Hi 

Im having alot of trouble applying DESeq2 to my metagenome gene abundance data , any advice regarding where I may be going wrong would be much appreciated.Early into my career so sorry for my ignorance.

dds <- DESeqDataSetFromMatrix(countData=spc.matrix,colData = env,design= ~ Habitat)

I have tried running estimateSizeFactors like so:

dds<-estimateSizeFactors(dds,type="iterate")

and get the following error:

Error in estimateDispersionsFit(object, fitType = fitType, quiet = quiet) : 
  all gene-wise dispersion estimates are within 2 orders of magnitude
  from the minimum value, and so the standard curve fitting techniques will not work.
  One can instead use the gene-wise estimates as final estimates:
  dds <- estimateDispersionsGeneEst(dds)
  dispersions(dds) <- mcols(dds)$dispGeneEst
  ...then continue with testing using nbinomWaldTest or nbinomLRT

I have tried to  then go on to run the estimateDispersionsGeneEst function as advised:

dds <- estimateDispersionsGeneEst(dds)

and get this error...

Error in .local(object, ...) :

  first calculate size factors, add normalizationFactors, or set normalized=FALSE

I tried to go back and reset the count data with the normalized=FALSE parameter 

countdat<-counts(dds,normalized=FALSE)

counts(dds)<-countdat

but still get the same error when i reapply the estimateDispersionsGeneEst function.

Many Thanks,

Briony