How to simulate nanopore reads?
It is important to train an error model as NanoSim does, as we do not fully understand the error processes involved in both the nanopore sequencing process and the basecalling process. Any sort of read simulator that does not use a species-specific model is just not going to produce realistic simulated reads.

As far as datasets go, I would recommend looking at this assembly and the associated data uploaded on EMBL:


  Michael, Todd P., et al. "High contiguity Arabidopsis thaliana
  genome assembly with a single nanopore flow cell." Nature
  communications 9.1 (2018): 541.


There are several data types there, as well as an assembly to train the models on.

Is it OK to train a model using reads from one individual and a reference assembly from another individual?

Generally, it is not good to map reads from one individual to the reference genome of another individual since this introduces something called reference bias. When we align reads to a reference genome generated from the same reads, or just from other reads from the same individual we remove this problem. All true reads will map to correctly assembled parts of the genome.

Why can we train a model for nanopore reads on a reference generated from ... nanopore reads? Won't we get a bad model for indels?

Yes, well, maybe. If the reference genome has been corrected to remove indels using a tool like pilon, then you can generally presume that the reference genome has very few to no indels present as a result of sequencing error from the Nanopore/PacBio reads. As a result, the model derived from aligning reads should have the correct error profile for indels.

Again, it is important that the long-read-assembly was corrected with Illumina shotgun reads from the same individual from which the long reads were derived. Otherwise the corrected reference would have a chimaera of indels and SNPs from multiple individuals.