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monocle

Clustering, differential expression, and trajectory analysis for single- cell RNA-Seq

Bioconductor version: 3.23 · Package version: 2.40.0

Monocle performs differential expression and time-series analysis for single-cell expression experiments. It orders individual cells according to progress through a biological process, without knowing ahead of time which genes define progress through that process. Monocle also performs differential expression analysis, clustering, visualization, and other useful tasks on single cell expression data. It is designed to work with RNA-Seq and qPCR data, but could be used with other types as well.

Installation

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

BiocManager::install("monocle")

Details

MaintainerCole Trapnell <coletrap@uw.edu>
AuthorCole Trapnell
LicenseArtistic-2.0
Downloads rank4170
Source branchRELEASE_3_23
biocViewsClustering, DataImport, DataRepresentation, DifferentialExpression, GeneExpression, ImmunoOncology, Infrastructure, MultipleComparison, QualityControl, RNASeq, Sequencing, Software, Visualization

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packagemonocle_2.40.0.tar.gz
Windows binary (x86_64)monocle_2.40.0.zip
macOS binary (arm64)monocle_2.40.0.tgz
macOS binary (x86_64)monocle_2.40.0.tgz
Dependencies

Depends: R (>= 2.10.0), methods, Matrix (>= 1.2-6), Biobase, ggplot2 (>= 1.0.0), VGAM (>= 1.0-6), DDRTree (>= 0.1.4)

Imports: parallel, igraph (>= 1.0.1), BiocGenerics, HSMMSingleCell (>= 0.101.5), plyr, cluster, combinat, fastICA, grid, irlba (>= 2.0.0), matrixStats, Rtsne, MASS, reshape2, leidenbase (>= 0.1.9), limma, tibble, dplyr, pheatmap, stringr, proxy, slam, viridis, stats, biocViews, RANN (>= 2.5), Rcpp (>= 0.12.0)

LinkingTo: Rcpp

Suggests: destiny, Hmisc, knitr, Seurat, scater, testthat

Reverse dependencies

Depends On Me (1): cicero

Imports Me (1): uSORT

Suggests Me (3): ClusterGVis, Seurat, sincell