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GJLS2: an R package for generalized joint location and scale analysis in X-inclusive genome-wide association studies.


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.

SUBMITTER: Deng WQ 

PROVIDER: S-EPMC8982384 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

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gJLS2: an R package for generalized joint location and scale analysis in X-inclusive genome-wide association studies.

Deng Wei Q WQ   Sun Lei L  

G3 (Bethesda, Md.) 20220401 4


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  ...[more]

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