miloR
Differential neighbourhood abundance testing on a graph
Bioconductor version: Release (3.20)
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")
):
Installation
To install this package, start R (version "4.4") 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 |
Mixed effect models for Milo DA testing | HTML | R Script |
Using contrasts for differential abundance testing | HTML | R Script |
Reference Manual | ||
NEWS | Text | |
LICENSE | Text |
Details
biocViews | FunctionalGenomics, MultipleComparison, SingleCell, Software |
Version | 2.2.0 |
In Bioconductor since | BioC 3.13 (R-4.1) (3.5 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, RcppEigen, RcppML |
Enhances | |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | miloR_2.2.0.tar.gz |
Windows Binary (x86_64) | miloR_2.2.0.zip |
macOS Binary (x86_64) | miloR_2.2.0.tgz |
macOS Binary (arm64) | miloR_2.1.0.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 |