Wang Nating, Chu Tinyi, Luo Jiangtao, Wu Rongling, Wang Zhong
College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China.
Graduate field of Computational Biology, Cornell University, Ithaca, NY, United States of America.
PeerJ. 2019 May 31;7:e7008. doi: 10.7717/peerj.7008. eCollection 2019.
Quantitative trait locus (QTL) mapping has been used as a powerful tool for inferring the complexity of the genetic architecture that underlies phenotypic traits. This approach has shown its unique power to map the developmental genetic architecture of complex traits by implementing longitudinal data analysis. Here, we introduce the R package based on the functional mapping framework, which integrates prior biological knowledge into the statistical model. Specifically, the functional mapping framework is engineered to include longitudinal curves that describe the genetic effects and the covariance matrix of the trait of interest. chooses the type of longitudinal curve and covariance matrix automatically using information criteria. is available for download at https://github.com/wzhy2000/Funmap2.
数量性状基因座(QTL)定位已成为推断表型性状潜在遗传结构复杂性的有力工具。通过实施纵向数据分析,这种方法已显示出其在绘制复杂性状发育遗传结构方面的独特能力。在此,我们介绍基于功能定位框架的R包,该框架将先前的生物学知识整合到统计模型中。具体而言,功能定位框架设计为包含描述感兴趣性状的遗传效应和协方差矩阵的纵向曲线。它使用信息准则自动选择纵向曲线和协方差矩阵的类型。可在https://github.com/wzhy2000/Funmap2下载。