zscore.wrap: Zscore wrapper function

In netbenchmark: Benchmarking of several gene network inference methods

Description

Z-score wrapper function.

Usage

    zscore.wrap(data)

Arguments

data	Numeric matrix with the microarray dataset to infer the network. Columns contain variables and rows contain samples.

Details

Zscore is a method that assumes interventional data, more concretely knockout experiments that leads to a change in other genes. The assumption is that the knocked-out gene i in the experiment k affects more strongly to the genes that it regulates than the others, the effect of the gene i over the gene j is captured with the Zscore z_{ij}:

z_{ij}=|\frac{x_{jk}-μ_j}{σ_j}|

mu_j and σ_j are respectively the mean and standard deviation of the empirical distribution of the gene j.

Value

zscore.wrap returns a matrix which is the weighted adjacency matrix of the network inferred by Zscore algorithm.

References

Prill, Robert J., et al. "Towards a rigorous assessment of systems biology models: the DREAM3 challenges." PloS one 5.2 (2010): e9202.

Examples

    # Data
    data <- runif(100)
    dim(data) <- c(10,10)
    # Inference
    net <- zscore.wrap(as.data.frame(data))

Example output

Loading required package: grndata

netbenchmark documentation built on May 2, 2019, 6:08 p.m.