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

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.