Hello , I did chip experiment with three replicates for two conditions ( normal condition(C) and phosphate deficiency condition (P)) on Rice genome. I tried to find differential regions from two conditions.because I have three replicates I used different software to find differential region between my two treatment. For peak calling in each sample, I used Sicer. Then for finding differential sites I used different ways but I doubt about them. Diffreps: Using control/input samples
If you have control samples such as DNA inputs or IgG, you can give them to diffReps. It will calculate fold enrichment ratios for each differential site, which can be used for further filtering purposes. However, diffReps does NOT use those control samples for differential analysis.
Diffbind: it used DEseq2 , and just count reads and it did not care about finding the peaks and then finding differential sites.
the last one that I trust more, is the solution from Biostar ( Matrix example: nomenclature: c1 = control1, c2 = control2, c3 = control3 t1 = tag1 (treatment1), t2 = tag2, t3 = tag3 map all datasets independently using Bowtie2. label these to keep track of the data (by name or tag or annotation) filter the BAM results by genomic region, if you know where the mark should be located on the reference genome. Use the tool SAMtool -> Slice BAM execute peak calling "all vs all" - nine runs detail run1-3: c1 & t1, c1 & t2, c1 & t3 then do the same for c2 and c3 this will produce 9 peak calling results, which can then be compared for common peaks and downstream analysis to compare, tools in the group "Operate on Genomic Intervals" and "BEDTools" will be the most useful to start with)
now I did the last one and I run my peak calling software 9 times and i have the matrix, but i do not know for the last step , for report our result I should go for the peaks that common in all of 9 peak set or just a few of them is fine?
