Hallo!
I would like to get some advice or recommendations from you about the integrated miRNA-mRNA analysis pipeline. Here is what I would like to do:
- integrate the microarray data from microRNA and mRNA experiments, however taking into account their differential expression and, moreover, those data won't be matched (just microarray data from GEO for miRNA and mRNA in the same cancer, e.g. breast cancer),
- take into consideration the signaling pathways, which are altered, as miRNA targets some involved genes,
- and visualize the significantly altered miRNA and their targeted genes among my datasets in e.g. Cytoscape software.
I performed such analysis using MAGIA2 web-tool, however it was very simple and I am not sure about the differential expression calculation, as MAGIA calculates it on its own. There is a lot of papers with similar studies, but I can see that there is a lot of different approaches, a lot of available tools and different pipelines, so I am not sure which can I treat as the most reliable and the best recently available.
I will be grateful if you suggest something :)
could you elaborate on what you mean by "differential expression"? do you mean within each microarray experiment or combining multiple experiments/platforms and find the DEGs across those in different conditions? the way you go by identifying DEGs will influence all the downstream analysis.
beside that, the pipeline "get DEGs --> look at what they do --> find a nice way to show a model of interactions" works pretty good
Differential expression I mean combining those multiple experiments, as the microRNA and mRNA data would not be matched. In addition, I would like to present few analysis for some cancer types among one work, so the results from each platform should be comparable, I think.
Getting DEGs - did you mean by limma? And then inetgrate it with my differentially expressed miRNAs or in reversed order?