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用于在群体结构校正的全基因组关联研究中检测上位性的最近邻投影距离回归

Nearest-Neighbor Projected Distance Regression for Epistasis Detection in GWAS With Population Structure Correction.

作者信息

Arabnejad Marziyeh, Montgomery Courtney G, Gaffney Patrick M, McKinney Brett A

机构信息

Tandy School of Computer Science, University of Tulsa, Tulsa, OK, United States.

Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, United States.

出版信息

Front Genet. 2020 Jul 22;11:784. doi: 10.3389/fgene.2020.00784. eCollection 2020.

Abstract

Nearest-neighbor Projected-Distance Regression (NPDR) is a feature selection technique that uses nearest-neighbors in high dimensional data to detect complex multivariate effects including epistasis. NPDR uses a regression formalism that allows statistical significance testing and efficient control for multiple testing. In addition, the regression formalism provides a mechanism for NPDR to adjust for population structure, which we apply to a GWAS of systemic lupus erythematosus (SLE). We also test NPDR on benchmark simulated genetic variant data with epistatic effects, main effects, imbalanced data for case-control design and continuous outcomes. NPDR identifies potential interactions in an epistasis network that influences the SLE disorder.

摘要

最近邻投影距离回归(NPDR)是一种特征选择技术,它利用高维数据中的最近邻来检测包括上位性在内的复杂多变量效应。NPDR使用一种回归形式,允许进行统计显著性检验并对多重检验进行有效控制。此外,回归形式为NPDR提供了一种调整群体结构的机制,我们将其应用于系统性红斑狼疮(SLE)的全基因组关联研究(GWAS)。我们还在具有上位性效应、主效应、病例对照设计不平衡数据和连续结果的基准模拟遗传变异数据上测试了NPDR。NPDR识别出影响SLE疾病的上位性网络中的潜在相互作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cae/7387719/f3941cef898e/fgene-11-00784-g001.jpg

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