Continuing analysis based on a log-likelihood ratio? (Comparing methylation between two PoolSeq phenotypes)
I assume you don't want to spend 1-2 years developing your own method based on nanopore data, so the path forward is to convert the output into a format used by standard DMR calling programs. There's no standard format for that, annoyingly, but the general things you'll need are:


Coordinates of a C/CpG with coverage
Number of reads supporting methylation at that site.
Number of reads not supporting methylation at that site.


Typically you would do some filtering before/after making such a table so you only have decent quality calls (that would translate into some reasonable log likelihood for your data) and possibly only sites with decent (5x, 10x, 30x, etc.) coverage. You'd then feed that for all of the replicates in all of your groups into programs like bsseq, DSS or Metilene (to not so randomly select 3 examples).

If there aren't DMR finding programs already developed specifically for nanopore data I expect someone is developing it. The technology has a higher error rate, but given that bisulfite conversion as required in Illumina data also leads to a higher error rate that's not necessarily a huge issue if the methylation calling itself is reasonably accurate and the depth is high enough. Note that you probably need 10X coverage as a bare minimum unless your effect size is very very large.