recipe sprinter

Single-cell Proliferation Rate Inference in Non-homogeneous Tumours through Evolutionary Routes (SPRINTER)

Homepage:

https://github.com/zaccaria-lab/SPRINTER

Documentation:

https://github.com/zaccaria-lab/SPRINTER/blob/v1.0.0/README.md

License:

OTHER / ACADEMIC NON-COMMERCIAL SOFTWARE LICENSE

Recipe:

/sprinter/meta.yaml

SPRINTER is an algorithm that uses single-cell whole-genome DNA sequencing data to enable the accurate identification of actively replicating cells in both the S and G2 phases of the cell cycle and their assignment to distinct tumour clones, thus providing a proxy to estimate clone-specific proliferation rates.

package sprinter

versions:

1.0.0-0

depends hmmlearn:

>=0.2.7

depends matplotlib-base:

>=3.5.0

depends numba:

>=0.55.0

depends numpy:

>=1.22.0,<=1.26.4

depends pandas:

>=1.3.0

depends pybedtools:

>=0.8.0

depends python:

>=3.9

depends scikit-learn:

>=1.0.0,<2.0.0

depends scipy:

>=1.7.0,<2.0.0

depends seaborn:

>=0.11.0

depends statsmodels:

>=0.13.0

requirements:

additional platforms:

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 sprinter

and update with::

   mamba update sprinter

To create a new environment, run:

mamba create --name myenvname sprinter

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/sprinter:<tag>

(see `sprinter/tags`_ for valid values for ``<tag>``)

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