https://github.com/bacpop/amr_reactapp

AMR prediction from S. pneumoniae assemblies in the browser
https://github.com/bacpop/amr_reactapp

amr genomics pneumococcus wasm

Last synced: 3 months ago
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AMR prediction from S. pneumoniae assemblies in the browser

• Host: GitHub
• URL: https://github.com/bacpop/amr_reactapp
• Owner: bacpop
• License: mit
• Created: 2021-12-01T11:11:55.000Z (over 4 years ago)
• Default Branch: main
• Last Pushed: 2022-02-03T14:53:02.000Z (over 4 years ago)
• Last Synced: 2025-09-09T13:39:32.770Z (11 months ago)
• Topics: amr, genomics, pneumococcus, wasm
• Language: JavaScript
• Homepage: https://amr.poppunk.net
• Size: 23.3 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
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# AMIMA 

## AMR prediction tool for *S.pneumoniae*

## Overview

https://amr.poppunk.net/ is a tool to predict antimicrobial resistance in __*S.pneumoniae*__. It applies linear models on genetic sequence data to return a probability of resistance to the five antibiotics

- Penicillin

- Chloramphenicol

- Erythromycin

- Tetracycline

- Trimethoprim/Sulfamethoxazole

### Intended use

Files in FASTA format can be uploaded via a drag and drop area. Submission of multiple files at a time is possible.

Files should cover the whole genome to ensure the models can be applied correctly.

Results are displayed in a table, giving the probability of resistance to the respective antibiotic.

The table can be downloaded in CSV format.

Don't use this tool for clinical practice.

### Methods

The models applied are logistic [ElasticNet](https://en.wikipedia.org/wiki/Elastic_net_regularization) models trained on data from the USA and South Africa from the [GPS](https://www.pneumogen.net/gps/) database.

Input features that are generated from the FASTA files are [unitigs](https://pubmed.ncbi.nlm.nih.gov/30419019/#&gid=article-figures&pid=fig-1-uid-0), which are nucleotide sequences of variable length. 

The models have been tested on independent datasets from Massachusetts and Maela (Thailand). The predicted binary resistance status (at a probability threshold of 0.5) was tested against the true recorded phenotype and [Balanced Accuracies](https://statisticaloddsandends.wordpress.com/2020/01/23/what-is-balanced-accuracy/) were calculated:

|Antibiotic|Massachusetts|Maela|

|----------|-------------|-----|

|Penicillin|0.933|0.836|

|Chlorampehnicol| |0.819|

|Erythromycin|0.959|0.961|

|Tetracycline|0.953|0.940|

|Trimethoprim/Sulfamethoxazole|0.954|0.837|

The website was build using React.js. The backend code can be found [here](https://github.com/bacpop/AMR_prediction).

### Contributors

This tool was developed by [Marie Gronemeyer](https://github.com/muppi1993) and [John Lees](https://github.com/johnlees).