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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
Published on: June 21, 2018
Effect of genotyping error in model-free linkage analysis using microsatellite or single-nucleotide polymorphism
Cheryl L Thompson1, Dan Baechle, Qing Lu
1Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA. clw8@cwru.edu
BMC Genetics
|February 3, 2006
Summary
Genotyping errors impact linkage analysis differently for single-nucleotide polymorphism (SNP) and microsatellite (MS) maps. SNP maps may be more affected, but accounting for errors can restore lost linkage detection power.
Area of Science:
- Genetics
- Bioinformatics
- Statistical Genetics
Background:
- Genotyping errors are common in genetic studies and can reduce the power of linkage detection.
- The impact of genotyping errors on linkage analysis may differ between single-nucleotide polymorphism (SNP) and microsatellite (MS) marker maps.
Purpose of the Study:
- To compare the impact of genotyping errors on linkage results for SNP and MS marker maps.
- To evaluate the effect of genotyping error rates on linkage detection power and type I error rates.
- To assess the utility of methods for accounting for genotyping errors in SNP data.
Main Methods:
- Detection of Mendelian-consistent genotyping errors using multipoint identity-by-descent sharing.
- Simulation of nuclear families with varying genotyping error rates (0%, 0.14%, 2.8%).
- Evaluation of linkage detection power and type I error rates for SNP and MS maps under different error scenarios.
- Application of a likelihood-based approach to account for genotyping errors in SNP data.
Main Results:
- A small fraction of Mendelian-consistent errors were detectable (18% for MS, 2.4% for SNP).
- SNP genotyping errors were more frequently Mendelian-consistent than MS errors, suggesting a potentially greater impact on SNP maps.
- In simulated data with genotyping errors, SNP maps showed higher power (75%) than MS maps (67%) but also slightly more false positives.
- Accounting for genotyping errors in SNP data using a likelihood-based method partially restored lost linkage detection power.
Conclusions:
- Genotyping errors can have a differential impact on linkage analysis depending on the marker type (SNP vs. MS).
- While SNP maps may be more susceptible to certain types of genotyping errors, they can offer higher power for linkage detection, especially when errors are accounted for.
- Methods to correct for genotyping errors are valuable for improving the reliability of linkage analysis, particularly with SNP data.
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