Normalize the data- coding

Now I am back to normalizing the data. I have a datafile I think I can work with. I need to figure out how to normalize all data to a single gene.

http://stackoverflow.com/questions/28334066/normalize-all-data-to-single-gene-observation-in-r

Great! another solution to my problem. I just love the stack overflow community. Great advice and a fun model to encourage participation.

So I normalized my data as suggested:

        df11<- group_by(df10g,type,pt.num)  
        df11<- mutate(df11, normIGF2R= value/value[GeneID=="IGF2R"])
        df11<-mutate(df11, log2normIGF2R = log2(normIGF2R))

But then I realized that I was going to try the T/D ratios of the normalized data and converted back to the format with T and D in separate columns sorting by patient to allow for the ratio columns

 df11b<- mutate(df10b, DnormIGF2R= D/D[GeneID=="IGF2R"], TnormIGF2R=T/T[GeneID=="IGF2R"])
        df11b<-mutate(df11b, NormT.D = TnormIGF2R/DnormIGF2R, log2NormT.D=log2(NormT.D))

So my data is normalized, log2, and T/D ratios. I can compare all the data by heatmaps.