DCGL (version 1.02)

dataC: Simulated dataset based on deliberately-perturbed gene regulation networks (Yu, et al., 2010)

Description

Simulated gene expression dataset, each containing 1000 rows and 20 columns (Yu, et al., 2010).

Usage

data(dataC)

format

A data frame with 1000 observations 20 variables.

• dataC

{ A data frame with 1000 observations 20 columns. The expression values. }

Details

We simulated three dataset pairs (denoted dataA, dataB, dataC) using SynTReN based on a predefined E.coli gene regulatory network of a total of 1300 genes (Van den Bulcke, et al., 2006). Specifically, we selected a sub-network of 1000 genes as the original network,and exerted artificial perturbation on 10 percents of its links as if it was from a different condition. The three groups had different perturbation types.For dataC, we used regulation-elimination-alteration (removing 5 percents links and altering 5 percents links). In each data matrix, the first ten columns correspond to one condition and the second ten correspond to the other.

References

Yu H., Liu B-H., et al., Link-specific Quantitative Methods to Identify Differentially Coexpressed Genes and Gene Pairs. Submitted. 2010 Van den Bulcke, T., et al. (2006) SynTReN: a generator of synthetic gene expression data for design and analysis of structure learning algorithms, BMC Bioinformatics, 7, 43.

Examples

data(dataC)
dataC[,1:10] # exprssion data for condition 1
dataC[,11:20] # exprssion data for condition 2
row.names(dataC) # gene identifier