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ADImpute

Adaptive Dropout Imputer (ADImpute)

Bioconductor version: 3.23 · Package version: 1.22.0

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.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("ADImpute")

Details

MaintainerAna Carolina Leote <anacarolinaleote@gmail.com>
AuthorAna Carolina Leote [cre, aut] (ORCID: <https://orcid.org/0000-0003-0879-328X>)
LicenseGPL-3 + file LICENSE
Bug Reportshttps://github.com/anacarolinaleote/ADImpute/issues
Downloads rank299
Source branchRELEASE_3_23
biocViewsGeneExpression, Network, Preprocessing, Sequencing, SingleCell, Software, Transcriptomics

Documentation

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Dependencies

Depends: R (>= 4.0)

Imports: checkmate, BiocParallel, data.table, DrImpute, kernlab, MASS, Matrix, methods, rsvd, S4Vectors, SAVER, SingleCellExperiment, stats, SummarizedExperiment, utils

Suggests: BiocStyle, knitr, rmarkdown, testthat