miloR

DOI: 10.18129/B9.bioc.miloR    

This package is for version 3.14 of Bioconductor; for the stable, up-to-date release version, see miloR.

Differential neighbourhood abundance testing on a graph

Bioconductor version: 3.14

This package performs single-cell differential abundance testing. Cell states are modelled as representative neighbourhoods on a nearest neighbour graph. Hypothesis testing is performed using a negative bionomial generalized linear model.

Author: Mike Morgan [aut, cre], Emma Dann [aut, ctb]

Maintainer: Mike Morgan <michael.morgan at cruk.cam.ac.uk>

Installation

To install this package, start R (version "4.1") and enter:

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

BiocManager::install("miloR")

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("miloR")

 

HTML	R Script	Differential abundance testing with Milo
HTML	R Script	Differential abundance testing with Milo - Mouse gastrulation example
PDF		Reference Manual
Text		NEWS
Text		LICENSE

Details

biocViews	FunctionalGenomics, MultipleComparison, SingleCell, Software
Version	1.2.0
In Bioconductor since	BioC 3.13 (R-4.1) (1 year)
License	GPL-3 + file LICENSE
Depends	R (>= 4.0.0), edgeR
Imports	BiocNeighbors, SingleCellExperiment, Matrix (>= 1.3-0), S4Vectors, stats, stringr, methods, igraph, irlba, cowplot, BiocParallel, BiocSingular, limma, ggplot2, tibble, matrixStats, ggraph, gtools, SummarizedExperiment, patchwork, tidyr, dplyr, ggrepel, ggbeeswarm, RColorBrewer, grDevices
LinkingTo
Suggests	testthat, MASS, mvtnorm, scater, scran, covr, knitr, rmarkdown, uwot, BiocStyle, MouseGastrulationData, magick, RCurl, curl, graphics
SystemRequirements
Enhances
URL	https://marionilab.github.io/miloR
BugReports	https://github.com/MarioniLab/miloR/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report

Package Archives

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

Source Package	miloR_1.2.0.tar.gz
Windows Binary	miloR_1.2.0.zip (32- & 64-bit)
macOS 10.13 (High Sierra)	miloR_1.2.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/miloR
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/miloR
Package Short Url	https://bioconductor.org/packages/miloR/
Package Downloads Report	Download Stats