Metadata-Version: 2.1
Name: Troika-TB
Version: 0.0.1
Summary: A pipeline implementing TB-Profiler for batch detection and reporting of anti-microbial resistance in TB for public health and clinical use.
Home-page: https://github.com/kristyhoran/troika
Author: Kristy Horan
Author-email: kristyhoran15@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.7
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: pytest
Requires-Dist: jinja2
Requires-Dist: biopython (>=1.70)
Requires-Dist: pandas (>=0.23.0)
Requires-Dist: numpy
Requires-Dist: svgwrite
Requires-Dist: psutil
Requires-Dist: sh
Requires-Dist: packaging
Requires-Dist: snakemake (>=5.4.0)
Requires-Dist: configargparse
Requires-Dist: xlsxwriter
Provides-Extra: tests
Requires-Dist: pytest ; extra == 'tests'
Requires-Dist: flake8 ; extra == 'tests'

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# Troika

Detection of resistance mechanisms in _Mycobacterium tuberculosis_ is dependent upon identification of SNPs that may confer decreased susceptibility to anti-mycobacterial drugs. Troika is a pipeline, which calls SNPs for both phylogenetic analysis and determination of AST. Troika leverages high quality tools, including [Snippy](https://github.com/tseemann/snippy) and [TB-profiler](https://github.com/jodyphelan/TBProfiler) and its related database to detect resistance conferring mutations from Illumina read data and filters these results for reporting for public health and clinical use in Australia.


### Motivation

There are many tools and databases available, however, for the purposes of reporting genomic AST for _M. tuberculosis_ in the context of public health and clinical use in Australia customisation is required. Rather than reinventing the wheel, Troika leverages a high quality database and a detection tool which is highly customisable. 


## Pipeline

Troika is designed for batch reporting of AST in _M. tuberculosis_ isolates generated from Illumina reads and phylogenetic analysis and clustering to identify potentially related isolates. This pipeline is in use at MDU Victoria Australia for Tuberculosis surveillance and AST reporting.

### Installation

TO COME

#### Conda (Recomended)

#### PyPi


### Running Troika

TO COME



