Open stephenturner opened 6 years ago
I thought this code was helpful to visualize the ABRicate results. In particular, @stephenturner implemented a way to get the consensus coverage information for genes with overlapping intervals in the ABRicate output, and he parsed the files by dataset, assembler, and trim value. This might be a future idea for visualizing results in the antibiotic resistance Jupyter notebook, or it could be a standalone script for data visualization. The dotted line shows the 90% coverage threshold, which is the default for SRST2 gene detection.
not sure what kind of capability python has for doing this. i had to treat the coverage intervals as genomic ranges and use plyranges (a dplyr-like interface for manipulating ranges) to do a grouped interval reduction.
I don't know either, but I appreciate you sharing this! It looks much better than what I was trying to sketch out as a visualization idea.
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