RT Journal Article SR Electronic T1 MODA: MOdule Differential Analysis for weighted gene co-expression network JF bioRxiv FD Cold Spring Harbor Laboratory SP 053496 DO 10.1101/053496 A1 Dong Li A1 James B. Brown A1 Luisa Orsini A1 Zhisong Pan A1 Guyu Hu A1 Shan He YR 2016 UL http://biorxiv.org/content/early/2016/05/19/053496.abstract AB Gene co-expression network differential analysis is designed to help biologists understand gene expression patterns under different condition. By comparing different gene co-expression networks we may find conserved part as well as condition specific set of genes. Taking the network as a collection as modules, we use a sample-saving method to construct condition-specific gene co-expression network, and identify differentially expressed subnetworks as conserved or condition specific modules which may be associated with biological processes. We have implemented the method as an R package which establishes a pipeline from expression profile to biological explanations. The usefulness of the method is also demonstrated by synthetic data as well as Daphnia magna gene expression data under different environmental stresses.Availability Available at https://www.cs.bham.ac.uk/szh/software.xhtmlContact s.he{at}cs.bham.ac.uk