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

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

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This study developed a method to identify disease-correlated pathways by integrating copy numbers (CN) and gene expression (GE). To evaluate the correlation between CN and GE, a suitable window size was assessed by simulation. Gene Set Enrichment Analysis (GSEA) was utilized to identify the possible pathways by CN, GE, and their correlations, respectively. Each of those enriched pathways was further assigned a score to incorporate the information from CN, GE, and their correlations. A dataset of 44 female non-smoking lung cancer patients with both normal and tumor tissues was used to evaluate the performance of this method. To further appraise the predicting abilities of those pathways, patients were classified by support vector machines using the pathways identified by only copy number, only gene expression and incorporating CN, GE, and their correlations. The results showed that the proposed method earned higher accuracy, sensitivity and specificity than traditional methods.

Original languageEnglish
Title of host publicationProceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010
Pages599-602
Number of pages4
DOIs
StatePublished - 2010
Externally publishedYes
Event2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010 - Hong Kong, China
Duration: 18 12 201021 12 2010

Publication series

NameProceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010

Conference

Conference2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010
Country/TerritoryChina
CityHong Kong
Period18/12/1021/12/10

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