:orphan: .. only available via index, not via toctree .. title:: Package Recipe 'bioconductor-adimpute' .. highlight: bash bioconductor-adimpute ===================== .. conda:recipe:: bioconductor-adimpute :replaces_section_title: :noindex: 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. .. conda:package:: bioconductor-adimpute |downloads_bioconductor-adimpute| |docker_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: .. rubric:: Installation You need a conda-compatible package manager (currently either `micromamba `_, `mamba `_, or `conda `_) and the Bioconda channel already activated (see :ref:`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: (see `bioconductor-adimpute/tags`_ for valid values for ````) .. |downloads_bioconductor-adimpute| image:: https://img.shields.io/conda/dn/bioconda/bioconductor-adimpute.svg?style=flat :target: https://anaconda.org/bioconda/bioconductor-adimpute :alt: (downloads) .. |docker_bioconductor-adimpute| image:: https://quay.io/repository/biocontainers/bioconductor-adimpute/status :target: https://quay.io/repository/biocontainers/bioconductor-adimpute .. _`bioconductor-adimpute/tags`: https://quay.io/repository/biocontainers/bioconductor-adimpute?tab=tags .. raw:: html Download stats ----------------- .. raw:: html :file: ../../templates/package_dashboard.html Link to this page ----------------- Render an |install-with-bioconda| badge with the following MarkDown:: [![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-adimpute/README.html) .. |install-with-bioconda| image:: https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat :target: http://bioconda.github.io/recipes/bioconductor-adimpute/README.html