I have  a Total RNA TrueSeq Illumina Stranded Paired-end Ribo0 Library.

I'm using Star to get a matrice of reads count.

I dont know which column count from output to take into account to make differential gene expression analysis.

As they say [here][1]

> Outputs read counts per gene into ReadsPerGene.out.tab file with 4
> columns which correspond to different strandedness options:
> 
> column 1: gene ID
> 
> column 2: counts for unstranded RNA-seq
> 
> column 3: counts for the 1st read strand aligned with RNA (htseq-count
> option -s yes)
> 
> column 4: counts for the 2nd read strand aligned with RNA (htseq-count
> option -s reverse)
> 
> Select the output according to the strandedness of your data.
> 
> Note, that if you have stranded data and choose one of the columns 3
> or 4, the other column (4 or 3) will give you the count of antisense
> reads.

I launch rseqc infer_experiment.py to check library preparatin of my data.

> It returns that fraction of reads were explained by  the following
> combination 1+-,1-+,2++,2-- meaning :
> 
> read1 mapped to ‘+’ strand indicates parental gene on ‘-‘ strand
> 
> read1 mapped to ‘-‘ strand indicates parental gene on ‘+’ strand
> 
> read2 mapped to ‘+’ strand indicates parental gene on ‘+’ strand
> 
> read2 mapped to ‘-‘ strand indicates parental gene on ‘-‘ strand

From what I understood, column4 (htseq-count -s reverse) seems to be the good count regarding the library. I have selected column 4.
But I was wondering what about the column 3 (which describe antisense reads).

For differential gene expression analysis, which count I need to use ?

What to do with column 3 antisense reads ? Is it a kind of artefact ? or do I have to pull column 3 and 4 together ?

Thanks for your help.



  [1]: https://groups.google.com/forum/#!topic/rna-star/gZRJx3ElRNo
You want column 4. Column 3 will presumably give you funky results when you have overlapping genes. Don't add anything together, just directly use column 4.