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scBFA

This is the development version of scBFA; for the stable release version, see scBFA.

A dimensionality reduction tool using gene detection pattern to mitigate noisy expression profile of scRNA-seq

Bioconductor version: Development (3.18)

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.

Author: Ruoxin Li [aut, cre], Gerald Quon [aut]

Maintainer: Ruoxin Li <uskli at ucdavis.edu>

Citation (from within R, enter citation("scBFA")):

Installation

To install this package, start R (version "4.3") and enter: 

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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("scBFA")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("scBFA")
Gene Detection Analysis for scRNA-seq HTML R Script
Reference Manual PDF
NEWS Text
LICENSE Text

Details

biocViews ATACSeq, BatchEffect, DimensionReduction, GeneExpression, KEGG, QualityControl, SingleCell, Software, Transcriptomics
Version 1.15.0
In Bioconductor since BioC 3.10 (R-3.6) (4 years)
License GPL-3 + file LICENSE
Depends R (>= 3.6)
Imports SingleCellExperiment, SummarizedExperiment, Seurat, MASS, zinbwave, stats, copula, ggplot2, DESeq2, utils, grid, methods, Matrix
Linking To
Suggests knitr, rmarkdown, testthat, Rtsne
System Requirements
Enhances
URL https://github.com/ucdavis/quon-titative-biology/BFA
Bug Reports https://github.com/ucdavis/quon-titative-biology/BFA/issues
See More
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package scBFA_1.15.0.tar.gz
Windows Binary scBFA_1.15.0.zip
macOS Binary (x86_64) scBFA_1.15.0.tgz
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/scBFA
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/scBFA
Bioc Package Browser https://code.bioconductor.org/browse/scBFA/
Package Short Url https://bioconductor.org/packages/scBFA/
Package Downloads Report Download Stats