Package: mnem
Type: Package
Title: Mixture Nested Effects Models
Version: 1.2.0
Author: Martin Pirkl
Maintainer: Martin Pirkl <martin.pirkl@bsse.ethz.ch>
Description: 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.
Depends: R (>= 3.6)
License: GPL-3
Encoding: UTF-8
LazyData: true
biocViews: Pathways, SystemsBiology, NetworkInference, Network, RNASeq,
        PooledScreens, SingleCell, CRISPR, ATACSeq, DNASeq,
        GeneExpression
RoxygenNote: 6.1.1
Imports: cluster, nem, epiNEM, graph, Rgraphviz, flexclust, lattice,
        naturalsort, snowfall, stats4, tsne, methods, graphics, stats,
        utils, Linnorm, data.table, Rcpp, RcppEigen, matrixStats,
        grDevices
LinkingTo: Rcpp, RcppEigen
VignetteBuilder: knitr
Suggests: knitr, devtools, rmarkdown, BiocGenerics, RUnit
NeedsCompilation: yes
git_url: https://git.bioconductor.org/packages/mnem
git_branch: RELEASE_3_10
git_last_commit: 1210f5a
git_last_commit_date: 2019-10-29
Date/Publication: 2019-10-29
Packaged: 2019-10-30 05:00:38 UTC; biocbuild
Built: R 3.6.1; i386-w64-mingw32; 2019-10-30 13:43:31 UTC; windows
Archs: i386, x64
