- recipe pyclone
PyClone: A probabilistic model for inferring clonal population structure from deep NGS sequencing.
- Homepage:
- License:
custom
- Recipe:
- Links:
doi: 10.1038/nmeth.2883
PyClone is statistical model and software tool designed to infer the prevalence of point mutations in heterogeneous cancer samples. The input data for PyClone consists of a set read counts from a deep sequencing experiment, the copy number of the genomic region containing the mutation and an estimate of tumour content.
- package pyclone¶
- Versions:
0.13.1-0- Depends:
on matplotlib-base
on numba
on numpy
on pandas
on pydp
>=0.2.4on python
<3on pyyaml
on scipy
on seaborn
- 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 pyclone
to add into an existing workspace instead, run:
pixi add pyclone
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 pyclone
Alternatively, to install into a new environment, run:
conda create -n envname pyclone
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/pyclone:<tag>
(see pyclone/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/pyclone/README.html)
