期刊论文详细信息
PeerJ | |
GeNET: a web application to explore and share Gene Co-expression Network Analysis data | |
Amit P. Desai1  Lourdes Peña-Castillo1  Mehdi Razeghin1  Oscar Meruvia-Pastor1  | |
[1]Department of Computer Science, Memorial University of Newfoundland, St. John’s, Canada | |
关键词: Gene expression; Gene co-expression network analysis (GCNA); Data visualization; Web tool; GeNET; Transcriptomics; | |
DOI : 10.7717/peerj.3678 | |
来源: DOAJ |
【 摘 要 】
Gene Co-expression Network Analysis (GCNA) is a popular approach to analyze a collection of gene expression profiles. GCNA yields an assignment of genes to gene co-expression modules, a list of gene sets statistically over-represented in these modules, and a gene-to-gene network. There are several computer programs for gene-to-gene network visualization, but these programs have limitations in terms of integrating all the data generated by a GCNA and making these data available online. To facilitate sharing and study of GCNA data, we developed GeNET. For researchers interested in sharing their GCNA data, GeNET provides a convenient interface to upload their data and automatically make it accessible to the public through an online server. For researchers interested in exploring GCNA data published by others, GeNET provides an intuitive online tool to interactively explore GCNA data by genes, gene sets or modules. In addition, GeNET allows users to download all or part of the published data for further computational analysis. To demonstrate the applicability of GeNET, we imported three published GCNA datasets, the largest of which consists of roughly 17,000 genes and 200 conditions. GeNET is available at bengi.cs.mun.ca/genet.【 授权许可】
Unknown