mnem
This is the development version of mnem; for the stable release version, see mnem.
Mixture Nested Effects Models
Bioconductor version: Development (3.24)
Mixture Nested Effects Models (mnem) is an extension of Nested Effects Models and allows for the analysis of single cell perturbation data provided by methods like Perturb-Seq (Dixit et al., 2016) or Crop-Seq (Datlinger et al., 2017). In those experiments each of many cells is perturbed by a knock-down of a specific gene, i.e. several cells are perturbed by a knock-down of gene A, several by a knock-down of gene B, ... and so forth. The observed read-out has to be multi-trait and in the case of the Perturb-/Crop-Seq gene are expression profiles for each cell. mnem uses a mixture model to simultaneously cluster the cell population into k clusters and and infer k networks causally linking the perturbed genes for each cluster. The mixture components are inferred via an expectation maximization algorithm.
Author: Martin Pirkl [aut, cre]
Maintainer: Martin Pirkl <martinpirkl at yahoo.de>
citation("mnem")):
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("mnem")
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("mnem")| mnem | HTML | R Script |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | ATACSeq, CRISPR, DNASeq, GeneExpression, Network, NetworkInference, Pathways, PooledScreens, RNASeq, SingleCell, Software, SystemsBiology |
| Version | 1.29.0 |
| In Bioconductor since | BioC 3.9 (R-3.6) (7.5 years) |
| License | GPL-3 |
| Depends | R (>= 4.1) |
| Imports | cluster, graph, Rgraphviz, flexclust, lattice, naturalsort, snowfall, stats4, tsne, methods, graphics, stats, utils, Linnorm, data.table, Rcpp, RcppEigen, matrixStats, grDevices, e1071, ggplot2, wesanderson |
| System Requirements | |
| URL | https://github.com/cbg-ethz/mnem/ |
| Bug Reports | https://github.com/cbg-ethz/mnem/issues |
See More
| Suggests | knitr, devtools, rmarkdown, BiocGenerics, RUnit, epiNEM, BiocStyle |
| Linking To | Rcpp, RcppEigen |
| Enhances | |
| Depends On Me | nempi |
| Imports Me | bnem, epiNEM |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | mnem_1.29.0.tar.gz |
| Windows Binary (x86_64) | mnem_1.29.0.zip (64-bit only) |
| macOS Binary (big-sur-x86_64) | mnem_1.29.0.tgz |
| macOS Binary (sonoma-arm64) | mnem_1.29.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/mnem |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/mnem |
| Bioc Package Browser | https://code.bioconductor.org/browse/mnem/ |
| Package Short Url | https://bioconductor.org/packages/mnem/ |
| Package Downloads Report | Download Stats |