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DESCRIPTION
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Package: scBFA
Version: 1.1.0
Date: 2019-03-09
Title: A dimensionality reduction tool using gene detection pattern to mitigate noisy expression profile of scRNA-seq
Description: 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.
Authors@R:
c(person(given = "Ruoxin",
family = "Li",
role = c("aut", "cre"),
email = "uskli@ucdavis.edu"),
person(given = "Gerald",
family = "Quon",
role = c("aut"),
email = "gquon@ucdavis.edu"))
URL: https://github.com/ucdavis/quon-titative-biology/BFA
BugReports: https://github.com/ucdavis/quon-titative-biology/BFA/issues
biocViews: SingleCell, Transcriptomics, DimensionReduction,GeneExpression, ATACSeq, BatchEffect, KEGG, QualityControl
Depends: R (>= 3.6)
Imports: SingleCellExperiment,
SummarizedExperiment,
Seurat,
MASS,
zinbwave,
stats,
copula,
ggplot2,
DESeq2,
utils,
grid,
methods,
Matrix
Suggests:
knitr,
rmarkdown,
testthat,
Rtsne
VignetteBuilder: knitr
RoxygenNote: 7.0.2
License: GPL-3 + file LICENSE
LazyData: true
Encoding: UTF-8