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DNA Microarrays

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...

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Updated: May 31, 2026

Infinium Assay for Large-scale SNP Genotyping Applications

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

A review of software for microarray genotyping.

Philippe Lamy¹, Jakob Grove, Carsten Wiuf

¹Bioinformatics Research Centre, Aarhus C, Denmark.

|June 30, 2011

Summary

This summary is machine-generated.

This review covers software for single nucleotide polymorphism (SNP) genotyping on microarray platforms, focusing on Affymetrix and Illumina arrays. It examines various statistical approaches used in genotyping algorithms and how new arrays drive algorithm updates.

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Last Updated: May 31, 2026

Infinium Assay for Large-scale SNP Genotyping Applications

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning

DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning

Published on: March 15, 2011

qPCRTag Analysis - A High Throughput, Real Time PCR Assay for Sc2.0 Genotyping

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Published on: May 25, 2015

Area of Science:

Genetics and Bioinformatics
Computational Biology

Background:

Microarray technology enables high-throughput genotyping of single nucleotide polymorphisms (SNPs).
Accurate SNP genotyping is crucial for genetic research, disease association studies, and personalized medicine.

Purpose of the Study:

To review and compare software tools for SNP genotyping on major microarray platforms.
To discuss the statistical methodologies underpinning different genotyping algorithms.
To highlight the relationship between new array releases and algorithm development.

Main Methods:

Literature review of genotyping software for Affymetrix and Illumina platforms.
Analysis of statistical principles employed in genotyping algorithms (e.g., likelihood, Bayesian).
Examination of algorithm design choices (e.g., single vs. all-array analysis).

Main Results:

A variety of genotyping algorithms exist, employing diverse statistical models.
Software development is closely tied to the release cycles of new microarray arrays.
Different algorithms offer varying performance characteristics depending on the data and statistical approach.

Conclusions:

The choice of genotyping software depends on the specific microarray platform and research question.
Continued innovation in statistical methods is essential for improving genotyping accuracy.
The field requires robust evaluation of genotyping algorithms to guide tool selection.