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

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.

Package details

AuthorRuoxin Li [aut, cre], Gerald Quon [aut]
Bioconductor views ATACSeq BatchEffect DimensionReduction GeneExpression KEGG QualityControl SingleCell Transcriptomics
MaintainerRuoxin Li <uskli@ucdavis.edu>
LicenseGPL-3 + file LICENSE
Version1.4.0
URL https://github.com/ucdavis/quon-titative-biology/BFA
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("scBFA")

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scBFA documentation built on Nov. 8, 2020, 5:24 p.m.