recipe ovrlpy

A python tool to investigate cell overlaps in imaging-based spatial transcriptomics data.

Homepage:

https://github.com/HiDiHlabs/ovrl.py

Documentation:

https://ovrlpy.readthedocs.io/

License:

MIT / MIT

Recipe:

/ovrlpy/meta.yaml

package ovrlpy

versions:

0.2.1-0

depends matplotlib-base:

>=3.8,<4.dev0

depends matplotlib-scalebar:

depends numpy:

>=1.25,<2.dev0

depends pandas:

>=2.0,<3.dev0

depends python:

>=3.11,<3.14

depends scikit-image:

>=0.18

depends scikit-learn:

>=1.1,<2.dev0

depends scipy:

>=1.11,<2.dev0

depends tqdm:

>=4.65,<5.dev0

depends umap-learn:

>=0.5,<1.dev0

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 ovrlpy

and update with::

   mamba update ovrlpy

To create a new environment, run:

mamba create --name myenvname ovrlpy

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/ovrlpy:<tag>

(see `ovrlpy/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/ovrlpy/README.html)