Hello!

I am new to RNA sequencing analysis and trying to assess expression of a particular gene and its isforms in 2 treatment conditions using DEXseq. The dataset I have has no replicates though. The data for each sample has been broken down in to seven fastq files. Since the data is paired ended I have 14 fastq files for each sample. Each fastq file was entered into tophat2 as paired ended data. Then I concatenated the resulting seven accepted_hits.bam files together, so that I can feed them in to HTseq. 

I have copied the command for count.txt file generation here. In that I have stated my data are paired ended while putting a single merged bam file in. Is this the correct way to put my data in? I want to clarify this because I get some errors in following steps. 

python dexseq_count.py output_from_dexseq_annotation.gff -p yes -f bam -r name

mutant_merged.bam DEXseq_count.txt

This is the error I get with its command.

> dxd = estimateDispersions( dxd )
using supplied model matrix
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
In addition: Warning message:
In MulticoreParam(workers = 1) :
  MulticoreParam not supported on Windows. Use SnowParam instead.

If anyone could give your opinion on this matter it will be a huge help.  

Thank you very much

Pabodha