sourmash taxonomy visualization brainstorm

Relevant Issues/PRs:

• sourmash-bio/sourmash#1515
• sourmash-bio/sourmash#969
• sourmash-bio/sourmash#1011 (comment)
• sourmash-bio/sourmash#985 (comment)
• sourmash-bio/sourmash#1543

Relevant Repos:

• https://github.com/dib-lab/2018-ncbi-lineages
• https://github.com/dib-lab/sourmash_databases
• https://github.com/dib-lab/2019-12-12-sourmash_viz
• https://github.com/luizirber/2020-cami
• sourmash-bio/databases#11 <- build databases from assembly_stats.txt
  • /home/irber/sourmash_databases/outputs/lca/lineages

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template:

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plots that should be acheivable from sourmash gather results

krona taxonomy plot

• publication: https://link.springer.com/article/10.1186/1471-2105-12-385
• language: javascript, perl
• execution environment: bash
• github: https://github.com/marbl/Krona
• required input: text file

BURRITO interactive plot

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BioSankey

• publication: https://www.degruyter.com/document/doi/10.1515/jib-2017-0063/html
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Biosankey (left)

Biosankey for change over time

MetaCoder

• publication: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005404
• language: R
• execution environment: R
• github:
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Heatmap

• summary:
• publication: NA; this particular heatmap is from MetaPhiAn but we could make our own
• language: python, R
• execution environment: python, R
• github: NA
• required input:

KEANU

• summary: acheives the same style as other graphics, but in pure python. Could be good inspiration for viz notebooks?
• publication: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2629-4
• language: python
• execution environment: python
• github: https://github.com/IGBB/keanu
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plots that require substantially more compute or metadata etc.

co-occurence of species in a group of metagenomes

• summary: co-occurence would need to be calculated from gather-species level summaries...probably.
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Iroki

• publication: https://www.iroki.net/wiki
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