scBFA
This package is for version 3.18 of Bioconductor; for the stable, up-to-date release version, see scBFA.
A dimensionality reduction tool using gene detection pattern to mitigate noisy expression profile of scRNA-seq
Bioconductor version: 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("scBFA")):
Installation
To install this package, start R (version "4.3") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
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 | ||
| NEWS | Text | |
| LICENSE | Text |
Details
| biocViews | ATACSeq, BatchEffect, DimensionReduction, GeneExpression, KEGG, QualityControl, SingleCell, Software, Transcriptomics |
| Version | 1.16.0 |
| In Bioconductor since | BioC 3.10 (R-3.6) (4.5 years) |
| License | GPL-3 + file LICENSE |
| Depends | R (>= 3.6) |
| Imports | SingleCellExperiment, SummarizedExperiment, Seurat, MASS, zinbwave, stats, copula, ggplot2, DESeq2, utils, grid, methods, Matrix |
| System Requirements | |
| URL | https://github.com/ucdavis/quon-titative-biology/BFA |
| Bug Reports | https://github.com/ucdavis/quon-titative-biology/BFA/issues |
See More
| Suggests | knitr, rmarkdown, testthat, Rtsne |
| Linking To | |
| Enhances | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | scBFA_1.16.0.tar.gz |
| Windows Binary | scBFA_1.16.0.zip |
| macOS Binary (x86_64) | scBFA_1.16.0.tgz |
| macOS Binary (arm64) | scBFA_1.16.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/scBFA |
| Source Repository (Developer Access) | git clone [email protected]:packages/scBFA |
| Bioc Package Browser | https://code.bioconductor.org/browse/scBFA/ |
| Package Short Url | https://bioconductor.org/packages/scBFA/ |
| Package Downloads Report | Download Stats |