recipe cellrank

CellRank for directed single-cell fate mapping

Homepage

https://github.com/theislab/cellrank

Documentation

https://cellrank.org

License

BSD

Recipe

/cellrank/meta.yaml

CellRank is a toolkit to uncover cellular dynamics based on Markov state modeling of single-cell data. It contains two main modules: kernels compute cell-cell transition probabilities and estimators generate hypothesis based on these.

package cellrank

Versions

1.3.1-0,  1.2.0-0,  1.1.0-0,  1.0.0-0,  1.0.0rc12-0,  1.0.0rc10-0,  1.0.0rc9-0,  1.0.0rc8-0,  1.0.0rc7-0, 

1.3.1-0,  1.2.0-0,  1.1.0-0,  1.0.0-0,  1.0.0rc12-0,  1.0.0rc10-0,  1.0.0rc9-0,  1.0.0rc8-0,  1.0.0rc7-0,  1.0.0rc6-0,  1.0.0rc4-0,  1.0.0rc2-0,  1.0.0rc0-0,  1.0.0b3-0

Depends

• anndata >=0.7.2

• docrep >=0.3.0

• future_fstrings

• ipywidgets >=7.5.1

• joblib >=0.13.1

• matplotlib-base >=3.3.0

• networkx >=2.2

• numba >=0.51.0

• numpy >=1.2.0

• pandas >=1.2.0

• pygam >=0.8.0

• pygpcca >=1.0.2

• python >=3.6

• scanpy >=1.6.0

• scikit-learn >=0.21.3

• scipy >=1.2.0

• scvelo >=0.2.2

• seaborn >=0.10.0

• setuptools >=41.0.1

• typing_extensions

• tzlocal >=1.5.1

• wrapt >=1.12.1

Required By

• cellrank-krylov

Installation

With an activated Bioconda channel (see 2. Set up channels), install with:

conda install cellrank

and update with:

conda update cellrank

or use the docker container:

docker pull quay.io/biocontainers/cellrank:<tag>

(see cellrank/tags for valid values for <tag>)

package cellrank-krylov

Versions

1.3.1-0,  1.2.0-0,  1.1.0-0,  1.0.0-0,  1.0.0rc12-0,  1.0.0rc10-0,  1.0.0rc9-0,  1.0.0rc8-0,  1.0.0rc7-0, 

1.3.1-0,  1.2.0-0,  1.1.0-0,  1.0.0-0,  1.0.0rc12-0,  1.0.0rc10-0,  1.0.0rc9-0,  1.0.0rc8-0,  1.0.0rc7-0,  1.0.0rc6-0,  1.0.0rc4-0,  1.0.0rc2-0,  1.0.0rc0-0

Depends

• cellrank 1.3.1 pyhdfd78af_0

• mpi4py >=3.0.3

• openmpi >=3.0.3

• petsc >=3.13.0

• petsc4py >=3.13.0

• python >=3.6

• slepc >=3.13.0

• slepc4py >=3.13.0

Required By

Installation

With an activated Bioconda channel (see 2. Set up channels), install with:

conda install cellrank-krylov

and update with:

conda update cellrank-krylov

or use the docker container:

docker pull quay.io/biocontainers/cellrank-krylov:<tag>

(see cellrank-krylov/tags for valid values for <tag>)

Link to this page

Render an badge with the following MarkDown:

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