https://github.com/biocore/taxster

taxster: assigning taxonomy to organisms you've never even heard of

https://github.com/biocore/taxster

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Repository

taxster: assigning taxonomy to organisms you've never even heard of

Basic Info
  • Host: GitHub
  • Owner: biocore
  • License: bsd-3-clause
  • Language: Python
  • Default Branch: master
  • Homepage:
  • Size: 167 KB
Statistics
  • Stars: 2
  • Watchers: 9
  • Forks: 4
  • Open Issues: 3
  • Releases: 0
Created about 12 years ago · Last pushed over 10 years ago
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Readme License

README.md

taxster: assigning taxonomy to organisms you've never even heard of

Hipster Bayes

This library contains tools for working with taxonomic assignment data. This should be considered pre-alpha software. Public APIs can and will change!

Install

pip install https://github.com/biocore/taxster/archive/master.zip

Consensus taxonomy assignments from .uc files

This example illustrates how to apply the consensus taxonomy processing described in Bokulich et al (in preparation). It assumes that you have the test data files included in this repository in ./test-data.

```python import taxster

taxonomymap = {} for line in open('./test-data/uc/tax-map.tsv', 'U'): line = line.strip() if line.startswith('#') or not line: continue fields = line.split('\t') id = fields[0] tax = fields[1].split('; ') taxonomymap[id] = tax

uc = open('./test-data/uc/1.uc', 'U') consensusassignments = taxster.ucconsensusassignments(uc, taxonomymap) ```

If you'd then like to write these out to file, you can do the following. This will write the consensus taxonomy assignments to a file that can be used with biom add-metadata (compatible with biom-format >= 2.1.5, < 2.2.0).

python f = open('uc-consensus-tax.tsv', 'w') for id_, (tax, fraction, hits) in consensus_assignments.items(): tax = '; '.join(tax) f.write('\t'.join(map(str, [id_, tax, fraction, hits]))) f.write('\n') f.close()

To get help with taxster.uc_consensus_assignments, call:

python help(taxster.uc_consensus_assignments)

Owner

  • Name: biocore
  • Login: biocore
  • Kind: organization
  • Location: Cyberspace

Collaboratively developed bioinformatics software.

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