I am a beginner in bioinformatics and have a question.
In RNA-seq analysis, we can obtain gene counts values and compare gene expression levels using DESeq2. This allows for analyses such as heat maps, volcano plots, and pathway analysis.
However, in the case of ATAC-seq, when comparing control and experimental groups using DiffBind, multiple peaks can exist within a single gene, and these peaks can either increase or decrease. Given that differential accessibility regions (DARs) can open or close within a single gene, depending on the peak or location (such as the distal intergenic, promoter, exon, intron, etc.), I am curious about how heat maps or other downstream analyses are possible in ATAC-seq.
Thank you.
You need to match peaks to genes. That can be by proximity plus by some common pattern, for example only DARs that are more accessable to genes that are overexpressed. Of course a closing peak could be a closing reporessor, hence leading to overactivation of the gene. But there is still to my knowledge no reliable and robust way to infer all that, so people often enough just say "more open - gene overexpressed" and ignore peaks that do not fit into this oversimplified construct. This entire peak-to-gene assignment problem is a big mess and not at all solved in the very least.