miloR
This is the released version of miloR; for the devel version, see miloR.
Differential neighbourhood abundance testing on a graph
Bioconductor version: Release (3.23)
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 abdn.ac.uk>
citation("miloR")):Mike Morgan, Emma Dann. miloR: Differential neighbourhood abundance testing on a graph. doi:10.18129/B9.bioc.miloR, R package version 2.8.1, https://bioconductor.org/packages/miloR.
Generated from the package metadata; it may differ from the package's own citation.
Installation
To install this package, start R (version "4.6") 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")| Using contrasts for differential abundance testing | HTML | R Script |
| 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 |
| Reference Manual | ||
| NEWS | Text | |
| LICENSE | Text |
Details
| biocViews | FunctionalGenomics, MultipleComparison, SingleCell, Software |
| Version | 2.8.1 |
| In Bioconductor since | BioC 3.13 (R-4.1) (5.5 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, pracma, numDeriv |
| System Requirements | |
| URL | https://marionilab.github.io/miloR |
| Bug Reports | https://github.com/MarioniLab/miloR/issues |
See More
| Suggests | testthat, mvtnorm, scater, scran, covr, knitr, rmarkdown, uwot, scuttle, BiocStyle, MouseGastrulationData, MouseThymusAgeing, magick, RCurl, MASS, curl, scRNAseq, graphics, sparseMatrixStats |
| Linking To | Rcpp, RcppArmadillo |
| Enhances | |
| Depends On Me | |
| Imports Me | dandelionR |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report, r-universe |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | miloR_2.8.1.tar.gz |
| Windows Binary (x86_64) | miloR_2.8.1.zip |
| macOS Binary (big-sur-x86_64) | miloR_2.8.1.tgz |
| macOS Binary (sonoma-arm64) | miloR_2.8.1.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/miloR |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/miloR |
| Package Short Url | https://bioconductor.org/packages/miloR/ |
| Package Downloads Report | Download Stats |
| Old Source Packages for BioC 3.23 | Source Archive |