CHD: Identification of dysfunctional modules and disease genes in congenital heart disease by a network-based approach
- Last updated: Oct 28, 2011
Introduction#
Welcome to our website! This is the supplementary materials webpage for our paper "Identification of dysfunctional modules and disease genes in congenital heart disease by a network-based approach". The source code and data used in this paper can be available here. Pay attention to the users: You can use and redistribute the data and code if you accept GNU General Public License (GPL). Any questions, please contact me by zpliu@sibs.ac.cn.
Background: The incidence of congenital heart disease (CHD) is continuously increasing among infants born alive nowadays, making it one of the leading causes of infant morbidity worldwide. Various studies suggest that both genetic and environmental factors lead to CHD, and therefore identifying its candidate genes and disease-markers has been one of the central topics in CHD research. By using the high-throughput genomic data of CHD which are available recently, network-based methods provide powerful alternatives of systematic analysis of complex diseases and identification of dysfunctional modules and candidate disease genes.
Results: In this paper, by modeling the information flow from source disease genes to targets of differentially expressed genes via a context-specific protein-protein interaction network, we extracted dysfunctional modules which were then validated by various types of measurements and independent datasets. Network topology analysis of these modules revealed major and auxiliary pathways and cellular processes in CHD, demonstrating the biological usefulness of the identified modules. We also prioritized a list of candidate CHD genes from these modules using a guilt-by-association approach, which are well supported by various kinds of literature and experimental evidence.
Reference#
- Danning He, Zhi-Ping Liu, Luonan Chen: Identification of dysfunctional modules and disease genes in congenital heart disease by a network-based approach. Submitted to BMC Genomics.
Data and code:#
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