- recipe tracegroomer
Format and normalise tracer metabolomics given file(s), to produce the .csv files which are ready for DIMet analysis.
- Homepage:
- License:
MIT
- Recipe:
- package tracegroomer¶
- versions:
0.1.4-0
,0.1.3-0
,0.1.2-0
,0.1.1-0
- depends click:
>=8.1.7,<9.0.0
- depends matplotlib-base:
>=3.8.2,<4.0.0
- depends mypy:
>=1.8.0,<2.0.0
- depends numpy:
>=1.26.4,<2.0.0
- depends openpyxl:
>=3.1.2,<4.0.0
- depends pandas:
>=2.2.0,<3.0.0
- depends pydantic:
>=1.10.8,<2.0.0
- depends python:
>=3.10.0,<4.0.0
- depends python-dotenv:
>=1.0.1,<2.0.0
- depends pyyaml:
>=6.0.1,<7.0.0
- depends scikit-learn:
>=1.4.0,<2.0.0
- depends scipy:
>=1.12.0,<2.0.0
- depends seaborn:
>=0.13.2,<0.14.0
- depends sphinx:
>=7.2.6,<8.0.0
- requirements:
Installation
You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).
While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.
Given that you already have a conda environment in which you want to have this package, install with:
mamba install tracegroomer and update with:: mamba update tracegroomer
To create a new environment, run:
mamba create --name myenvname tracegroomer
with
myenvname
being a reasonable name for the environment (see e.g. the mamba docs for details and further options).Alternatively, use the docker container:
docker pull quay.io/biocontainers/tracegroomer:<tag> (see `tracegroomer/tags`_ for valid values for ``<tag>``)
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/tracegroomer/README.html)