I am having trouble using my results from DESeq2 when comparing the differential expression of bacterial genes between disease and control to then calculate the Bray-Curtis dissimilarity and subsequently plot a PCoA.
My output from DESeq2 I have saved as a data frame. It consists of 6000 rows which are the gene names, and two columns, one for p value ( all are <0.05) and one for log2FOldChange > 1. The data frame is called siggenes1. Do I need to normalize my data before running the Bray-Curtis and PCoA? I thought that this was already done through DESEq2, but looking at my code which I can provide, I haven't included normalisation=T when carrying out the DESeq2.
Or would I need to normalise using the sweep function the initial data prior to using DESeq2?
My code for Bray-Curtis Dissimilarity
vegDistOut=vegdist(t(siggenes1),"bray")
The above gets 1 value which is 0.995. Now I am a bit lost as to how I would devise code for plotting a PCoA with this, as my next bit of code is wrong.
pcoaOut=pcoa(vegDistOut)
Error in array(STATS, dims[perm]) : 'dims' cannot be of length 0
I cannot proceed anymore because of the above steps.
If anybody could please help, I would be really grateful. Thank-you