Title
DCoSpect: A Novel Differentially Coexpressed Gene Module Detection Algorithm Using Spectral Clustering
Abstract
Microarray-based gene coexpression analysis is widely used to investigate the regulation pattern of a group (or cluster) of genes in a specific phenotype condition. Recent approaches look for differential coexpression patterns, where there exists a significant change in coexpression pattern between two phenotype conditions. These changes happen due to the alternation in regulatory mechanism across different phenotype conditions. Here, we develop a novel algorithm DCoSpect to identify differentially coexpressed modules across two phenotype conditions. DCoSpect uses spectral clustering algorithm to cluster the differential coexpression network. The proposed method is assessed by comparing with state-of-the-art techniques. We show that DCoSpect outperforms the state of the art in terms of significance and interpretability of detected modules. The biological significance of the discovered modules is also investigated using GO and pathway enrichment analysis.
Year
DOI
Venue
2015
10.1007/978-81-322-2695-6_7
PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON FRONTIERS IN INTELLIGENT COMPUTING: THEORY AND APPLICATIONS (FICTA) 2015
Keywords
Field
DocType
Microarray gene expression,Differential coexpression,Spectral clustering,Correlation
Interpretability,Spectral clustering,Gene,Microarray,Spectral clustering algorithm,Phenotype,Computer science,Algorithm,Correlation,Alternation (linguistics)
Conference
Volume
ISSN
Citations 
404
2194-5357
0
PageRank 
References 
Authors
0.34
8
3
Name
Order
Citations
PageRank
sumanta ray100.34
sinchani chakraborty200.34
Anirban Mukhopadhyay371150.07