Entering edit mode
7.2 years ago
lessismore
★
1.4k
Hey everybody,
I've read a few studies on merging microarray datasets (corresponding to specific series) from GEO. Some of them RMA normalize the series data (es. GSExxx) separately and then, once merged, renormalize the whole dataset. Some of them normalize the whole dataset they intend to build basically RMA analyzing all the CEL files from multiple series (es. GSExx1, GSExx2, GSExx3, etc..).
What's the correct approach according to your opinion and, if you can, please cite some useful papers, it would be a great help,
thanks in advance!
It may depend on what question you're trying to address. It could be that you could process the data sets separately and do the merging downstream.
That's fine, but, still, after merging, you'll need to normalize it for making them comparable.
Not necessarily. It depends on what you want to do with the data. For example if you want to build a graph with genes as nodes, you could build a graph for each data set and then combine the graphs afterwards in various ways.
I want to integrate the data for following Differential expression analysis.