Hello All, I need to analyze certain rna seq data. In the past I have done a simple wt(n=3) vs mutant(n=3) analysis following these steps(please correct me if this is not right):

1. Trimming: trimmomatic
2. Quality : fastqc, picard
3. alignment : Hisat2 align each replicate as is
4. quatification: stringtie
5. differential gene expression: use the -Aflag in stringtie and prepDE.py python file to build a matrix compatible with deseq2 and design would be WT,WT,WT,MT,MT,MT
6. gsea and functional analysis based on significant gene from deseq2

Where as now i need to perform RNAseq analysis where my design in something like this

condition/timepoints    seq-lib
1   paired-end
1   paired-end
1   paired-end
2   paired-end
2   paired-end
2   paired-end
3   paired-end
3   paired-end
3   paired-end
4   paired-end
4   paired-end
4   paired-end
5   paired-end
5   paired-end
5   paired-end
6   paired-end
6   paired-end
6   paired-end
7   paired-end
7   paired-end
7   paired-end
8   paired-end
8   paired-end
8   paired-end

what steps would vary and do i need to perform for such a experimental design , do i need to merge transcripts in stringtie?

How do I go about deseq2 design I may be wrong here but is it right to say

1vs2,3,4,5,6,7,8
 2vs1,3,4,5,6,7,8

so on and so forth and if yes how do i achieve this?

Many thanks