Meta-analytic framework for liquid association
Meta-analytic framework for liquid association
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DOI：
10.1093/bioinformatics/btx138
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发表时间：
2017-07-15
期刊：
影响因子：
5.8
通讯作者：
Tseng, George C.
中科院分区：
文献类型：
--
作者：
Wang, Lin;Liu, Silvia;Tseng, George C.
动机：虽然通过成对表达相关性的共表达分析被广泛用于在全基因组尺度上阐明基因-基因相互作用，但许多复杂的多基因调控需要更先进的检测方法。液体关联（LA）是一个强大的工具来检测两个基因变量的动态相关性取决于第三个变量（LA侦察基因）的表达水平。然而，由于队列偏倚、生物学变异和有限的样本量，单次转录组学研究的LA检测通常不稳定且不可推广。随着微阵列和NGS技术的快速发展，LA分析结合多种基因表达研究可以提供更准确和稳定的结果。结果：在本文中，我们提出了两种LA分析的荟萃分析方法（MetaLA和MetaMLA），以结合联合收割机多种转录组学研究。为了弥补计算量大的缺点，我们还提出了一种两步快速筛选算法：自举滤波和符号滤波。我们将该方法应用于五个酿酒酵母数据集与环境变化。快速筛选算法减少了98%的运行时间。与单一研究分析相比，MetaLA和MetaMLA提供了更强的检测信号和更一致和稳定的结果。最上面的三胞胎在与环境变化有关的基本生物过程中高度富集。我们的方法可以帮助生物学家了解不同环境暴露或疾病状态下的潜在调控机制。
Motivation: Although coexpression analysis via pair-wise expression correlation is popularly used to elucidate gene-gene interactions at the whole-genome scale, many complicated multi-gene regulations require more advanced detection methods. Liquid association (LA) is a powerful tool to detect the dynamic correlation of two gene variables depending on the expression level of a third variable (LA scouting gene). LA detection from single transcriptomic study, however, is often unstable and not generalizable due to cohort bias, biological variation and limited sample size. With the rapid development of microarray and NGS technology, LA analysis combining multiple gene expression studies can provide more accurate and stable results.Results: In this article, we proposed two meta-analytic approaches for LA analysis (MetaLA and MetaMLA) to combine multiple transcriptomic studies. To compensate demanding computing, we also proposed a two-step fast screening algorithm for more efficient genome-wide screening: boot-strap filtering and sign filtering. We applied the methods to five Saccharomyces cerevisiae datasets related to environmental changes. The fast screening algorithm reduced 98% of running time. When compared with single study analysis, MetaLA and MetaMLA provided stronger detection signal and more consistent and stable results. The top triplets are highly enriched in fundamental biological processes related to environmental changes. Our method can help biologists understand underlying regulatory mechanisms under different environmental exposure or disease states.