Integrative pathway analysis with gene expression, miRNA, methylation and copy number variation for breast cancer subtypes.

IF 0.9 4区 数学 Q3 Mathematics
Henry Linder, Yuping Zhang, Yunqi Wang, Zhengqing Ouyang
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引用次数: 0

Abstract

Developments in biotechnologies enable multi-platform data collection for functional genomic units apart from the gene. Profiling of non-coding microRNAs (miRNAs) is a valuable tool for understanding the molecular profile of the cell, both for canonical functions and malignant behavior due to complex diseases. We propose a graphical mixed-effects statistical model incorporating miRNA-gene target relationships. We implement an integrative pathway analysis that leverages measurements of miRNA activity for joint analysis with multimodal observations of gene activity including gene expression, methylation, and copy number variation. We apply our analysis to a breast cancer dataset, and consider differential activity in signaling pathways across breast tumor subtypes. We offer discussion of specific signaling pathways and the effect of miRNA integration, as well as publish an interactive data visualization to give public access to the results of our analysis.

利用基因表达、miRNA、甲基化和拷贝数变异对乳腺癌亚型进行整合通路分析。
生物技术的发展使基因以外的功能基因组单元的多平台数据收集成为可能。对非编码 microRNA(miRNA)进行分析是了解细胞分子特征的重要工具,既能了解典型功能,也能了解复杂疾病导致的恶性行为。我们提出了一种包含 miRNA 与基因靶标关系的图形混合效应统计模型。我们实施了一种综合通路分析,利用对 miRNA 活性的测量与基因活性的多模态观测(包括基因表达、甲基化和拷贝数变异)进行联合分析。我们将分析结果应用于乳腺癌数据集,并考虑了不同乳腺癌亚型的信号通路活动差异。我们对特定信号通路和 miRNA 整合的影响进行了讨论,并发布了交互式数据可视化,让公众了解我们的分析结果。
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来源期刊
CiteScore
1.20
自引率
11.10%
发文量
8
审稿时长
6-12 weeks
期刊介绍: Statistical Applications in Genetics and Molecular Biology seeks to publish significant research on the application of statistical ideas to problems arising from computational biology. The focus of the papers should be on the relevant statistical issues but should contain a succinct description of the relevant biological problem being considered. The range of topics is wide and will include topics such as linkage mapping, association studies, gene finding and sequence alignment, protein structure prediction, design and analysis of microarray data, molecular evolution and phylogenetic trees, DNA topology, and data base search strategies. Both original research and review articles will be warmly received.
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