How to simulate nanopore reads? I have looked already here: Tools for simulating Oxford Nanopore reads
. This doesn't answer my question, because it lists a few Nanopore read simulators, but I have specific problems with each of them.

I am trying to simulate some Nanopore reads. I could use NanoSim, but that tool seems to be very difficult to use. I only have a reference genome, but you need training data as well? anyone have any experience with this? I can only find bacterial and yeast data (and I want to try this on Arabidopsis thaliana reference)

Another promising tool I found, was a paper for SNaReSim, reference here:
https://ieeexplore.ieee.org/document/8031171. However I cannot seem to find the tool itself, which is also mentioned in the other stackexchange post I mentioned above. 

Does anyone have experience simulating PacBio reads with NanoSim, SNaReSim or maybe another tool? Because I am not sure about which one to use. Others like SiLiCO or ReadSim were updated 2 years ago and I believe that Nanopore technology has improved a lot in that time.

To clarify a bit on why I want to simulate data: I just want to test several tools about SV calling and simulating for a school project. All of the points mentioned in the comments I will use for the discussion, but I wanted to focus on 1 read simulator per technology and didn't know what to use, because Nanopore is difficult to simulate in that sense. That was already known to me.
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.