Man pages for dirmeier/knockout
Statistical Analysis of High-Throughput Genetic Perturbation Screens
| bootstrap | Create a bootstrap sample from a data-set |
| dataSet-methods | Getter for a data set |
| diffuse-methods | Network diffusion |
| filter-methods | Filter the rows of a perturbation data set |
| geneEffects-methods | Getter for the complete list of genes and their effect sizes |
| graph-methods | Getter for graph used for network diffusion |
| HMAnalysedPerturbationData-class | Data wrapper for analysed perturbation data using a... |
| hm-methods | Jointly analyse multiple genetic perturbation screens using a... |
| inference-methods | Getter for inference used for analysis of perturbation data |
| isBootstrapped-methods | Getter for boolean if boostrapping was used |
| modelFit-methods | Getter for model fit |
| nestedGeneEffects-methods | Getter for the completed list of nested gene effects |
| NetworkAnalysedPerturbationData-class | Data wrapper for analysed perturbation data using network... |
| params-methods | Getter for parameters used for analysis of perturbation data |
| PerturbationData-class | Data wrapper for a data set of a perturbation screen. |
| perturbatr-package | perturbatr |
| plot.NetworkAnalysedPerturbationData | Plot a 'NetworkAnalysedPerturbationData' object |
| plot.PerturbationData | Plot perturbation data |
| rbind.PerturbationData | Bind multiple perturbation data sets together by row |
| rnaiscreen | A pan-viral perturbation dataset |
| setModelData-methods | Create model data for an hierarchical model |
