NDLI: Stratification of Gene Coexpression Patterns and GO Function Mining for a RNA-Seq Data Series

Content Provider	PubMed Central
Author	Zhao, Hui Cao, Fenglin Gong, Yonghui Xu, Huafeng Fei, Yiping Wu, Longyue Ye, Xiangmei Yang, Dongguang Liu, Xiuhua Xia, Li Zhou, Jin
Copyright Year	2014
Abstract	RNA-Seq is emerging as an increasingly important tool in biological research, and it provides the most direct evidence of the relationship between the physiological state and molecular changes in cells. A large amount of RNA-Seq data across diverse experimental conditions have been generated and deposited in public databases. However, most developed approaches for coexpression analyses focus on the coexpression pattern mining of the transcriptome, thereby ignoring the magnitude of gene differences in one pattern. Furthermore, the functional relationships of genes in one pattern, and notably among patterns, were not always recognized. In this study, we developed an integrated strategy to identify differential coexpression patterns of genes and probed the functional mechanisms of the modules. Two real datasets were used to validate the method and allow comparisons with other methods. One of the datasets was selected to illustrate the flow of a typical analysis. In summary, we present an approach to robustly detect coexpression patterns in transcriptomes and to stratify patterns according to their relative differences. Furthermore, a global relationship between patterns and biological functions was constructed. In addition, a freely accessible web toolkit “coexpression pattern mining and GO functional analysis” (COGO) was developed.
Related Links	http://dx.doi.org/10.1155/2014/969768
Starting Page	969768
File Format	PDF
ISSN	23146141
e-ISSN	23146141
Journal	BioMed Research International
Volume Number	2014
Language	English
Publisher	Hindawi Publishing Corporation
Publisher Date	2014-01-01
Access Restriction	Open
Rights Holder	Hindawi Publishing Corporation
Subject Keyword	Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Immunology and Microbiology Medicine Biochemistry, Genetics and Molecular Biology

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