Takes as input an incomplete perturbation profile and differential gene expression in log odds and infers unobserved perturbations and augments observed ones. The inference is done by iteratively inferring a network from the perturbations and inferring perturbations from the network. The network inference is done by Nested Effects Models.
|Bioconductor views||ATACSeq CRISPR Classification DNASeq DifferentialExpression DifferentialMethylation GeneExpression GeneSignaling Network NetworkInference NeuralNetwork Pathways PooledScreens RNASeq SingleCell Software SystemsBiology|
|Package repository||View on GitHub|
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