recipe fastppm

Fast Perfect Phylogeny Mixture Regression using Tree-Structured Dual Dynamic Programming

Homepage:

https://github.com/elkebir-group/fastppm

License:

MIT

Recipe:

/fastppm/meta.yaml

`fastppm` (fast perfect phylogeny mixtures) is a C++/Python library for fast estimation of unknown frequency matrices, given variant and total read counts over an n-clonal tree.

package fastppm

(downloads) docker_fastppm

versions:

1.1.1-0,  1.1.0-0

depends libgcc:

>=13

depends libstdcxx:

>=13

depends python:

>=3.10,<3.11.0a0

depends python_abi:

3.10.* *_cp310

requirements:

additional platforms:
linux-aarch64,  osx-arm64

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 fastppm

and update with::

   mamba update fastppm

To create a new environment, run:

mamba create --name myenvname fastppm

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/fastppm:<tag>

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

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Link to this page

Render an install-with-bioconda 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/fastppm/README.html)