Introduction

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.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.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 .

Publications

  1. iGC-an integrated analysis package of gene expression and copy number alteration.
    Cite this
    Lai YP, Wang LB, Wang WA, Lai LC, Tsai MH, Lu TP, Chuang EY, 2017-01-01 - BMC bioinformatics

Credits

  1. Yi-Pin Lai
    Developer

    Bioinformatics and Biostatistics Core, Center of Genomic Medicine, Taiwan, Province of China

  2. Liang-Bo Wang
    Developer

    Graduate Institute of Biomedical Electronics and Bioinformatics, Department of Electrical Engineering, Taiwan, Province of China

  3. Wei-An Wang
    Developer

    Bioinformatics and Biostatistics Core, Center of Genomic Medicine, Taiwan, Province of China

  4. Liang-Chuan Lai
    Developer

    Graduate Institute of Physiology, National Taiwan University, Taiwan, Province of China

  5. Mong-Hsun Tsai
    Developer

    Institute of Biotechnology, National Taiwan University, Taiwan, Province of China

  6. Tzu-Pin Lu
    Developer

    Department of Public Health, Institute of Epidemiology and Preventive Medicine

  7. Eric Y Chuang
    Investigator

    Graduate Institute of Biomedical Electronics and Bioinformatics, Department of Electrical Engineering, Taiwan, Province of China

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Summary
AccessionBT001858
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesR
User InterfaceTerminal Command Line
Download Count0
Country/RegionTaiwan, Province of China
Submitted ByEric Y Chuang