Hello to all,
I have previously performed gene expression analysis using R to find hub genes that were significantly different in expression from control genes, I mean differentially expressed genes (DEGs). In some articles I red about weighted correlation network analysis (WGCNA) that its concepts is very similar to those of finding DEGS.
I want to know if anyone has ever done WGCNA in R?
Does it have a special command?
Do I have to install a specific DEGs package? Or Is this analysis different from the gene expression analysis that determines the DEGs ?
I am very grateful for the guidance of experts in this field.
Dear Maryam Rahimi-Tesiye ,
Look the link, maybe helpful.
Article Weighted Correlation Network Analysis (WGCNA) Applied to the...
Regards,
Shafagat
Well, getting WGCNA to work is a litlle bit of work. It tooks me about a year to master. There are multiple online tools that allows analysis to be done without R but these are limited in their tuning ability. I recommend using Cemitool (google it for the links) as an R package, much simpler to use than the original WGCNA package. There is also the Bionero package, very handy as well. You will need at least 15 samples to perform a reliable analysis. Teh concept of WGCNA is not very similar to DEG, the algorithm will capture DEG AND highly correlated genes (that are not necessarily DEGs). Finally, WGCNA will capture the hubs of your GCN, something not done by DEG since it is an analysis gene by gene. Good luck but no luck without work...
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