Baiting for ITS1-5.8S-ITS2 ribosomal regions about getorganelle HOT 1 CLOSED

Hi Max,

Thanks for reaching out with detailed information.

• (1) It's expected to be either circular or linear. For more information, please see here https://github.com/Kinggerm/GetOrganelle/wiki/FAQ#why-does-getorganelle-generate-a-circular-genome-or-not-for-embplant_nrfungus_nr.
• (2&3&4). A shorter length is problematic. It results from the conservative shortcut that the current GetOrganelle version took, which only assigns the unique label to only one contig, which should work with a complete circular result but not the other way around. I have improved this in the next version (available at the intermediate_graph branch); however, it will take a while for me to test the new version comprehensively before releasing it.
  I believe you are doing step 4 manually and correctly. The filtered*fastg file can be helpful too. I usually check it rather than the original fastg file. You can also do step 4 using a semi-manual (combining "slim_graph.py") approach.
• (5) Probably using evaluate_assembly_using_mapping.py and/or building a phylogeny as you did.
• (6) Yes and no. You can input single-end short read using -u. It's not compatible mainly because using long error-prone reads alone can be problematic. I'm developing another tool (Traversome) for combining short- and long- reads to solve a more generic problem.
• (7) It depends on how diverged the sequences are. If it were plastomes within angiosperm scope, which evolved slowly, I would say no influence at all. I don't know much about animal ITS. But you can easily confirm this by using a more related label.

Extra tip, given the depths & the graph, you can speed up each run by using even a larger -w and fewer rounds.

Best,
Jianjun

from getorganelle.