitis, adult 
                                   45                                    45 
            Ulcerative colitis, child 
                                   48

The data is now ready for linear modeling.