recipe bioconductor-screclassify

scReClassify: post hoc cell type classification of single-cell RNA-seq data

Homepage:

https://bioconductor.org/packages/3.20/bioc/html/scReClassify.html

License:

GPL-3 + file LICENSE

Recipe:

/bioconductor-screclassify/meta.yaml

A post hoc cell type classification tool to fine-tune cell type annotations generated by any cell type classification procedure with semi-supervised learning algorithm AdaSampling technique. The current version of scReClassify supports Support Vector Machine and Random Forest as a base classifier.

package bioconductor-screclassify

versions:

1.12.0-0,  1.8.0-0,  1.6.0-0,  1.4.0-0,  1.0.0-0

depends bioconductor-singlecellexperiment:

>=1.28.0,<1.29.0

depends bioconductor-summarizedexperiment:

>=1.36.0,<1.37.0

depends r-base:

>=4.4,<4.5.0a0

depends r-e1071:

depends r-randomforest:

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 bioconductor-screclassify

and update with::

   mamba update bioconductor-screclassify

To create a new environment, run:

mamba create --name myenvname bioconductor-screclassify

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/bioconductor-screclassify:<tag>

(see `bioconductor-screclassify/tags`_ for valid values for ``<tag>``)

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Link to this page

Render an badge with the following MarkDown:

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