- recipe m-party
Mining Protein dAtasets foR Targeted EnzYmes
- Homepage:
- Documentation:
- License:
MIT / MIT license
- Recipe:
M-PARTY takes an input FASTA file with a variable number of aminoacidic sequences and performes a search against an considerable amount of Hidden Markov Models, previously built and trained from state of the art plastic (PE - polyethylene) degrading enzymes. This process relies on the hmmsearch function from HMMER to perform the structural annotation. Output deduces about the potential presence of plastic degradring enzymes in the inputed sequences, and is composed by 3 distinct files, in order to help the user to have an easier time to read and conclude about the results.
- package m-party¶
- Versions:
0.2.2-0- Depends:
on cd-hit
on clint
on hmmer
on openpyxl
on pandas
on pyyaml
on snakemake
on t-coffee
on upimapi
- 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 m-party
to add into an existing workspace instead, run:
pixi add m-party
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 m-party
Alternatively, to install into a new environment, run:
conda create -n envname m-party
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/m-party:<tag>
(see m-party/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:
[](http://bioconda.github.io/recipes/m-party/README.html)
