scholarly journals Genetic association studies: Design, analysis and interpretation

2002 ◽  
Vol 3 (2) ◽  
pp. 146-153 ◽  
Author(s):  
Cathryn M. Lewis
Keyword(s):  
Genetic Association ◽  
Transmission Disequilibrium Test ◽  
Population Stratification ◽  
Genetic Model ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Case Control ◽  
Case Control Studies ◽  
Transmission Disequilibrium ◽  
Family Based

Abstract This paper provides a review of the design and analysis of genetic association studies. In case control studies, the different contingency tables and their relationships to the underlying genetic model are defined. Population stratification is discussed, with suggested methods to identify and correct for the effect. The transmission disequilibrium test is provided as an alternative family-based test, which is robust to population stratification. The relative benefits of each analysis are summarised.

scholarly journals FRACTAL CHARACTERIZATIONS OF MAX STATISTICAL DISTRIBUTION IN GENETIC ASSOCIATION STUDIES

2009 ◽  
Vol 12 (04n05) ◽  
pp. 513-531 ◽  
Author(s):  
WENTIAN LI ◽  
YANING YANG
Keyword(s):  
Genetic Association ◽  
Degrees Of Freedom ◽  
Association Studies ◽  
Disease Model ◽  
Null Distribution ◽  
Genetic Association Studies ◽  
Case Control ◽  
Case Control Studies ◽  
Chi Square ◽  
Two Parameters

Two noninteger parameters are defined for MAX statistics, which are maxima of d simpler test statistics. The first parameter, d MAX , is the fractional number of tests, representing the equivalent numbers of independent tests in MAX. If the d tests are dependent, d MAX < d. The second parameter is the fractional degrees of freedom k of the chi-square distribution [Formula: see text] that fits the MAX null distribution. These two parameters, d MAX and k, can be independently defined, and k can be noninteger even if d MAX is an integer. We illustrate these two parameters using the examples of MAX2 and MAX3 statistics in genetic case-control studies. We speculate that k is related to the amount of ambiguity of the model inferred by the test. In the case-control genetic association, tests with low k (e.g. k = 1) are able to provide definitive information about the disease model, as versus tests with high k (e.g. k = 2) that are completely uncertain about the disease model. Similar to Heisenberg's uncertain principle, the ability to infer disease model and the ability to detect significant association may not be simultaneously optimized, and k seems to measure the level of their balance.

scholarly journals Benchmarking statistical methods for analyzing parent-child dyads in genetic association studies

2021 ◽  
Author(s):  
Debashree Ray ◽  
Candelaria I Vergara ◽  
Margaret I Taub ◽  
Genevieve L Wojcik ◽  
Christine Ladd-Acosta ◽  
...  
Keyword(s):  
Genetic Association ◽  
Statistical Methods ◽  
Population Stratification ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Type I ◽  
Simulation Experiments ◽  
Case Mother ◽  
Family Based ◽  
Parent Child

Genetic association studies of child health outcomes often employ family-based designs. One of the most popular family-based designs is the case-parent trio design that considers the smallest possible nuclear family consisting of two parents and their affected child. This trio design is particularly advantageous for studying relatively rare disorders because it is less prone to type 1 error inflation due to population stratification compared to population-based study designs (e.g., case-control studies). However, obtaining genetic data from both parents is difficult, from a practical perspective, and many large studies predominantly measure genetic variants in mother-child dyads. While some statistical methods for analyzing parent-child dyad data (most commonly involving mother-child pairs) exist, it is not clear if they provide the same advantage as trio methods in protecting against population stratification, or if a specific dyad design (e.g., case-mother dyads vs. case-mother/control-mother dyads) is more advantageous. In this article, we review existing statistical methods for analyzing genome-wide data on dyads and perform extensive simulation experiments to benchmark their type I errors and statistical power under different scenarios. We extend our evaluation to existing methods for analyzing a combination of case-parent trios and dyads together. We apply these methods on genotyped and imputed data from multi-ethnic mother-child pairs only, case-parent trios only or combinations of both dyads and trios from the Gene, Environment Association Studies consortium (GENEVA), where each family was ascertained through a child affected by nonsyndromic cleft lip with or without cleft palate. Results from the GENEVA study corroborate the findings from our simulation experiments. Finally, we provide recommendations for using statistical genetic association methods for dyads.

scholarly journals An alternative experimental case–control design for genetic association studies on bovine mastitis

animal ◽  
2017 ◽  
Vol 11 (4) ◽  
pp. 574-579 ◽  
Author(s):  
S. Biffani ◽  
M. Del Corvo ◽  
R. Capoferri ◽  
A. Pedretti ◽  
M. Luini ◽  
...  
Keyword(s):  
Genetic Association ◽  
Association Studies ◽  
Bovine Mastitis ◽  
Genetic Association Studies ◽  
Control Design ◽  
Case Control

Population stratification confounds genetic association studies among Latinos

2005 ◽  
Vol 118 (5) ◽  
pp. 652-664 ◽  
Author(s):  
Shweta Choudhry ◽  
Natasha E. Coyle ◽  
Hua Tang ◽  
Keyan Salari ◽  
Denise Lind ◽  
...  
Keyword(s):  
Genetic Association ◽  
Population Stratification ◽  
Association Studies ◽  
Genetic Association Studies
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