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. |