Package Recipe 'geno2phenotb'

recipe geno2phenotb

Prediction of Mycobacterium tuberculosis drug resistance from WGS data.

Homepage:: https://github.com/msmdev/geno2phenoTB
Documentation:: https://geno2phenotb.readthedocs.io/en/latest
License:: LGPL / LGPL-3.0-only
Recipe:: /geno2phenotb/meta.yaml

geno2phenoTB is a machine learning based tool to predict resistance of Mycobacterium tuberculosis against antibiotics using whole-genome sequencing data.

package geno2phenotb¶

Versions:

1.0.1-1, 1.0.1-0, 1.0.0-0

Depends:

on bwa
on gatk 3.8.*
on imbalanced-learn 0.8.1.*
on importlib_metadata
on joblib 1.2.*
on mtbseq
on numpy 1.21.5.*
on packaging 21.*
on pandas 0.25.3.*
on perl-base 2.23.*
on python 3.8.17.*
on requests 2.*
on samtools 1.6.*
on scikit-learn 0.24.2.*
on scipy 1.7.3.*
on setuptools
on tqdm 4.*
on wheel 0.37.*

Additional platforms:

Installation¶

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi¶

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install geno2phenotb

to add into an existing workspace instead, run:

pixi add geno2phenotb

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda¶

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install geno2phenotb

Alternatively, to install into a new environment, run:

conda create -n envname geno2phenotb

with envname being the name of the desired environment.

Container¶

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

docker pull quay.io/biocontainers/geno2phenotb:<tag>

(see geno2phenotb/tags for valid values for <tag>).

Integrated deployment¶

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

Download stats¶

Link to this page¶

Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/geno2phenotb/README.html)