title: A matrix rank based concordance index for evaluating and detecting conditional specific co-expressed gene modules.
abstract: Gene co-expression network analysis (GCNA) is widely adopted in bioinformatics and biomedical research with applications such as gene function prediction, protein-protein interaction inference, disease markers identification, and copy number variance discovery. Currently there is a lack of rigorous analysis on the mathematical condition for which the co-expressed gene module should satisfy.
  
  
  
  In this paper, we present a linear algebraic based Centralized Concordance Index (CCI) for evaluating the concordance of co-expressed gene modules from gene co-expression network analysis. The CCI can be used to evaluate the performance for co-expression network analysis algorithms as well as for detecting condition specific co-expression modules. We applied CCI in detecting lung tumor specific gene modules.
  
  
  
  Simulation showed that CCI is a robust indicator for evaluating the concordance of a group of co-expressed genes. The application to lung cancer datasets revealed interesting potential tumor specific genetic alterations including CNVs and even hints for gene-fusion. Deeper analysis required for understanding the molecular mechanisms of all such condition specific co-expression relationships.
  
  
  
  The CCI can be used to evaluate the performance for co-expression network analysis algorithms as well as for detecting condition specific co-expression modules. It is shown to be more robust to outliers and interfering modules than density based on Pearson correlation coefficients.
authors.affiliation: College of Computer and Control Engineering, Nankai University, Tianjin, China.|College of Software, Nankai University, Tianjin, China.|Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA.
authors.forename: Zhi
authors.initials: Z
authors.lastname: Han
authors.affiliation: Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA.|The CCC Biomedical Informatics Shared Resource, The Ohio State University, Columbus, OH, USA.
authors.forename: Jie
authors.initials: J
authors.lastname: Zhang
authors.affiliation: College of Computer and Control Engineering, Nankai University, Tianjin, China.|College of Software, Nankai University, Tianjin, China.
authors.forename: Guoyuan
authors.initials: G
authors.lastname: Sun
authors.affiliation: College of Computer and Control Engineering, Nankai University, Tianjin, China.|College of Software, Nankai University, Tianjin, China.
authors.forename: Gang
authors.initials: G
authors.lastname: Liu
authors.affiliation: Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA. kun.huang@osumc.edu.|The CCC Biomedical Informatics Shared Resource, The Ohio State University, Columbus, OH, USA. kun.huang@osumc.edu.
authors.forename: Kun
authors.initials: K
authors.lastname: Huang
mesh_terms: D000465:Algorithms; D056915:DNA Copy Number Variations / Q000235:genetics; D015972:Gene Expression Regulation, Neoplastic / Q000235:genetics*; D053263:Gene Regulatory Networks / Q000235:genetics*; D006801:Humans; D008175:Lung Neoplasms / Q000235:genetics* / Q000473:pathology; D008962:Models, Theoretical; D009363:Neoplasm Proteins / Q000235:genetics*; D015398:Signal Transduction / Q000235:genetics
chemical_list: D009363:Neoplasm Proteins