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 details |
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Author | Martin Pirkl |
Bioconductor views | ATACSeq CRISPR DNASeq GeneExpression Network NetworkInference Pathways PooledScreens RNASeq SingleCell SystemsBiology |
Maintainer | Martin Pirkl <martin.pirkl@bsse.ethz.ch> |
License | GPL-3 |
Version | 1.6.5 |
Package repository | View on Bioconductor |
Installation |
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