recipe bioconductor-adimpute

Adaptive Dropout Imputer (ADImpute)

Homepage:

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

License:

GPL-3 + file LICENSE

Recipe:

/bioconductor-adimpute/meta.yaml

Single-cell RNA sequencing (scRNA-seq) methods are typically unable to quantify the expression levels of all genes in a cell, creating a need for the computational prediction of missing values (‘dropout imputation’). Most existing dropout imputation methods are limited in the sense that they exclusively use the scRNA-seq dataset at hand and do not exploit external gene-gene relationship information. Here we propose two novel methods: a gene regulatory network-based approach using gene-gene relationships learnt from external data and a baseline approach corresponding to a sample-wide average. ADImpute can implement these novel methods and also combine them with existing imputation methods (currently supported: DrImpute, SAVER). ADImpute can learn the best performing method per gene and combine the results from different methods into an ensemble.

package bioconductor-adimpute

versions:

1.12.0-0,  1.10.0-0,  1.8.0-0,  1.4.0-0,  1.2.0-0,  1.0.0-1,  1.0.0-0

depends bioconductor-biocparallel:

>=1.36.0,<1.37.0

depends bioconductor-s4vectors:

>=0.40.0,<0.41.0

depends bioconductor-singlecellexperiment:

>=1.24.0,<1.25.0

depends bioconductor-summarizedexperiment:

>=1.32.0,<1.33.0

depends r-base:

>=4.3,<4.4.0a0

depends r-checkmate:

depends r-data.table:

depends r-drimpute:

depends r-kernlab:

depends r-mass:

depends r-matrix:

depends r-rsvd:

depends r-saver:

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-adimpute

and update with::

   mamba update bioconductor-adimpute

To create a new environment, run:

mamba create --name myenvname bioconductor-adimpute

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-adimpute:<tag>

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

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Link to this page

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