This package is for version 3.15 of Bioconductor; for the stable, up-to-date release version, see miloR.
Bioconductor version: 3.15
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 cruk.cam.ac.uk>
Citation (from within R,
enter citation("miloR")
):
To install this package, start R (version "4.2") 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.
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 |
HTML | R Script | Using contrasts for differential abundance testing |
Reference Manual | ||
Text | NEWS | |
Text | LICENSE |
biocViews | FunctionalGenomics, MultipleComparison, SingleCell, Software |
Version | 1.4.0 |
In Bioconductor since | BioC 3.13 (R-4.1) (1.5 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 |
LinkingTo | |
Suggests | testthat, MASS, mvtnorm, scater, scran, covr, knitr, rmarkdown, uwot, scuttle, BiocStyle, MouseGastrulationData, MouseThymusAgeing, 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 |
Follow Installation instructions to use this package in your R session.
Source Package | miloR_1.4.0.tar.gz |
Windows Binary | miloR_1.4.0.zip |
macOS Binary (x86_64) | miloR_1.4.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/miloR |
Source Repository (Developer Access) | git clone [email protected]:packages/miloR |
Package Short Url | https://bioconductor.org/packages/miloR/ |
Package Downloads Report | Download Stats |
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