Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON L8P 3R2, Canada.
Peter Boris Centre for Addictions Research, St. Joseph's Healthcare Hamilton, McMaster University, Hamilton, ON L8P 3R2, Canada.
G3 (Bethesda). 2022 Apr 4;12(4). doi: 10.1093/g3journal/jkac049.
A joint analysis of location and scale can be a powerful tool in genome-wide association studies to uncover previously overlooked markers that influence a quantitative trait through both mean and variance, as well as to prioritize candidates for gene-environment interactions. This approach has recently been generalized to handle related samples, dosage data, and the analytically challenging X-chromosome. We disseminate the latest advances in methodology through a user-friendly R software package with added functionalities to support genome-wide analysis on individual-level or summary-level data. The implemented R package can be called from PLINK or directly in a scripting environment, to enable a streamlined genome-wide analysis for biobank-scale data. Application results on individual-level and summary-level data highlight the advantage of the joint test to discover more genome-wide signals as compared to a location or scale test alone. We hope the availability of gJLS2 software package will encourage more scale and/or joint analyses in large-scale datasets, and promote the standardized reporting of their P-values to be shared with the scientific community.
联合分析位置和规模可以成为全基因组关联研究中的有力工具，用于发现以前被忽视的通过平均值和方差影响数量性状的标记，以及为基因-环境相互作用的候选者确定优先级。这种方法最近已经被推广到处理相关样本、剂量数据和分析上具有挑战性的 X 染色体。我们通过一个用户友好的 R 软件包传播最新的方法学进展，该软件包具有额外的功能，可支持个体水平或汇总水平数据的全基因组分析。实现的 R 包可以从 PLINK 调用，也可以直接在脚本环境中调用，从而能够对生物库规模的数据进行简化的全基因组分析。个体水平和汇总水平数据的应用结果突出了联合检验相对于位置或规模检验的优势，可发现更多全基因组信号。我们希望 gJLS2 软件包的可用性将鼓励在大型数据集上进行更多的规模和/或联合分析，并促进标准化报告其 P 值，以便与科学界共享。
