多 SNP 中介交互联合检验。
Multi-SNP mediation intersection-union test.
机构信息
Department of Biostatistics, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Department of Genetics, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
出版信息
Bioinformatics. 2019 Nov 1;35(22):4724-4729. doi: 10.1093/bioinformatics/btz285.
SUMMARY
Tens of thousands of reproducibly identified GWAS (Genome-Wide Association Studies) variants, with the vast majority falling in non-coding regions resulting in no eventual protein products, call urgently for mechanistic interpretations. Although numerous methods exist, there are few, if any methods, for simultaneously testing the mediation effects of multiple correlated SNPs via some mediator (e.g. the expression of a gene in the neighborhood) on phenotypic outcome. We propose multi-SNP mediation intersection-union test (SMUT) to fill in this methodological gap. Our extensive simulations demonstrate the validity of SMUT as well as substantial, up to 92%, power gains over alternative methods. In addition, SMUT confirmed known mediators in a real dataset of Finns for plasma adiponectin level, which were missed by many alternative methods. We believe SMUT will become a useful tool to generate mechanistic hypotheses underlying GWAS variants, facilitating functional follow-up.
AVAILABILITY AND IMPLEMENTATION
The R package SMUT is publicly available from CRAN at https://CRAN.R-project.org/package=SMUT.
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
摘要
数以万计的可重复识别的 GWAS（全基因组关联研究）变异，绝大多数位于非编码区域，最终没有产生蛋白质产物，迫切需要进行机制解释。尽管存在许多方法，但几乎没有（如果有的话）方法可以同时通过某些中介物（例如，附近基因的表达）来测试多个相关 SNP 对表型结果的中介效应。我们提出多 SNP 中介交叉-并集检验（SMUT）来填补这一方法上的空白。我们的广泛模拟表明，SMUT 是有效的，并且与替代方法相比，具有高达 92%的强大增益。此外，SMUT 在芬兰人血浆脂联素水平的真实数据集确认了已知的中介物，而许多替代方法都错过了这些中介物。我们相信 SMUT 将成为生成 GWAS 变异背后的机制假设的有用工具，促进功能后续研究。
可用性和实现
SMUT 的 R 包可在 CRAN 上公开获得，网址为 https://CRAN.R-project.org/package=SMUT。
补充信息
补充数据可在生物信息学在线获得。
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