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MAST

Model-based Analysis of Single Cell Transcriptomics


Bioconductor version: Release (3.18)

Methods and models for handling zero-inflated single cell assay data.

Author: Andrew McDavid [aut, cre], Greg Finak [aut], Masanao Yajima [aut]

Maintainer: Andrew McDavid <Andrew_McDavid at urmc.rochester.edu>

Citation (from within R, enter citation("MAST")):

Installation

To install this package, start R (version "4.3") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("MAST")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("MAST")
An Introduction to MAST HTML R Script
Interoptability between MAST and SingleCellExperiment-derived packages HTML R Script
Using MAST for filtering, differential expression and gene set enrichment in MAIT cells HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews DifferentialExpression, GeneExpression, GeneSetEnrichment, RNASeq, SingleCell, Software, Transcriptomics
Version 1.28.0
In Bioconductor since BioC 3.4 (R-3.3) (7.5 years)
License GPL(>= 2)
Depends SingleCellExperiment(>= 1.2.0), R (>= 3.5)
Imports Biobase, BiocGenerics, S4Vectors, data.table, ggplot2, plyr, stringr, abind, methods, parallel, reshape2, stats, stats4, graphics, utils, SummarizedExperiment(>= 1.5.3), progress, Matrix
System Requirements
URL https://github.com/RGLab/MAST/
Bug Reports https://github.com/RGLab/MAST/issues
See More
Suggests knitr, rmarkdown, testthat, lme4 (>= 1.0), blme, roxygen2 (> 6.0.0), numDeriv, car, gdata, lattice, GGally, GSEABase, NMF, TxDb.Hsapiens.UCSC.hg19.knownGene, rsvd, limma, RColorBrewer, BiocStyle, scater, DelayedArray, HDF5Array, zinbwave, dplyr
Linking To
Enhances
Depends On Me POWSC
Imports Me benchdamic, celaref, singleCellTK
Suggests Me clusterExperiment, EWCE
Links To Me
Build Report Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package MAST_1.28.0.tar.gz
Windows Binary MAST_1.28.0.zip
macOS Binary (x86_64) MAST_1.28.0.tgz
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/MAST
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/MAST
Bioc Package Browser https://code.bioconductor.org/browse/MAST/
Package Short Url https://bioconductor.org/packages/MAST/
Package Downloads Report Download Stats