Package: slalom
Type: Package
Title: Factorial Latent Variable Modeling of Single-Cell RNA-Seq Data
Version: 1.25.0
Date: 2021-11-21
Authors@R: c(person("Florian", "Buettner", role=c("aut"),
        email=""), person("Naruemon",
        "Pratanwanich", role=c("aut"), email=""),
        person("Davis", "McCarthy", role=c("aut", "cre"), email=""),
        person("John", "Marioni", role = c("aut"), email=""),
        person("Oliver", "Stegle", role = c("aut"), email=""))
Description: 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 
Depends: R (>= 4.0)
Imports: Rcpp (>= 0.12.8), RcppArmadillo, BH, ggplot2, grid, GSEABase,
        methods, rsvd, SingleCellExperiment, SummarizedExperiment, stats
Suggests: BiocStyle, knitr, rhdf5, rmarkdown, scater, testthat
LinkingTo: Rcpp, RcppArmadillo, BH
License: GPL-2
VignetteBuilder: knitr
LazyData: true
Encoding: UTF-8
biocViews: ImmunoOncology, SingleCell, RNASeq, Normalization,
        Visualization, DimensionReduction, Transcriptomics,
        GeneExpression, Sequencing, Software, Reactome, KEGG
RoxygenNote: 6.0.1