- recipe gsmap
gsMap (genetically informed spatial mapping of cells for complex traits)
- Homepage:
- Documentation:
- License:
MIT / MIT
- Recipe:
gsMap integrates spatial transcriptomics (ST) data with genome-wide association study (GWAS) summary statistics to map cells to human complex traits, including diseases, in a spatially resolved manner.
- package gsmap¶
- versions:
1.71.2-0,1.71.1-0,1.70-0- depends bitarray:
- depends jinja2:
- depends kaleido-core:
- depends matplotlib-base:
- depends numpy:
- depends pandas:
- depends plotly:
- depends progress:
- depends pyarrow:
- depends pyfiglet:
- depends pyranges:
- depends python:
>=3.8- depends pyyaml:
- depends scanpy:
>=1.8- depends scikit-learn:
- depends scikit-misc:
- depends scipy:
- depends seaborn-base:
- depends tqdm:
- depends zarr:
- 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 gsmap and update with:: mamba update gsmap
To create a new environment, run:
mamba create --name myenvname gsmap
with
myenvnamebeing 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/gsmap:<tag> (see `gsmap/tags`_ for valid values for ``<tag>``)
Download stats¶
Link to this page¶
Render an 
badge with the following MarkDown:
[](http://bioconda.github.io/recipes/gsmap/README.html)
