recipe bioconductor-scannotatr

Pretrained learning models for cell type prediction on single cell RNA-sequencing data

Homepage:

https://bioconductor.org/packages/3.18/bioc/html/scAnnotatR.html

License:

MIT + file LICENSE

Recipe:

/bioconductor-scannotatr/meta.yaml

The package comprises a set of pretrained machine learning models to predict basic immune cell types. This enables all users to quickly get a first annotation of the cell types present in their dataset without requiring prior knowledge. scAnnotatR also allows users to train their own models to predict new cell types based on specific research needs.

package bioconductor-scannotatr

versions:

1.8.0-0,  1.6.0-0,  1.4.0-0,  1.0.0-0

depends bioconductor-annotationhub:

>=3.10.0,<3.11.0

depends bioconductor-singlecellexperiment:

>=1.24.0,<1.25.0

depends bioconductor-summarizedexperiment:

>=1.32.0,<1.33.0

depends r-ape:

depends r-base:

>=4.3,<4.4.0a0

depends r-caret:

depends r-data.tree:

depends r-dplyr:

depends r-e1071:

depends r-ggplot2:

depends r-kernlab:

depends r-proc:

depends r-rocr:

depends r-seurat:

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 bioconductor-scannotatr

and update with::

   mamba update bioconductor-scannotatr

To create a new environment, run:

mamba create --name myenvname bioconductor-scannotatr

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-scannotatr:<tag>

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

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Link to this page

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