iGC—an integrated analysis package of gene expression and copy number alteration

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• 作者：Yi-Pin Lai ; Liang-Bo Wang ; Wei-An Wang ; Liang-Chuan Lai…
• 关键词：Copy number alteration ; Gene expression ; R/Bioconductor
• 刊名：BMC Bioinformatics
• 出版年：2017
• 出版时间：December 2017
• 年：2017
• 卷：18
• 期：1
• 全文大小：2553KB
• 刊物主题：Bioinformatics; Microarrays; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Algorithms;
• 出版者：BioMed Central
• ISSN：1471-2105
• 卷排序：18

文摘

BackgroundWith 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.