A BOOTSTRAP MODEL COMPARISON TEST FOR IDENTIFYING GENES WITH CONTEXT-SPECIFIC PATTERNS OF GENETIC REGULATION.
A BOOTSTRAP MODEL COMPARISON TEST FOR IDENTIFYING GENES WITH CONTEXT-SPECIFIC PATTERNS OF GENETIC REGULATION.
复制标题
用于识别具有特定背景遗传调控模式的基因的引导模型比较测试。
DOI：
10.1101/2023.03.06.531446
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
Pan,Wei
中科院分区：
文献类型：
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作者：
Malakhov,MykhayloM;Dai,Ben;Shen,XiaotongT;Pan,Wei
了解遗传变异如何影响基因表达对于全面了解产生复杂性状的功能途径至关重要。尽管大量研究已经证实许多基因在不同的人体组织和细胞类型中存在差异表达，但不存在用于识别表达受到差异调节的基因的工具。在这里，我们介绍 DRAB（Bootstrapping 差异调控分析），这是一种基于基因的方法，用于测试组织或其他生物环境之间的基因调控模式是否存在显着差异。 DRAB 首先利用弹性网络来学习局部遗传调控的特定上下文模型，然后应用一种新颖的基于引导程序的模型比较测试来检查它们的等效性。与之前的模型比较测试不同，我们提出的方法可以通过考虑特征选择和模型训练的可变性来确定群体水平模型是否具有相同的预测性能。我们在基因型组织表达 (GTEx) 项目中对来自多种人体组织的 mRNA 表达数据验证了 DRAB。 DRAB 产生了生物学上合理的结果，并且有足够的能力检测具有组织特异性调控特征的基因，同时有效控制假阳性。通过提供一个促进差异调控基因优先顺序的框架，我们的研究使未来能够发现分子表型的遗传结构。
Understanding how genetic variation affects gene expression is essential for a complete picture of the functional pathways that give rise to complex traits. Although numerous studies have established that many genes are differentially expressed in distinct human tissues and cell types, no tools exist for identifying the genes whose expression is differentially regulated. Here we introduce DRAB (Differential Regulation Analysis by Bootstrapping), a gene-based method for testing whether patterns of genetic regulation are significantly different between tissues or other biological contexts. DRAB first leverages the elastic net to learn context-specific models of local genetic regulation and then applies a novel bootstrap-based model comparison test to check their equivalency. Unlike previous model comparison tests, our proposed approach can determine whether population-level models have equal predictive performance by accounting for the variability of feature selection and model training. We validated DRAB on mRNA expression data from a variety of human tissues in the Genotype-Tissue Expression (GTEx) Project. DRAB yielded biologically reasonable results and had sufficient power to detect genes with tissue-specific regulatory profiles while effectively controlling false positives. By providing a framework that facilitates the prioritization of differentially regulated genes, our study enables future discoveries on the genetic architecture of molecular phenotypes.