Dear all,
So, I have a goal to find a mutation of a gene which occur in the promoter region. The SNP is already well known so I imagine my workflow is to check the SNP and then compare it to the known mutation. The problem is, I realized that the exome-seq data doesn't cover the promoter region and I think RNA-seq data also doesn't cover promoter region. My advisor tell me to find another data set which cover the promoter region but I think to find the correct data set is not that easy because my gene target is known to be transcribed in the liver and I need to find normal - cancer cohort sample. So, first question is, do you have any suggestion for me how to find the mutation which occur in promoter region or it is just impossible? I have read another similar question and the answer seems confusing to me. And the second question, do you have any suggestion how to find / to filter publicly available data which is really fit for my need? I only familiar with NCBI Geodata sets but I don't know other online resource. Thank you very much for any suggestion you have.
So it is not possible to detect SNP type which occur in promoter region from RNA-seq or Exome-seq data? My study is just the analysis data from published data and I can not do some experiment. I browsed NCBI GEO, it seems CHIP-seq or CAGE-seq data is not many and I think it is hard to find the published data which fit my study (liver cell and tumor-nontumor sample)
It is possible to detect SNPs in the promoter region from RNA-seq or Exome data, but typically these regions are not well covered in these experiments, but sometimes it is. And yes probably it will be hard to find those studies for liver cell.
So, the typical variation detection using Exome-seq or RNA-seq is not detecting the mutation in promoter region, right? With the promoter regions not well covered, probably the result will not good for making a conclusion. But I will try my luck with my gene of interest and my available data. CHIP-seq and SAGE-seq is really rare to find in NCBI GEO. Thank you.