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slalom

Factorial Latent Variable Modeling of Single-Cell RNA-Seq Data

Bioconductor version: 3.24 · Package version: 1.35.0

slalom is a scalable modelling framework for single-cell RNA-seq data that uses gene set annotations to dissect single-cell transcriptome heterogeneity, thereby allowing to identify biological drivers of cell-to-cell variability and model confounding factors. The method uses Bayesian factor analysis with a latent variable model to identify active pathways (selected by the user, e.g. KEGG pathways) that explain variation in a single-cell RNA-seq dataset. This an R/C++ implementation of the f-scLVM Python package. See the publication describing the method at https://doi.org/10.1186/s13059-017-1334-8.

Installation

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

BiocManager::install("slalom")

Details

MaintainerDavis McCarthy <davis@ebi.ac.uk>
AuthorFlorian Buettner [aut], Naruemon Pratanwanich [aut], Davis McCarthy [aut, cre], John Marioni [aut], Oliver Stegle [aut]
LicenseGPL-2
Downloads rank299
Source branchdevel
biocViewsDimensionReduction, GeneExpression, ImmunoOncology, KEGG, Normalization, RNASeq, Reactome, Sequencing, SingleCell, Software, Transcriptomics, Visualization

Documentation

Download

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

Source packageslalom_1.35.0.tar.gz
Windows binary (x86_64)slalom_1.35.0.zip
Dependencies

Depends: R (>= 4.0)

Imports: Rcpp (>= 0.12.8), RcppArmadillo, BH, ggplot2, grid, GSEABase, methods, rsvd, SingleCellExperiment, SummarizedExperiment, stats

LinkingTo: Rcpp, RcppArmadillo, BH

Suggests: BiocStyle, knitr, rhdf5, rmarkdown, scater, testthat