I'm using a GEO dataset (GSE140830) — HumanHT-12 v4 Expression BeadChip (nuID) platform — in a study, but I am having problems regarding the metadata and so how to remove outliers verified in the study. I know that it is possible to relate the info observed in the study with the data present in the metadata using affy (for example: from the series matrix file):
Data <- ReadAffy(filenames=row.names(targets), celfile.path=datadir, phenoData = targets)
In this case, the row.names carries the sample ID, but can I do something like this with Illumina data since the expression info is in table format and the table has different codes representing the samples (for example, GSM4187774 in phenoData and 5872617031_A in raw_data file)?
I believe it would be easier to rename based on what's in the expression data. But would it be possible to load this data and establish a relationship between the files in such a way as to make it easier to create groups, remove samples, and design the statistical test?
Thank you very much!