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demuxSNP

scRNAseq demultiplexing using cell hashing and SNPs

Bioconductor version: 3.23 · Package version: 1.10.0

This package assists in demultiplexing scRNAseq data using both cell hashing and SNPs data. The SNP profile of each group os learned using high confidence assignments from the cell hashing data. Cells which cannot be assigned with high confidence from the cell hashing data are assigned to their most similar group based on their SNPs. We also provide some helper function to optimise SNP selection, create training data and merge SNP data into the SingleCellExperiment framework.

Installation

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

BiocManager::install("demuxSNP")

Details

MaintainerMichael Lynch <michael.lynch@ul.ie>
AuthorMichael Lynch [aut, cre] (ORCID: <https://orcid.org/0000-0001-9535-6461>), Aedin Culhane [aut] (ORCID: <https://orcid.org/0000-0002-1395-9734>)
LicenseGPL-3
URLhttps://github.com/michaelplynch/demuxSNP
Bug Reportshttps://github.com/michaelplynch/demuxSNP/issues
Downloads rank400
Source branchRELEASE_3_23
biocViewsClassification, SingleCell, Software

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packagedemuxSNP_1.10.0.tar.gz
Windows binary (x86_64)demuxSNP_1.10.0.zip
macOS binary (arm64)demuxSNP_1.10.0.tgz
macOS binary (x86_64)demuxSNP_1.10.0.tgz
Dependencies

Depends: R (>= 4.3.0), SingleCellExperiment, VariantAnnotation, ensembldb

Imports: MatrixGenerics, BiocGenerics, class, Seqinfo, IRanges, Matrix, SummarizedExperiment, demuxmix, methods, KernelKnn, dplyr

Suggests: knitr, rmarkdown, ComplexHeatmap, viridisLite, ggpubr, dittoSeq, EnsDb.Hsapiens.v86, BiocStyle, RefManageR, testthat (>= 3.0.0), Seurat