scBFA
A dimensionality reduction tool using gene detection pattern to mitigate noisy expression profile of scRNA-seq
Bioconductor version: 3.24 · Package version: 1.27.0
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.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("scBFA") Details
| Maintainer | Ruoxin Li <uskli@ucdavis.edu> |
| Author | Ruoxin Li [aut, cre], Gerald Quon [aut] |
| License | GPL-3 + file LICENSE |
| URL | https://github.com/ucdavis/quon-titative-biology/BFA |
| Bug Reports | https://github.com/ucdavis/quon-titative-biology/BFA/issues |
| Downloads rank | 433 |
| Source branch | devel |
| biocViews | ATACSeq, BatchEffect, DimensionReduction, GeneExpression, KEGG, QualityControl, SingleCell, Software, Transcriptomics |
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | scBFA_1.27.0.tar.gz |
| Windows binary (x86_64) | scBFA_1.27.0.zip |
| macOS binary (arm64) | scBFA_1.27.0.tgz |
| macOS binary (x86_64) | scBFA_1.27.0.tgz |