Package: scBFA
Version: 1.25.0
Date: 2019-03-09
Title: A dimensionality reduction tool using gene detection pattern to mitigate noisy expression profile of scRNA-seq
Description: This package is designed to model gene detection pattern of scRNA-seq through a binary factor analysis model. This model allows user to pass into a cell level covariate matrix X and gene level covariate matrix Q to account for nuisance variance(e.g batch effect), and it will output a low dimensional embedding matrix for downstream analysis.
Authors@R:
   c(person(given = "Ruoxin",
            family = "Li",
            role = c("aut", "cre"),
            email = "uskli@ucdavis.edu"),
     person(given = "Gerald",
            family = "Quon",
            role = c("aut"),
            email = "gquon@ucdavis.edu"))
URL: https://github.com/ucdavis/quon-titative-biology/BFA
BugReports: https://github.com/ucdavis/quon-titative-biology/BFA/issues
biocViews: SingleCell, Transcriptomics, DimensionReduction,GeneExpression, ATACSeq, BatchEffect, KEGG, QualityControl
Depends: R (>= 3.6)
Imports: SingleCellExperiment,
        SummarizedExperiment,
        Seurat,
	    MASS,
	    zinbwave,
        stats,
        copula,
        ggplot2,
        DESeq2,
        utils,
        grid,
        methods,
	Matrix
Suggests:
    knitr,
    rmarkdown,
    testthat,
    Rtsne
VignetteBuilder: knitr
RoxygenNote: 7.0.2
License: GPL-3 + file LICENSE
LazyData: true
Encoding: UTF-8
git_url: https://git.bioconductor.org/packages/scBFA
git_branch: devel
git_last_commit: 128392e
git_last_commit_date: 2025-10-29
Repository: Bioconductor 3.23
