quon-titative-biology/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.

Getting started

Package details

Bioconductor views ATACSeq BatchEffect DimensionReduction GeneExpression KEGG QualityControl SingleCell Transcriptomics
LicenseGPL-3 + file LICENSE
URL https://github.com/ucdavis/quon-titative-biology/BFA
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
quon-titative-biology/scBFA documentation built on March 24, 2020, 7:30 p.m.