- recipe starfish
Standardized analysis pipeline for image-based transcriptomics.
- Homepage:
- Documentation:
- License:
MIT / MIT
- Recipe:
- package starfish¶
-
- Versions:
0.4.0-0,0.3.4-0,0.3.3-0,0.3.2-0,0.3.1-0,0.3.0-0,0.2.2-0,0.2.1-0,0.2.0-0,0.4.0-0,0.3.4-0,0.3.3-0,0.3.2-0,0.3.1-0,0.3.0-0,0.2.2-0,0.2.1-0,0.2.0-0,0.1.10-0,0.1.9-0,0.1.8-0,0.1.7-0,0.1.6-0,0.1.5-0,0.1.4-0,0.1.3-0,0.1.2-0,0.1.1-0,0.1.0-0,0.0.31-0,0.0.30-0,0.0.29-0,0.0.27-0,0.0.26-2,0.0.25-2,0.0.23-2,0.0.21-2,0.0.20-2,0.0.19-2,0.0.18-2,0.0.17-2,0.0.16-2,0.0.14-2,0.0.14-1,0.0.14-0- Depends:
on click
on docutils
<0.20on h5py
on jsonschema
<4.18on matplotlib-base
<3.8on mistune
0.8.4on numpy
<2on python
>=3.9,<3.13on read-roi
on referencing
on regional
on scikit-image
>0.22on scikit-learn
on seaborn-base
on semantic_version
on showit
on slicedimage
on sympy
on tqdm
on trackpy
on validators
on xarray
<2023.09
- 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 starfish
to add into an existing workspace instead, run:
pixi add starfish
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 starfish
Alternatively, to install into a new environment, run:
conda create -n envname starfish
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/starfish:<tag>
(see starfish/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/starfish/README.html)