Skip to content
Fowler Lab
Fowler Lab

Predicting antibiotic resistance de novo

  • News
  • Research
    • Overview
    • Manifesto
    • Software
    • Reproducibility
    • Publications
  • Members
  • Teaching
  • Contact
    • PhDs
  • Wiki
Fowler Lab
Fowler Lab

Predicting antibiotic resistance de novo

New software: gemucator

Philip Fowler, 4th September 20184th September 2018

Short for “Genbank Mutation Locator”. A simple Python3 package that if you pass it a mutation it will give you the location in the specified genbank file.

> gemucator-run.py --mutation rpoB_S450L
rpoB_S450L:
761153 t
761154 c
761155 g

(H37rV.gbk for M. tuberculosis is loaded by default). Or you can go the other way

> gemucator-run.py --location 761153
rpoB_S450

It has no unit testing, but checks that the mutation is consistent with the genbank file which means you can check if your genetic catalogue is correct.

> gemucator-run.py --mutation rpoB_K450L
Traceback (most recent call last):
File "/Users/fowler/Library/Python/3.5/bin/gemucator-run.py", line 6, in <module>
exec(compile(open(__file__).read(), __file__, 'exec'))
File "/Users/fowler/packages/gemucator/bin/gemucator-run.py", line 14, in <module>
(locations,bases)=tb_reference_genome.locate_mutation(options.mutation)
File "/Users/fowler/packages/gemucator/gemucator/core.py", line 127, in locate_mutation
assert before==bases.translate(), "wildtype amino acid specified in mutation does not match the "+self.genbank_file+" genbank file"
AssertionError: wildtype amino acid specified in mutation does not match the config/H37rV.gbk genbank file

 

Share this:

  • Click to share on X (Opens in new window) X
  • Click to share on Bluesky (Opens in new window) Bluesky
  • Click to email a link to a friend (Opens in new window) Email
  • Click to share on LinkedIn (Opens in new window) LinkedIn
  • Click to share on Mastodon (Opens in new window) Mastodon

Related

antimicrobial resistance computing tuberculosis

Post navigation

Previous post
Next post

Related Posts

antimicrobial resistance

New preprint: compensatory mutations are associated with increased growth in resistant samples of M. tuberculosis.

22nd June 20238th December 2023

In this preprint, Viki Brunner shows how, using the large CRyPTIC dataset, she can recapitulate…

Share this:

  • Click to share on X (Opens in new window) X
  • Click to share on Bluesky (Opens in new window) Bluesky
  • Click to email a link to a friend (Opens in new window) Email
  • Click to share on LinkedIn (Opens in new window) LinkedIn
  • Click to share on Mastodon (Opens in new window) Mastodon
Read More
citizen science

Automated detection of bacterial growth on 96-well plates (AMyGDA)

11th December 20175th August 2018

I am involved in an international collaboration, the Comprehensive Resistance Prediction for Tuberculosis: an International Consortium…

Share this:

  • Click to share on X (Opens in new window) X
  • Click to share on Bluesky (Opens in new window) Bluesky
  • Click to email a link to a friend (Opens in new window) Email
  • Click to share on LinkedIn (Opens in new window) LinkedIn
  • Click to share on Mastodon (Opens in new window) Mastodon
Read More

Viki Brunner wins poster prize

23rd November 202223rd November 2022

The whole group attended the first INEOS Oxford Institute meeting on Multidisciplinary Approaches to AMR…

Share this:

  • Click to share on X (Opens in new window) X
  • Click to share on Bluesky (Opens in new window) Bluesky
  • Click to email a link to a friend (Opens in new window) Email
  • Click to share on LinkedIn (Opens in new window) LinkedIn
  • Click to share on Mastodon (Opens in new window) Mastodon
Read More

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Privacy & Cookies: This site uses cookies. By continuing to use this website, you agree to their use.

To find out more, including how to control cookies, see here: Cookie Policy
    ©2025 Fowler Lab | WordPress Theme by SuperbThemes