recipe starfish

Standardized analysis pipeline for image-based transcriptomics.

Homepage:

https://github.com/spacetx/starfish

Documentation:

https://spacetx-starfish.readthedocs.io/en/latest

License:

MIT / MIT

Recipe:

/starfish/meta.yaml

package starfish

(downloads) docker_starfish

versions:
0.3.0-00.2.2-00.2.1-00.2.0-00.1.10-00.1.9-00.1.8-00.1.7-00.1.6-0

0.3.0-00.2.2-00.2.1-00.2.0-00.1.10-00.1.9-00.1.8-00.1.7-00.1.6-00.1.5-00.1.4-00.1.3-00.1.2-00.1.1-00.1.0-00.0.31-00.0.30-00.0.29-00.0.27-00.0.26-20.0.25-20.0.23-20.0.21-20.0.20-20.0.19-20.0.18-20.0.17-20.0.16-20.0.14-20.0.14-10.0.14-0

depends click:

depends docutils:

<0.21

depends h5py:

depends jsonschema:

<4.18

depends matplotlib-base:

<3.8

depends mistune:

0.8.4

depends numpy:

<1.25

depends python:

>=3.9,<3.12

depends read-roi:

depends regional:

depends scikit-image:

0.21

depends scikit-learn:

depends seaborn-base:

depends semantic_version:

depends showit:

depends slicedimage:

depends sympy:

depends tqdm:

depends trackpy:

depends validators:

depends xarray:

<2023.09

requirements:

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 starfish

and update with::

   mamba update starfish

To create a new environment, run:

mamba create --name myenvname starfish

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/starfish:<tag>

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

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