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anglemania

Feature Extraction for scRNA-seq Dataset Integration

Bioconductor version: 3.23 · Package version: 1.2.0

anglemania extracts genes from multi-batch scRNA-seq experiments for downstream dataset integration. It shows improvement over the conventional usage of highly-variable genes for many integration tasks. We leverage gene-gene correlations that are stable across batches to identify biologically informative genes which are less affected by batch effects. Currently, its main use is for single-cell RNA-seq dataset integration, but it can be applied for other multi-batch downstream analyses such as NMF.

Installation

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

BiocManager::install("anglemania")

Details

MaintainerAaron Kollotzek <aaron.kollotzek@mdc-berlin.de>
AuthorAaron Kollotzek [aut, cre] (ORCID: <https://orcid.org/0009-0009-7142-4015>), Vedran Franke [aut] (ORCID: <https://orcid.org/0000-0003-3606-6792>), Artem Baranovskii [aut], Altuna Akalin [aut], SFB1588 [fnd] (Funded by the DFG – Deutsche Forschungsgemeinschaft)
LicenseGPL (>= 3)
URLhttps://github.com/BIMSBbioinfo/anglemania/
Bug Reportshttps://github.com/BIMSBbioinfo/anglemania/issues
Downloads rank141
Source branchRELEASE_3_23
biocViewsBatchEffect, FeatureExtraction, MultipleComparison, SingleCell, Software

Documentation

Download

Dependencies

Depends: R (>= 4.5.0)

Imports: bigparallelr, bigstatsr, checkmate, digest, dplyr, Matrix, pbapply, S4Vectors, SingleCellExperiment, stats, SummarizedExperiment, tidyr, withr

LinkingTo: Rcpp, rmio, bigstatsr

Suggests: batchelor, BiocStyle, bluster, knitr, magick, matrixStats, patchwork, RcppArmadillo, rmarkdown, scater, scran, Seurat, splatter, testthat (>= 3.0.0), UpSetR