scBFA

DOI: 10.18129/B9.bioc.scBFA    

This is the development version of scBFA; to use it, please install the devel version of Bioconductor.

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

Bioconductor version: Development (3.10)

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 "3.6") and enter:

if (!requireNamespace("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")

 

HTML R Script Gene Detection Analysis for scRNA-seq
PDF   Reference Manual
Text   NEWS

Details

biocViews ATACSeq, BatchEffect, DimensionReduction, GeneExpression, KEGG, QualityControl, SingleCell, Software, Transcriptomics
Version 0.99.918
In Bioconductor since BioC 3.10 (R-3.6)
License GPL-3
Depends R (>= 3.6)
Imports SingleCellExperiment, SummarizedExperiment, Seurat, MASS, zinbwave, stats, copula, ggplot2, DESeq2, utils, grid, methods
LinkingTo
Suggests knitr, rmarkdown, testthat, Rtsne
SystemRequirements
Enhances
URL https://github.com/ucdavis/quon-titative-biology/BFA
BugReports https://github.com/ucdavis/quon-titative-biology/BFA/issues
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_0.99.918.tar.gz
Windows Binary scBFA_0.99.918.zip
Mac OS X 10.11 (El Capitan) scBFA_0.99.918.tgz
Source Repository git clone https://git.bioconductor.org/packages/scBFA
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/scBFA
Package Short Url https://bioconductor.org/packages/scBFA/
Package Downloads Report Download Stats

Documentation »

Bioconductor

R / CRAN packages and documentation

Support »

Please read the posting guide. Post questions about Bioconductor to one of the following locations: