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miloR

Differential neighbourhood abundance testing on a graph

Bioconductor version: Release (3.17)

Milo 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 abdn.ac.uk>

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

Installation

To install this package, start R (version "4.3") 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")
Differential abundance testing with Milo HTML R Script
Differential abundance testing with Milo - Mouse gastrulation example HTML R Script
Using contrasts for differential abundance testing HTML R Script
Reference Manual PDF
NEWS Text
LICENSE Text

Details

biocViews FunctionalGenomics, MultipleComparison, SingleCell, Software
Version 1.8.1
In Bioconductor since BioC 3.13 (R-4.1) (2 years)
License GPL-3 + file LICENSE
Depends R (>= 4.0.0), edgeR
Imports BiocNeighbors, BiocGenerics, 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
Linking To
Suggests testthat, MASS, mvtnorm, scater, scran, covr, knitr, rmarkdown, uwot, scuttle, BiocStyle, MouseGastrulationData, MouseThymusAgeing, magick, RCurl, curl, graphics
System Requirements
Enhances
URL https://marionilab.github.io/miloR
Bug Reports https://github.com/MarioniLab/miloR/issues
See More
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_1.8.1.tar.gz
Windows Binary miloR_1.8.1.zip (64-bit only)
macOS Binary (x86_64) miloR_1.8.1.tgz
macOS Binary (arm64) miloR_1.8.1.tgz
Source Repository git clone https://git.bioconductor.org/packages/miloR
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/miloR
Bioc Package Browser https://code.bioconductor.org/browse/miloR/
Package Short Url https://bioconductor.org/packages/miloR/
Package Downloads Report Download Stats