Hi, I have some candidate genomic regions of interest and would like to see if they are differentially expressed between two conditions. Each condition has three biological replicates.
Because I cannot define the boundaries of the candidate genomic regions exactly (they are not annotated with gene model), I thought about comparison read counts at the single nucleotide level (therefore comparison of sequencing depth) and applying some thresholds (p-value or test statistics) to define differential (continuous) regions. Is it possible for me to provide DESeq2 with read counts at single nucleotide resolution ("depth") to perform statistical tests generating statistic or p-value so that I can get significant at each base ?
Thanks for your help !!
By the way, when ChIP-seq data is analyzed by DESeq2 for differential binding (for example: diffBind), the region is pre-defined by peak calling software such as MACS. Here, the size of region is variable. If read depth is not good for DESeq2, do you think that small size of region is also not good for DESeq analysis? Do you have any suggestion for minimum size of region good for DESeq2 ?
I don’t have much suggestion for this but my concern was driven by the auto correlation more than the range of counts.