Hi Modzari,

This is more of an R problem and less of a WGCNA or RNAseq/array problem. What the code you pasted does, is import an annotation file which is a series of columns with gene name, probe name, genomic coordinates etc, and associate those annotations with the results of the correlation test performed as cor(datExprFemale,datTraits,use="p"). To adapt this you would 1. Run the correlation test on your own trait data and 2. associate the results with your own annotation file. To associate the results you just need to use a key value (gene ID, probe ID, transcript ID) that exists in both your datExpr dataframe and your annotation file. Then you use any number of functions to put them together including merge() from base, or join(), from dplyer to combine the tables. The tutorial uses match() followed by a square bracket subset but I find that clunky. I prefer to use the join family of functions from dplyr.

I'm shooting in the dark without running the whole tutorial myself but a simplified version of the above would look like this:

#read anntoations
GeneAnnotation=read.csv(file="GeneAnnotation.csv")

#get the gene names. Looks like datExprFemale is wide??
gene = names(datExprFemale)

# run the correlation
datGS.Traits=data.frame(cor(datExprFemale,datTraits,use="p"))

#flip the dataframe if it is indeed wide
datGS.Traits = t(datGS.Traits)

#add the genes
datGS.Traits$gene = gene

#make sure you have a 'gene' in your annotation file for the join to work
datGS.Traits.annotated = dplyr::full_join(datExprFemale, datGS.Traits, by='gene')