recipe bioconductor-adimpute

Adaptive Dropout Imputer (ADImpute)



GPL-3 + file LICENSE



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

(downloads) docker_bioconductor-adimpute



Required By:


With an activated Bioconda channel (see set-up-channels), install with:

conda install bioconductor-adimpute

and update with:

conda update bioconductor-adimpute

or use the docker container:

docker pull<tag>

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

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