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  "Title": "A Generalized Joint Location and Scale Framework for Association\nTesting",
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  "Authors@R": "c(person(given = \"Wei\",\nfamily = \"Deng\",\nrole = c(\"aut\", \"cre\"),\nemail = \"dengwq@mcmaster.ca\"),\nperson(given = \"Lei\",\nfamily = \"Sun\",\nrole = c(\"aut\"),\nemail = \"lei.sun@utoronto.ca\"))",
  "Description": "An update to the Joint Location-Scale (JLS) testing\nframework that identifies associated SNPs, gene-sets and\npathways with main and/or interaction effects on quantitative\ntraits (Soave et al., 2015; <doi:10.1016/j.ajhg.2015.05.015>).\nThe JLS method simultaneously tests the null hypothesis of\nequal mean and equal variance across genotypes, by aggregating\nassociation evidence from the individual location/mean-only and\nscale/variance-only tests using Fisher's method. The\ngeneralized joint location-scale (gJLS) framework has been\ndeveloped to deal specifically with sample correlation and\ngroup uncertainty (Soave and Sun, 2017;\n<doi:10.1111/biom.12651>). The current release: gJLS2, include\nadditional functionalities that enable analyses of X-chromosome\ngenotype data through novel methods for location (Chen et al.,\n2021; <doi:10.1002/gepi.22422>) and scale (Deng et al., 2019;\n<doi:10.1002/gepi.22247>).",
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