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Updated: Jun 12, 2026

Infinium Assay for Large-scale SNP Genotyping Applications

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

Genotype imputation for genome-wide association studies.

Jonathan Marchini¹, Bryan Howie

¹Department of Statistics, University of Oxford, Oxford, UK. marchini@stats.ox.ac.uk

Nature Reviews. Genetics

|June 3, 2010

Summary

Genome-wide association studies identify disease links. Genotype imputation enhances these studies by improving power and enabling meta-analysis for complex human diseases.

Area of Science:

Genetics
Bioinformatics
Statistical genomics

Background:

Genome-wide association (GWA) studies have identified numerous associations for complex human diseases.
Genotype imputation is a crucial technique in analyzing GWA data.

Purpose of the Study:

To review statistical methods for genotype imputation.
To discuss factors affecting imputation performance.
To cover methods for assessing imputation quality and association testing.

Main Methods:

Description of various statistical genotype imputation methods.
Analysis of factors influencing imputation accuracy and performance.
Review of quality control and association testing strategies for imputed data.

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Published on: June 21, 2018

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Infinium Assay for Large-scale SNP Genotyping Applications

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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Main Results:

Imputation significantly boosts statistical power in GWA studies.
It facilitates fine-mapping of disease-associated regions.
Enables robust meta-analysis across diverse GWA datasets.

Conclusions:

Genotype imputation is essential for maximizing the utility of GWA studies.
Understanding imputation performance is key to reliable genetic association findings.
Accurate imputation supports the discovery of genetic variants underlying complex diseases.