Gene-set profiles: Visualizing dissimilarity within gene co-expression networks for biomarker identification
Conference proceedings article
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Publication Details
Author list: Shama S., Lu P., Doungpan N., Meechai A., Chan J.H.
Publisher: Hindawi
Publication year: 2017
Volume number: Part F130152
Start page: 79
End page: 80
Number of pages: 2
ISBN: 9781450352925
ISSN: 0146-9428
eISSN: 1745-4557
Languages: English-Great Britain (EN-GB)
Abstract
We present a method to visualize gene co-expression from microarray data by plotting profiles of dissimilarity within gene-sets of biological pathways. A gene co-expression network is created by computing the correlation between each gene pair in a gene-set. We transform the networks into scale-free networks in order to calculate the dissimilarity weights that are used to create our profiles. Our approach further distinguishes between gene pairs consisting of both, one, or no statistically significant genes. We and that the shapes and density of the profiles provide useful information for identification of disease gene biomarkers. Our results provide a means of visualizing the overall distribution of gene dissimilarity for each gene-set, as well as how gene dissimilarity is linked to the mutual signifi?cance of gene pairs within a gene-set. ฉ 2017 Copyright held by the owner/author(s).
Keywords
biomarker, Dissimilarity, Gene co-expression network, gene-set profile, topological overlap,, WGCNA
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