miloR
This is the development version of miloR; for the stable release version, see miloR.
Differential neighbourhood abundance testing on a graph
Bioconductor version: Development (3.24)
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")):
Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M (2015). "Orchestrating high-throughput genomic analysis with Bioconductor." Nature Methods, 12(2), 115–121. doi:10.1038/nmeth.3252.
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JYH, Zhang J (2004). "Bioconductor: open software development for computational biology and bioinformatics." Genome Biology, 5(10), R80. doi:10.1186/gb-2004-5-10-r80.
Installation
To install this package, start R (version "4.6") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
## The following initializes the development version of Bioconductor
BiocManager::install(version = "devel")
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 | 2.9.1 |
| In Bioconductor since | BioC 3.13 (R-4.1) (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 |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | miloR_2.9.1.tar.gz |
| Windows Binary (x86_64) | miloR_2.9.1.zip |
| macOS Binary (big-sur-x86_64) | miloR_2.9.1.tgz |
| macOS Binary (sonoma-arm64) | miloR_2.9.1.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 |