Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

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...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

A BODIPY-based turn-on fluorescent probe for the selective detection of hydrogen sulfide in solution and in cells.

Talanta·2015

Same author

Analysis of sagittal balance using spinopelvic parameters in ankylosing spondylitis patients treated with vertebral column decancellation surgery.

Acta orthopaedica Belgica·2015

Same author

Using a 3D Culture System to Differentiate Visceral Adipocytes In Vitro.

Endocrinology·2015

Same author

Noncontact Monitoring of Blood Oxygen Saturation Using Camera and Dual-Wavelength Imaging System.

IEEE transactions on bio-medical engineering·2015

Same author

Digital human modeling and its applications: Review and future prospects.

Journal of X-ray science and technology·2015

Same author

Capture-based high-coverage NGS: a powerful tool to uncover a wide spectrum of mutation types.

Genetics in medicine : official journal of the American College of Medical Genetics·2015

Same journal

Draft Genome Sequence of Multidrug-Resistant <i>Acinetobacter baumannii</i> smu isolated from a Bloodstream Infection in Sikkim, India.

Journal of genomics·2026

Same journal

Draft Genomes of Geographically Distinct Strains and Progeny of the Ectomycorrhizal Basidiomycete <i>Laccaria bicolor</i>.

Journal of genomics·2026

Same journal

<i>De Novo</i> Genome Assembly of the Myanmar Puddle Frog, <i>Phrynoglossus myanhessei</i> (Anura: Dicroglossidae).

Journal of genomics·2026

Same journal

Whole genome Shotgun Sequence of <i>Anopheles stephensi,</i> The Host of Malaria parasite, <i>Plasmodium</i> sp.

Journal of genomics·2025

Same journal

Whole-Genome Shotgun Sequencing and Assembly of <i>Anopheles gambiae G3</i>, the Host of Malaria Parasite <i>Plasmodium sp</i>.

Journal of genomics·2025

Same journal

Identification of Splicing Variation Associated with Parental Behavior in the Burying Beetles (<i>Nicrophorus orbicollis</i>).

Journal of genomics·2025

See all related articles

Search research articles

Related Experiment Video

Updated: Sep 30, 2025

DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning

DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning

Published on: March 15, 2011

GTQC: Automated Genotyping Array Quality Control and Report.

Shilin Zhao¹, Limin Jiang², Hui Yu²

¹Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN.

Journal of Genomics

|March 18, 2022

Summary

This summary is machine-generated.

Genotyping array quality control is streamlined by the new R package GTQC (GenoTyping Quality Control). This tool automates data inspection, reducing manual effort and improving efficiency for genetic association studies.

Keywords:

genotyping microarray quality control

More Related Videos

Infinium Assay for Large-scale SNP Genotyping Applications

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

Array Comparative Genomic Hybridization Array CGH for Detection of Genomic Copy Number Variants

Array Comparative Genomic Hybridization Array CGH for Detection of Genomic Copy Number Variants

Published on: February 21, 2015

Related Experiment Videos

Last Updated: Sep 30, 2025

DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning

DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning

Published on: March 15, 2011

Infinium Assay for Large-scale SNP Genotyping Applications

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

Array Comparative Genomic Hybridization Array CGH for Detection of Genomic Copy Number Variants

Array Comparative Genomic Hybridization Array CGH for Detection of Genomic Copy Number Variants

Published on: February 21, 2015

Area of Science:

Genomics
Bioinformatics
Statistical Genetics

Background:

Genotyping arrays are cost-effective for large-scale genome-wide genetic association studies (GWAS).
Rigorous quality control (QC) is essential for reliable genotyping data and robust study outcomes.
Current QC processes for genotyping arrays are labor-intensive and require significant manual intervention.

Purpose of the Study:

To develop an automated solution for genotyping array quality control.
To reduce manual labor and improve the efficiency of QC procedures.
To provide a comprehensive tool for inspecting genotype data quality.

Main Methods:

Development of an R package named GTQC (GenoTyping Quality Control).
Implementation of established QC protocols and strategies into an automated workflow.
Generation of a detailed HTML report with tables and figures summarizing QC metrics.

Main Results:

GTQC automates a majority of the quality control steps for general array genotyping data.
The package covers a wide range of genotype data quality metrics.
An HTML report is generated, facilitating swift and rigorous data quality inspection.

Conclusions:

GTQC significantly streamlines genotyping quality control, saving time and resources.
The R package enables efficient and robust data quality assessment for downstream GWAS.
Automation of QC procedures minimizes manual effort and optimizes resource allocation.