title: iGC-an integrated analysis package of gene expression and copy number alteration.
abstract: BACKGROUND
  With the advancement in high-throughput technologies, researchers can simultaneously investigate gene expression and copy number alteration (CNA) data from individual patients at a lower cost. Traditional analysis methods analyze each type of data individually and integrate their results using Venn diagrams. Challenges arise, however, when the results are irreproducible and inconsistent across multiple platforms. To address these issues, one possible approach is to concurrently analyze both gene expression profiling and CNAs in the same individual.
  
  
  RESULTS
  We have developed an open-source R/Bioconductor package (iGC). Multiple input formats are supported and users can define their own criteria for identifying differentially expressed genes driven by CNAs. The analysis of two real microarray datasets demonstrated that the CNA-driven genes identified by the iGC package showed significantly higher Pearson correlation coefficients with their gene expression levels and copy numbers than those genes located in a genomic region with CNA. Compared with the Venn diagram approach, the iGC package showed better performance.
  
  
  CONCLUSIONS
  The iGC package is effective and useful for identifying CNA-driven genes. By simultaneously considering both comparative genomic and transcriptomic data, it can provide better understanding of biological and medical questions. The iGC package's source code and manual are freely available at https://www.bioconductor.org/packages/release/bioc/html/iGC.html .
authors.affiliation: Bioinformatics and Biostatistics Core, Center of Genomic Medicine, National Taiwan University, Taipei, Taiwan.
authors.forename: Yi-Pin
authors.initials: YP
authors.lastname: Lai
authors.affiliation: Bioinformatics and Biostatistics Core, Center of Genomic Medicine, National Taiwan University, Taipei, Taiwan.|Graduate Institute of Biomedical Electronics and Bioinformatics, Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan.
authors.forename: Liang-Bo
authors.initials: LB
authors.lastname: Wang
authors.affiliation: Bioinformatics and Biostatistics Core, Center of Genomic Medicine, National Taiwan University, Taipei, Taiwan.
authors.forename: Wei-An
authors.initials: WA
authors.lastname: Wang
authors.affiliation: Bioinformatics and Biostatistics Core, Center of Genomic Medicine, National Taiwan University, Taipei, Taiwan.|Graduate Institute of Physiology, National Taiwan University, Taipei, Taiwan.
authors.forename: Liang-Chuan
authors.initials: LC
authors.lastname: Lai
authors.affiliation: Bioinformatics and Biostatistics Core, Center of Genomic Medicine, National Taiwan University, Taipei, Taiwan.|Institute of Biotechnology, National Taiwan University, Taipei, Taiwan.
authors.forename: Mong-Hsun
authors.initials: MH
authors.lastname: Tsai
authors.affiliation: Department of Public Health, Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan. tplu@ntu.edu.tw.
authors.forename: Tzu-Pin
authors.initials: TP
authors.lastname: Lu
authors.affiliation: Bioinformatics and Biostatistics Core, Center of Genomic Medicine, National Taiwan University, Taipei, Taiwan. chuangey@ntu.edu.tw.|Graduate Institute of Biomedical Electronics and Bioinformatics, Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan. chuangey@ntu.edu.tw.
authors.forename: Eric Y
authors.initials: EY
authors.lastname: Chuang
mesh_terms: D056915:DNA Copy Number Variations; D015870:Gene Expression; D020869:Gene Expression Profiling / Q000379:methods*; D016678:Genome; D006801:Humans; D012984:Software; D059467:Transcriptome
keywords: Copy number alteration; Gene expression; R/Bioconductor