Scholarlink

<p>Functional regression-based method (FRM) is an efficient and powerful tool for identifying genetic variants associated with complex traits and diseases by jointly considering the effects of multiple variants within a gene, however, no accessible software has been developed to realize the methods in practice. In this paper, we introduce the <i>FixFRM</i> R package that implements FRMs for gene-based tests. It provides a unified framework for quantitative and dichotomous trait analysis with various options for genetic variant and effect estimation. We use the package to identify gene that significantly associated withasthma using data from SNPassoc R package and compare to SKAT and SKAT-O. We further showcase an innovative application of FRMs to mixture exposure analysis using National Health and Nutrition Examination Survey data, modeling the joint effects of multiple environmental exposures by treating exposure levels as “genetic variants”. FRM achieves acceptable performance in the simulation study and obtains similar <i>p</i>-value as weighted quantile sum regression does in real application. The <i>FixFRM</i> package bridges the gap between the theoretical advantages and practical implementation for gene-based tests and mixture exposure analysis. Its user-friendly interface and comprehensive options facilitate powerful screening of genetic and environmental effects on complex traits.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Introduction of FixFRM package for gene-based association test and its innovative application to mixture exposure analysis

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年9月26日

查看全文
  • Xin Peng,
  • Haixin Feng,
  • Renhuizi Wei,
  • Wenqian Ruan,
  • Jun Wu,
  • Chulan Ou,
  • Zhongxin Zhu,
  • Linxi He,
  • Bingsong Zhang

摘要

Functional regression-based method (FRM) is an efficient and powerful tool for identifying genetic variants associated with complex traits and diseases by jointly considering the effects of multiple variants within a gene, however, no accessible software has been developed to realize the methods in practice. In this paper, we introduce the FixFRM R package that implements FRMs for gene-based tests. It provides a unified framework for quantitative and dichotomous trait analysis with various options for genetic variant and effect estimation. We use the package to identify gene that significantly associated withasthma using data from SNPassoc R package and compare to SKAT and SKAT-O. We further showcase an innovative application of FRMs to mixture exposure analysis using National Health and Nutrition Examination Survey data, modeling the joint effects of multiple environmental exposures by treating exposure levels as “genetic variants”. FRM achieves acceptable performance in the simulation study and obtains similar p-value as weighted quantile sum regression does in real application. The FixFRM package bridges the gap between the theoretical advantages and practical implementation for gene-based tests and mixture exposure analysis. Its user-friendly interface and comprehensive options facilitate powerful screening of genetic and environmental effects on complex traits.