<?xml version="1.0" encoding="UTF-8"?>
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Cauchy Weighted Joint Test for Pharmacogenetics Analysis</dc:title>
  <dc:title>R package cwot version 0.1.0</dc:title>
  <dc:description>A flexible and robust joint test of the single nucleotide polymorphism (SNP) main effect and genotype-by-treatment interaction effect for continuous and binary endpoints. Two analytic procedures, Cauchy weighted joint test (CWOT) and adaptively weighted joint test (AWOT), are proposed to accurately calculate the joint test p-value. The proposed methods are evaluated through extensive simulations under various scenarios. The results show that the proposed AWOT and CWOT control type I error well and outperform existing methods in detecting the most interesting signal patterns in pharmacogenetics (PGx) association studies. For reference, see Hong Zhang, Devan Mehrotra and Judong Shen (2022) &lt;doi:10.13140/RG.2.2.28323.53280&gt;.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Imports: stats, SPAtest, mvtnorm</dc:relation>
  <dc:creator>Hong Zhang &lt;hzhang@wpi.edu&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Hong Zhang [aut, cre] (ORCID: &lt;https://orcid.org/0000-0002-8869-8671&gt;)</dc:contributor>
  <dc:rights>GPL-2</dc:rights>
  <dc:date>2022-09-23</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=cwot</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.cwot</dc:identifier>
</oai_dc:dc>
