Add densmap embed method and fix binning-summary cluster column bug

[evanroyrees]

• :snake: Add densmap --embed-method to autometa-kmers entrypoint
• :snake: Add trimap --embed-method to autometa-kmers entrypoint
• :memo: Add TODO comments for easy addition of denSNE when it is easily available through conda or pip installation
• :bug: Change hardcoded 'cluster' column in autometa-binning-summary to cluster_col variable

Some comparisons of these methods are explored here: https://github.com/WiscEvan/embed_methods

[Sidduppal]

Trimap runs successfully however, I'm getting an error on running densmap. Command run: autometa-kmers --fasta 78mbp_metagenome.bacteria.fna --kmers 78mbp_metagenome.kmers.tsv --size 5 --norm-output 78mbp_metagenome.kmers.normalized.tsv --embedding-output 78mbp_metagenome.kmers.embedded_densmap.tsv --embedding-method densmap Error: Traceback (most recent call last): File "/home/sidd/miniconda3/envs/autometa/bin/autometa-kmers", line 33, in <module> sys.exit(load_entry_point('Autometa==2.0a0', 'console_scripts', 'autometa-kmers')()) File "/home/sidd/miniconda3/envs/autometa/lib/python3.8/site-packages/Autometa-2.0a0-py3.8.egg/autometa/common/kmers.py", line 738, in main embedded_df = embed( File "/home/sidd/miniconda3/envs/autometa/lib/python3.8/site-packages/Autometa-2.0a0-py3.8.egg/autometa/common/kmers.py", line 609, in embed X = dispatcher[method](**method_args) File "/home/sidd/miniconda3/envs/autometa/lib/python3.8/site-packages/Autometa-2.0a0-py3.8.egg/autometa/common/kmers.py", line 588, in do_UMAP return UMAP( TypeError: __init__() got an unexpected keyword argument 'densmap'

[Sidduppal]

Step by step tutorial under documentation was not changed (link). You should mention the new options available in the usage table and maybe link to your Jupyter notebook (under advanced usage section) so the user can visually see the difference between them as well?

[evanroyrees]

Step by step tutorial under documentation was not changed (link). You should mention the new options available in the usage table and maybe link to your Jupyter notebook (under advanced usage section) so the user can visually see the difference between them as well?

Whoops. Missed this, thanks 🙏 . Good idea. Will do 👍