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Infinium Assay for Large-scale SNP Genotyping Applications
Published on: November 19, 2013
Genotype imputation in genome-wide association studies.
Eleonora Porcu1, Serena Sanna, Christian Fuchsberger
1Department of Biostatistics, Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, Michigan, USA.
Current Protocols in Human Genetics
|July 16, 2013
Summary
Genotype imputation, a computational method, enhances genetic association studies by filling in missing data and harmonizing datasets. This approach, using reference panels like the 1000 Genomes Project, improves statistical power for genetic discovery.
Area of Science:
- Genetics
- Bioinformatics
- Statistical Genetics
Background:
- Genotype imputation is crucial for increasing the statistical power of genetic association studies.
- Missing genotype data and the need for harmonized datasets for meta-analyses present significant challenges in genetic research.
- Accurate imputation is essential for maximizing the utility of genomic data.
Purpose of the Study:
- To provide an introductory overview of genotype imputation methods.
- To describe a practical two-step imputation approach involving genotype phasing and reference panel imputation.
- To guide researchers on data preparation, quality control, and optimizing imputation using high-density reference panels.
Main Methods:
- A two-step imputation strategy: first, phasing study genotypes, then imputing reference panel genotypes into study haplotypes.
- Utilizing high-density reference panels, such as the 1000 Genomes Project (over 39 million variants).
- Demonstrating data preparation, quality control, and running imputation with detailed computational steps.
Main Results:
- The study illustrates the application of a computationally intensive two-step imputation process.
- The influence of key factors like reference panel selection, marker density, and imputation settings on imputation quality is demonstrated.
- Insights into critical aspects for successful genotype imputation are provided using simulated data.
Conclusions:
- Genotype imputation is a powerful in silico tool for enhancing genetic association studies.
- The described two-step method, coupled with large reference panels, offers a robust approach to imputation.
- Understanding the impact of various parameters is key to achieving high-quality imputation results and advancing genetic discovery.
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