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):
- Trimming: trimmomatic
- Quality : fastqc, picard
- alignment : Hisat2 align each replicate as is
- quatification: stringtie
- differential gene expression: use the
-Aflag in stringtie and
prepDE.pypython file to build a matrix compatible with deseq2 and design would be
- 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
so on and so forth and if yes how do i achieve this?