TY - JOUR
T1 - A nonparametric alternative to the Cochran-Armitage trend test in genetic case-control association studies
T2 - The Jonckheere-Terpstra trend test
AU - Manning, Sydney E.
AU - Ku, Hung Chih
AU - Dluzen, Douglas F.
AU - Xing, Chao
AU - Zhou, Zhengyang
N1 - Funding Information:
This work is supported by the National Institute of Environmental Health Sciences grant R03ES034138 to C.X. and Z.Z. D.F.D. and Z.Z. are also supported in part by the National Institute on Minority Health and Health Disparities grant 5U54MD013376-8281. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. There was no additional external funding received for this study. The authors acknowledge the Texas Advanced Computing Center (https://www.tacc.utexas. edu) at The University of Texas at Austin for providing high performance computing resources that have contributed to the research results reported within this paper.
Publisher Copyright:
© 2023 Manning et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2023/2
Y1 - 2023/2
N2 - Identifications of novel genetic signals conferring susceptibility to human complex diseases is pivotal to the disease diagnosis, prevention, and treatment. Genetic association study is a powerful tool to discover candidate genetic signals that contribute to diseases, through statistical tests for correlation between the disease status and genetic variations in study samples. In such studies with a case-control design, a standard practice is to perform the Cochran-Armitage (CA) trend test under an additive genetic model, which suffers from power loss when the model assumption is wrong. The Jonckheere-Terpstra (JT) trend test is an alternative method to evaluate association in a nonparametric way. This study compares the power of the JT trend test and the CA trend test in various scenarios, including different sample sizes (200–2000), minor allele frequencies (0.05–0.4), and underlying modes of inheritance (dominant genetic model to recessive genetic model). By simulation and real data analysis, it is shown that in general the JT trend test has higher, similar, and lower power than the CA trend test when the underlying mode of inheritance is dominant, additive, and recessive, respectively; when the sample size is small and the minor allele frequency is low, the JT trend test outperforms the CA trend test across the spectrum of genetic models. In sum, the JT trend test is a valuable alternative to the CA trend test under certain circumstances with higher statistical power, which could lead to better detection of genetic signals to human diseases and finer dissection of their genetic architecture.
AB - Identifications of novel genetic signals conferring susceptibility to human complex diseases is pivotal to the disease diagnosis, prevention, and treatment. Genetic association study is a powerful tool to discover candidate genetic signals that contribute to diseases, through statistical tests for correlation between the disease status and genetic variations in study samples. In such studies with a case-control design, a standard practice is to perform the Cochran-Armitage (CA) trend test under an additive genetic model, which suffers from power loss when the model assumption is wrong. The Jonckheere-Terpstra (JT) trend test is an alternative method to evaluate association in a nonparametric way. This study compares the power of the JT trend test and the CA trend test in various scenarios, including different sample sizes (200–2000), minor allele frequencies (0.05–0.4), and underlying modes of inheritance (dominant genetic model to recessive genetic model). By simulation and real data analysis, it is shown that in general the JT trend test has higher, similar, and lower power than the CA trend test when the underlying mode of inheritance is dominant, additive, and recessive, respectively; when the sample size is small and the minor allele frequency is low, the JT trend test outperforms the CA trend test across the spectrum of genetic models. In sum, the JT trend test is a valuable alternative to the CA trend test under certain circumstances with higher statistical power, which could lead to better detection of genetic signals to human diseases and finer dissection of their genetic architecture.
UR - http://www.scopus.com/inward/record.url?scp=85147318862&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0280809
DO - 10.1371/journal.pone.0280809
M3 - Article
C2 - 36730335
AN - SCOPUS:85147318862
SN - 1932-6203
VL - 18
JO - PLoS ONE
JF - PLoS ONE
IS - 2 February
M1 - e0280809
ER -