Hello,
I am doing an RNA-seq data analysis. I already have several spesific gene as my target. What I want to do is actually comparing the gene expression level with the SNP mutation. So, for now, I want to get the gene expression level with this RNA-seq data. Because of my analysis focus on SNP and gene expression analysis, I don' have any interest in between group differential expression analysis. I already follow DESeq2 tutorial but I only get the fold change difference for 2 groups, normal and disease. So, the question is, I want to check the fold change to 1 of the sample as the base. I imagine like this. I have 14 sample. I will have fold change for difference between 1 and 2, 1 and 3, and so on, until 1 and 14. So, is this method possible to do in DESeq2 and probably you can share your idea how to do this with DESeq2. Thank you very much for your help.
Hmm. I am a bit confused here. So, basically, for this particular gene, the info about possible SNP is already there. My task now is to check the SNP for each sample and then try to make some correlation between gene expression and thos SNP. For example, for SNP type 1, the gene expression level is reduced half if compared to SNP type2. So, what you mean is I just can compare the read counts for those comparison? I'm still confused whether read counts can be interpreted as gene expression level.
If you already know what samples have the SNP of interest then theoretically you could just visualise the normalised counts of that gene, if you want to see gene expression effects on the SNP. If you're doing SNP detection then DESeq2 is not going to do that for you, you'll need to do something like follow the GATK pipeline for SNP and Indel calling.
"I'm still confused whether read counts can be interpreted as gene expression level"
Well, that's what DESeq2 uses to quantify gene expression, integer gene level counts. What else could you use as a metric for 'gene expression'?
For SNP detection, I will do another workflow because the sample is separated between RNA-seq and exome seq. So, in conclusion, I just can compare the normalized count as the basis of comparison between sample. Ok. Thank you so much for your explanation.