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Related Experiment Video

Updated: Jan 17, 2026

Infinium Assay for Large-scale SNP Genotyping Applications

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

Advances in haplotype phasing and genotype imputation.

Quan Sun^1,2, Yun Li^3,4

¹Center for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA.

Nature Reviews. Genetics

|September 24, 2025

Summary

This summary is machine-generated.

Haplotype phasing and genotype imputation are crucial for improving genome coverage in genetic studies. Researchers must carefully select tools, filters, and reference panels, with long-read sequencing promising future advancements.

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Area of Science:

Genomics
Bioinformatics
Genetic Epidemiology

Background:

Haplotype phasing and genotype imputation are essential for enhancing genome coverage in genomic analyses.
These techniques are vital for studies like genome-wide association studies (GWAS).

Purpose of the Study:

To review the current landscape of haplotype phasing and genotype imputation tools.
To highlight practical considerations for researchers utilizing these methods.
To discuss future directions, including the impact of emerging technologies.

Main Methods:

Review of existing computational tools for haplotype phasing and genotype imputation.
Discussion of practical factors influencing tool selection and application.
Analysis of the potential impact of long-read sequencing technologies.

Main Results:

Numerous tools are available for haplotype phasing and genotype imputation, with ongoing evolution.
Key considerations include tool choice, quality control, data privacy, and reference panel selection.
Long-read sequencing presents new opportunities for methodological development in this field.

Conclusions:

Effective haplotype phasing and genotype imputation are critical for maximizing genomic data utility.
Researchers must navigate several practical aspects to optimize these processes.
Technological advancements, particularly long-read sequencing, are expected to drive future innovation.