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Psy-Fer / SquiggleKit

SquiggleKit: A toolkit for manipulating nanopore signal data
MIT License
120 stars 23 forks source link

degenerated bases & scrappie squiggle #21

Closed splaisan closed 4 years ago

splaisan commented 4 years ago

IUPAC bases are apparently not supported by scrappie to create the kmers I cross-reference my scrappie request here in case someone has a solution

thanks

Psy-Fer commented 4 years ago

I've commented on the linked issue. There may be other ways to go about what you want, depending on what your goal is.

Psy-Fer commented 4 years ago

You can pm me on twitter if you wish to talk privately about that. @PsyFer

Psy-Fer commented 4 years ago

Happy to continue to chat here if your like.

splaisan commented 4 years ago

sure, let me try some now that I finally could build scrappie from source (failed miserably using conda and pip) I will get some test fast5 data and see if I can spot the two 16S primers with MotifSeq.py. I will post here when I have issues or results whichever comes first :-)

Psy-Fer commented 4 years ago

Was there an issue with my instructions for getting scrappie on python3 working with pip?

splaisan commented 4 years ago

with conda it was spitting a page of package incompatibilities but I read that the conda build is not maintained by the makers of the tool. With pip it apparently installed but the command was not available for use in the conda env ?? It could have been my server which has been so much tweaked that it sometimes makes strange things. I then took the source from the ONT git and installed it on the server with success (I could create a kmer from a primer and discover the issue with undefined bases). I am not incriminating your instruction, more think it was my server. If you want to see the errors with conda I can probably reproduce them in a fresh env.

Psy-Fer commented 4 years ago

Ahh, yes. I've not tested any of my tools with conda. Mostly because of my rather intense dislike of conda as a reliable bioinformatics framework, over just building clean and separate python environments.