| Literature DB >> 35201341 |
Wei Q Deng1,2, Lei Sun3,4.
Abstract
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.Entities:
Keywords: PLINK; R; X-chromosome association; gene–environment interactions; joint location and scale; variance heterogeneity
Mesh:
Year: 2022 PMID: 35201341 PMCID: PMC8982384 DOI: 10.1093/g3journal/jkac049
Source DB: PubMed Journal: G3 (Bethesda) ISSN: 2160-1836 Impact factor: 3.154