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scBFA

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

Bioconductor version: 3.23 · Package version: 1.26.0

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

MaintainerRuoxin Li <uskli@ucdavis.edu>
AuthorRuoxin Li [aut, cre], Gerald Quon [aut]
LicenseGPL-3 + file LICENSE
URLhttps://github.com/ucdavis/quon-titative-biology/BFA
Bug Reportshttps://github.com/ucdavis/quon-titative-biology/BFA/issues
Downloads rank274
Source branchRELEASE_3_23
biocViewsATACSeq, BatchEffect, DimensionReduction, GeneExpression, KEGG, QualityControl, SingleCell, Software, Transcriptomics

Documentation

Download

Dependencies

Depends: R (>= 3.6)

Imports: SingleCellExperiment, SummarizedExperiment, Seurat, MASS, zinbwave, stats, copula, ggplot2, DESeq2, utils, grid, methods, Matrix

Suggests: knitr, rmarkdown, testthat, Rtsne