Impact of Missing Data on Genetic Tests
Author Information
Author(s): Guo Chao-Yu, Cui Jing, Cupples L Adrienne
Primary Institution: Boston University
Hypothesis
How does non-ignorable missingness affect genetic tests of linkage and association using case-parent trios?
Conclusion
The EM-HRR test is more powerful than the 1-TDT when parental genotypes are missing randomly, despite the impact of non-ignorable missingness.
Supporting Evidence
- The study found that the type I error of tests using incomplete trios was not inflated under either recessive or dominant disease models.
- The power of the tests was found to be inflated due to an excess of heterozygous parents in dyads.
- The EM-HRR test outperformed the 1-TDT under conditions of non-ignorable missingness.
Takeaway
This study looks at how missing information from parents can change the results of genetic tests, and it finds a better way to handle that missing data.
Methodology
The study used computer simulations with unrelated case-parent trios to examine the effects of non-ignorable missingness on genetic tests.
Potential Biases
Potential bias due to the non-random nature of missing parental genotypes.
Limitations
The results may not generalize to populations with different missingness patterns or to tests not examined in this study.
Participant Demographics
Simulated data from the Danacaa population.
Digital Object Identifier (DOI)
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