Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China.
Beijing Engineering Research Center for IoT Software and Systems, Beijing, 100124, China.
Sci Rep. 2018 Jan 12;8(1):622. doi: 10.1038/s41598-017-18705-z.
Investigating how genes jointly affect complex human diseases is important, yet challenging. The network approach (e.g., weighted gene co-expression network analysis (WGCNA)) is a powerful tool. However, genomic data usually contain substantial batch effects, which could mask true genomic signals. Paired design is a powerful tool that can reduce batch effects. However, it is currently unclear how to appropriately apply WGCNA to genomic data from paired design. In this paper, we modified the current WGCNA pipeline to analyse high-throughput genomic data from paired design. We illustrated the modified WGCNA pipeline by analysing the miRNA dataset provided by Shiah et al. (2014), which contains forty oral squamous cell carcinoma (OSCC) specimens and their matched non-tumourous epithelial counterparts. OSCC is the sixth most common cancer worldwide. The modified WGCNA pipeline identified two sets of novel miRNAs associated with OSCC, in addition to the existing miRNAs reported by Shiah et al. (2014). Thus, this work will be of great interest to readers of various scientific disciplines, in particular, genetic and genomic scientists as well as medical scientists working on cancer.
研究基因如何共同影响复杂的人类疾病非常重要，但也极具挑战性。网络方法（例如，加权基因共表达网络分析（WGCNA））是一种强大的工具。然而，基因组数据通常包含大量批次效应，这可能会掩盖真实的基因组信号。配对设计是一种强大的工具，可以减少批次效应。然而，目前尚不清楚如何将 WGCNA 恰当地应用于配对设计的基因组数据。在本文中，我们修改了当前的 WGCNA 管道，以分析来自配对设计的高通量基因组数据。我们通过分析 Shiah 等人提供的 miRNA 数据集（2014 年）来说明修改后的 WGCNA 管道，该数据集包含四十个口腔鳞状细胞癌（OSCC）标本及其对应的非肿瘤上皮对照。OSCC 是全球第六大常见癌症。除了 Shiah 等人（2014 年）报道的现有 miRNA 之外，修改后的 WGCNA 管道还鉴定出了两组与 OSCC 相关的新 miRNA。因此，这项工作将引起各个科学领域的读者，特别是从事癌症研究的遗传和基因组科学家以及医学科学家的极大兴趣。
