-
recipe
bioconductor-mnem
Mixture Nested Effects Models
- Homepage
- License
GPL-3
- Recipe
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.
-
package
bioconductor-mnem
¶ -
- Versions
1.6.1-0
,1.4.0-0
- Depends
bioconductor-graph
>=1.68.0,<1.69.0
bioconductor-linnorm
>=2.14.0,<2.15.0
bioconductor-rgraphviz
>=2.34.0,<2.35.0
libblas
>=3.8.0,<4.0a0
libgcc-ng
>=7.5.0
liblapack
>=3.8.0,<4.0a0
libstdcxx-ng
>=7.5.0
r-base
>=4.0,<4.1.0a0
- Required By
Installation
With an activated Bioconda channel (see 2. Set up channels), install with:
conda install bioconductor-mnem
and update with:
conda update bioconductor-mnem
or use the docker container:
docker pull quay.io/biocontainers/bioconductor-mnem:<tag>
(see bioconductor-mnem/tags for valid values for
<tag>
)
Link to this page¶
Render an badge with the following MarkDown:
[](http://bioconda.github.io/recipes/bioconductor-mnem/README.html)