Introduction: From Clustering to Density Plots3 years ago
Clustering | Visualization of networks
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| Nested Effects Models-based perturbation inference: | Inference of unobserved perturbations from gene expression profiles.4 years ago
Introduction | Installation and loading | Small example | Data simulation | Perturbation inference | Prior matrix | Final perturbation matrix | Session information | References:
| Epistatic Nested Effects Models: | Inferring mixed epistasis from indirect measurements of knock-out screens6 years ago
Introduction | Loading epiNEM | Quick start | Simulations | Yeast knock-out screens | Identification of significant modulators for pairs of double knock-outs | Validation of identified interactions | String-db interactions | Graph based GO similarity scores | Enrichment analysis | Enrichment of identified sets of modulators for each double knock-out | Enrichment of effect reporters for each identified modulator | Creation of data objects | Session information | References
| Mixture Nested Effects Models: | Simultaneous inference of causal networks and corresponding subpopulations from single cell perturbation data6 years ago
Introduction | Installation and loading | Small example | Data simulation | Network inference w.r.t. complexity | Cell responsibilities | Discrete data | Multiple perturbations | Application to pooled CRISPR screens | Cell cycle regulators (Perturb-seq) | Session information | Discrete data model | Expectation of the complete data log likelihood for large data sets | References: