epiNEM


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Documentation for package ‘epiNEM’ version 1.0.1

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AddLogicGates extend model with node representing logic gate
CreateExtendedAdjacency Create an extended adjacency matrix
CreateRandomGraph Create a random graph
CreateTopology create topology for a randomly generated pathway topology
epiAnno Plots logical gate data annotation. The 8 heatmaps visualize what perfect data would look like in respective to each logical gate. Perfect data is equivalent to Boolean truth tables.
epiNEM Epistatic NEMs - main function. This function contains the inference algorithm to learn logical networks from knock-down data including double knock-downs.
epiScreen This function is used to analyse knock-out screens with multiple double and single knock-outs combined in one data set.
ExtendTopology Extending topology of normal "nem"
GenerateData Generate data from extended model. Given a model created from CreateTopology and ExtendTopology, this function creeates acorresponding artificial data matrix, which is used as a ground truth for simulation studies.
HeatmapOP heatmap function based on the lattice package more information: ?xyplot
Mll Evaluation of graphs
plot.epiNEM Plots the winning pathway structure
plot.epiScreen Plots the sresults of a systematic knock-out screen
plot.epiSim Plots the simulation results
sameith_GO graph-based GO similarity scores, string GO annotations for Sameith et al., 2015 data The data consists of lists including epiNEM identified and general similarity scores and GO annotations for each triple. For details see the vignette.
sameith_string sig. of string interaction scores for Sameith et al., 2015 data The data consists of a list including a vectors of pairs (for interactions) and a corresponding list of interaction scores derived form the string database. For details see the vignette.
samscreen Example data: epiNEM results for the Sameith et al., 2015 knock-out screen The result of the epiNEM analysis of the data from "http://www.holstegelab.nl/publications/ sv/signaling_redundancy/downloads/DataS1.txt". The data consists of a list of matrices with the likelihoods (ll) for each analysed triple of signalling genes and the inferred logic (logic) for each triple. The signalling genes or modulators C are the rows and the signalling genes from the double knock-downs are in the columns. For details see the vignette.
sim Example data: simulation results Contains simulation results. How they were aquired is explained in the vignette. The data conists of a list of data matrices holding sensitivity and specificity (spec, sens) of network edges for the variious methods compared to the ground truth, sensitivity and specificity (sens2, spec2) of the expected data for epiNEM and Boolean NEMs and accuracy of the inferred logics for both. The different methods are in the rows and the columns denote the different independent simulation runs.
SimEpiNEM Compares different network reconstruction algorithm on simulated data.
wageningen_GO graph-based GO similarity scores, string GO annotations for van Wageningen et al., 2015 data The data consists of lists including epiNEM identified and general similarity scores and GO annotations for each triple. For details see the vignette.
wageningen_string sig. of string interaction scores for van Wageningen et al., 2010 data The data consists of a list including a vectors of pairs (for interactions) and a corresponding list of interaction scores derived form the string database. For details see the vignette.
wagscreen Example data: epiNEM results for the Wageningen et al., 2010 knock-out screen "http://www.holstegelab.nl/publications/GSTF_geneticinteractions/ downloads/del_mutants_limma.txt" The data consists of a list of matrices with the likelihoods (ll) for each analysed triple of signalling genes and the inferred logic (logic) for each triple. The signalling genes or modulators C are the rows and the signalling genes from the double knock-downs are in the columns. For details see the vignette.