gnwdata: Synthetic data sources simulated using GeneNetWeaver

In wyguo/RLowPCor: Inference of co-expression gene network using relevance low order partial correlation from large scale expression data

Description

The sources include time-series composed of 1 perturbation x 5 experiments x 3 replicates for GNW100 and GNW500 networks, respectively. GNW100 includes 5 In Silico network structures with 100 genes used in DREAM4 challenge while GNW500 includes 5 network structures with 500 genes which are subsets of E.coli source network in GeneNetweaver. Each time course is sampled at 21 time points. In each experiment, one third of genes are randomly selcted and perturbed from steady states at initial time point and the perturbations are removed at half time duration. Biological and technical noises are added to the datasets according to the settings in DREAM4 challenge [1,2].

Usage

data(gnwdata)

Format

An object of data list

References

[1] Schaffter T, Marbach D, Floreano D: GeneNetWeaver: In silico benchmark generation and performance profiling of network inference methods. Bioinformatics 2011, 27(16):2263-2270.

[2] Marbach D, Prill RJ, Schaffter T, Mattiussi C, Floreano D, Stolovitzky G: Revealing strengths and weaknesses of methods for gene network inference. Proceedings of the National Academy of Sciences 2010, 107(14):6286-6291.

Examples

data(gnwdata)
sapply(gnwdata,names)

wyguo/RLowPCor documentation built on May 4, 2019, 12:04 p.m.