miloR
This package is for version 3.20 of Bioconductor; for the stable, up-to-date release version, see miloR.
Differential neighbourhood abundance testing on a graph
Bioconductor version: 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]
             
           
, 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) (4 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_2.2.0.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 |