Concurrent analysis of copy number variation and gene expression: Application in paired non-smoking female lung cancer patients

Pei Chun Chen, Tzu Pin Lu, Jung Chih Chang, Liang Chuan Lai, Mong Hsun Tsai, Chuhsing Kate Hsiao, Eric Y. Chuang*

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

Abstract

Recent studies indicate that both genomic alterations and transcriptional dysregulation influence the disease progresses. This study proposes a method identifying pathways by integrating copy numbers (CN), gene expressions (GE) and their correlations. A lung cancer patients dataset with both normal and tumor tissues is utilized to evaluate the performance of the proposed method. To further appraise the predicting abilities of those pathways, these patients are classified by support vector machines. Based on the classification results, pathways integrating CN, GE and their correlations is more informative and biologically meaningful and perform better than pathways obtained by only CN or only GE.

Original languageEnglish
Pages (from-to)92-104
Number of pages13
JournalInternational Journal of Data Mining and Bioinformatics
Volume8
Issue number1
DOIs
StatePublished - 2013
Externally publishedYes

Keywords

  • CN
  • Concurrent analysis
  • Copy number
  • GE
  • Gene expression
  • Gene set enrichment analysis
  • Pathways
  • Support vector machine

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