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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
Published on: June 21, 2018
Rapid testing of SNPs and gene-environment interactions in case-parent trio data based on exact analytic parameter
Holger Schwender1, Margaret A Taub, Terri H Beaty
1TU Dortmund University, 44221 Dortmund, Germany. holger.schwender@udo.edu
Biometrics
|December 14, 2011
Summary
This study introduces faster methods for analyzing single nucleotide polymorphisms (SNPs) in disease association studies using case-parent trios. These new analytic approaches significantly reduce computation time for genetic analysis, enabling quicker identification of disease-related genetic markers.
Area of Science:
- Genetics
- Statistical Genetics
- Bioinformatics
Background:
- Case-parent trio studies analyze genetic transmission of disease-associated alleles.
- The genotypic transmission/disequilibrium test (gTDT) is a common statistical method for this analysis.
- gTDT typically relies on iterative procedures for model fitting.
Purpose of the Study:
- To derive exact closed-form solutions for parameter estimates in gTDT.
- To develop efficient methods for testing SNP effects and gene-environment interactions.
- To propose a fast computation procedure for the MAX gTDT statistic and its p-value.
Main Methods:
- Derivation of analytic solutions for conditional logistic regression models.
- Development of MAX gTDT statistic for unknown genetic models.
- Implementation of fast permutation-based p-value computation.
Main Results:
- Analytic parameter estimates were derived for additive, dominant, and recessive SNP effects.
- Analytic estimates were also found for gene-environment interactions.
- The proposed MAX gTDT procedure significantly reduced computation time for whole-genome scans.
Conclusions:
- New analytic methods offer substantial computational advantages over iterative approaches.
- These methods enable rapid analysis of large SNP datasets in genetic association studies.
- The findings facilitate faster identification of SNPs associated with diseases like cleft.
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