ADImpute
Adaptive Dropout Imputer (ADImpute)
Bioconductor version: 3.24 · Package version: 1.23.0
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
| Maintainer | Ana Carolina Leote <anacarolinaleote@gmail.com> |
| Author | Ana Carolina Leote [cre, aut] (ORCID: <https://orcid.org/0000-0003-0879-328X>) |
| License | GPL-3 + file LICENSE |
| Bug Reports | https://github.com/anacarolinaleote/ADImpute/issues |
| Downloads rank | 467 |
| Source branch | devel |
| biocViews | GeneExpression, Network, Preprocessing, Sequencing, SingleCell, Software, Transcriptomics |
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | ADImpute_1.23.0.tar.gz |
| Windows binary (x86_64) | ADImpute_1.23.0.zip |
| macOS binary (arm64) | ADImpute_1.23.0.tgz |
| macOS binary (x86_64) | ADImpute_1.23.0.tgz |
Dependencies
Depends: R (>= 4.0)
Imports: checkmate, BiocParallel, data.table, DrImpute, kernlab, MASS, Matrix, methods, rsvd, S4Vectors, SAVER, SingleCellExperiment, stats, SummarizedExperiment, utils