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Differential neighbourhood abundance testing on a graph

Bioconductor version: Release (3.19)

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

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

Maintainer: Mike Morgan <michael.morgan at>

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


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


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


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

Differential abundance testing with Milo HTML R Script
Differential abundance testing with Milo - Mouse gastrulation example HTML R Script
Mixed effect models for Milo DA testing HTML R Script
Using contrasts for differential abundance testing HTML R Script
Reference Manual PDF


biocViews FunctionalGenomics, MultipleComparison, SingleCell, Software
Version 2.0.0
In Bioconductor since BioC 3.13 (R-4.1) (3 years)
License GPL-3 + file LICENSE
Depends R (>= 4.0.0), edgeR
Imports BiocNeighbors, BiocGenerics, SingleCellExperiment, Matrix (>= 1.3-0), MatrixGenerics, S4Vectors, stats, stringr, methods, igraph, irlba, utils, cowplot, BiocParallel, BiocSingular, limma, ggplot2, tibble, matrixStats, ggraph, gtools, SummarizedExperiment, patchwork, tidyr, dplyr, ggrepel, ggbeeswarm, RColorBrewer, grDevices, Rcpp, numDeriv
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Suggests testthat, mvtnorm, scater, scran, covr, knitr, rmarkdown, uwot, scuttle, BiocStyle, MouseGastrulationData, MouseThymusAgeing, magick, RCurl, MASS, curl, scRNAseq, graphics
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Source Package miloR_2.0.0.tar.gz
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macOS Binary (x86_64) miloR_2.0.0.tgz
macOS Binary (arm64) miloR_2.0.0.tgz
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