MAST
Model-based Analysis of Single Cell Transcriptomics
Bioconductor version: Release (3.17)
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("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 | ||
NEWS | Text |
Details
biocViews | DifferentialExpression, GeneExpression, GeneSetEnrichment, RNASeq, SingleCell, Software, Transcriptomics |
Version | 1.26.0 |
In Bioconductor since | BioC 3.4 (R-3.3) (7 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 |
Linking To | |
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 |
System Requirements | |
Enhances | |
URL | https://github.com/RGLab/MAST/ |
Bug Reports | https://github.com/RGLab/MAST/issues |
See More
Depends On Me | POWSC |
Imports Me | benchdamic, celaref, singleCellTK |
Suggests Me | clusterExperiment, EWCE |
Links To Me | |
Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | MAST_1.26.0.tar.gz |
Windows Binary | MAST_1.26.0.zip |
macOS Binary (x86_64) | MAST_1.26.0.tgz |
macOS Binary (arm64) | MAST_1.25.1.tgz |
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 |