Differential Coexpression Analysis of Gene Expression Microarray Data


[Up] [Top]

Documentation for package ‘DCGL’ version 1.02

Help Pages

DCGL-package Differential Coexpression Analysis of Microarray Data
ASC Identify DCGs (Differentially-Coexpressed genes) based on 'Average Specific Connection'
dataA Simulated dataset based on deliberately-perturbed gene regulation networks (Yu, et al., 2010)
dataB Simulated dataset based on deliberately-perturbed gene regulation networks (Yu, et al., 2010)
dataC Simulated dataset based on deliberately-perturbed gene regulation networks (Yu, et al., 2010)
DCe To identify DCGs (Differentially-Coexpressed Genes) and DCLs (Differentially-Coexpressed Links)
DCGL Differential Coexpression Analysis of Microarray Data
DCp To identify DCGs (Differentially-Coexpressed genes) based on the 'Differential Coexpression Profile'
expressionBasedfilter To filter genes according to expression level
LFC Select DCLs based on 'Limit Fold Change' model
LRC Identify DCGs (Differentially-Coexpressed genes) based on 'Log Ratio Connections'
percentLinkfilter To filter gene coexpression links according to the max expression correlation value
qLinkfilter To filter gene coexpression links according to the q-values of expression correlation values
Simulated.ABC Simulated datasets based on deliberately-perturbed gene regulation networks (Yu, et al., 2010)
systematicLinkfilter A systematic procedure for estimating a cutoff threshold of coexpression networks
varianceBasedfilter To filter genes according to expression variability
WGCNA To identify DCGs (Differentially-Coexpressed genes) based on the 'Weighted Gene Coexpression Network Analysis'