Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

DNA Microarrays02:34

DNA Microarrays

21.9K
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...
21.9K

You might also read

Related Articles

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

Sort by
Same author

First-Line Enfortumab Vedotin Plus Pembrolizumab vs Gemcitabine Plus Cisplatin for Metastatic Urothelial Carcinoma.

JAMA network open·2026
Same author

Comparative analysis of genitourinary toxicity following bladder outlet obstruction procedures in patients before versus after radiotherapy for localized prostate cancer: a retrospective cohort study using the TriNetX database.

Prostate cancer and prostatic diseases·2026
Same author

Associations between erectile dysfunction, low testosterone, and cardiometabolic risk: an age stratified, propensity-matched cohort study.

International journal of impotence research·2026
Same author

A Supervised, Online, Home-Based Eccentric Resistance Exercise Program for Patients With Metabolic Dysfunction-Associated Steatotic Liver Disease.

Gastroenterology research·2026
Same author

Haemochromatosis - a modern clinician's guide.

Internal medicine journal·2026
Same author

Addition of immune checkpoint inhibitors to intravesical BCG for high-risk BCG-naïve non-muscle invasive bladder cancer: Systematic review and meta-analysis.

BJUI compass·2026

Related Experiment Video

Updated: Mar 15, 2026

Perturbations of Circulating miRNAs in Irritable Bowel Syndrome Detected Using a Multiplexed High-throughput Gene Expression Platform
10:37

Perturbations of Circulating miRNAs in Irritable Bowel Syndrome Detected Using a Multiplexed High-throughput Gene Expression Platform

Published on: November 30, 2016

8.7K

Evaluation of Different Normalization and Analysis Procedures for Illumina Gene Expression Microarray Data Involving

Daniel M Johnstone1,2,3,4, Carlos Riveros5,6, Moones Heidari7

  • 1Centre for Bioinformatics, Biomarker Discovery and Information-Based Medicine, The University of Newcastle, Callaghan, NSW 2308, Australia. daniel.johnstone@sydney.edu.au.

Microarrays (Basel, Switzerland)
|September 9, 2016
PubMed
Summary

Different analysis methods significantly alter gene expression results from Illumina microarrays, especially for small changes. Choosing the right normalization and analysis strategy is crucial to avoid missing biological insights.

Keywords:
Illuminagene expression microarraynormalization

More Related Videos

Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform
13:14

Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform

Published on: August 10, 2009

12.3K
Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples
07:30

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Published on: June 8, 2020

12.9K

Related Experiment Videos

Last Updated: Mar 15, 2026

Perturbations of Circulating miRNAs in Irritable Bowel Syndrome Detected Using a Multiplexed High-throughput Gene Expression Platform
10:37

Perturbations of Circulating miRNAs in Irritable Bowel Syndrome Detected Using a Multiplexed High-throughput Gene Expression Platform

Published on: November 30, 2016

8.7K
Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform
13:14

Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform

Published on: August 10, 2009

12.3K
Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples
07:30

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Published on: June 8, 2020

12.9K

Area of Science:

  • Genomics
  • Bioinformatics
  • Gene Expression Analysis

Background:

  • Illumina microarrays are valuable for detecting subtle gene expression shifts due to high technical reproducibility.
  • Limited understanding exists on how varying normalization and differential expression analysis strategies impact microarray study outcomes.
  • The influence of analytical choices is particularly critical for datasets with modest expression variations.

Purpose of the Study:

  • To evaluate the concordance of gene lists derived from different normalization and analysis strategies on Illumina microarray data.
  • To assess the impact of these analytical variations on downstream pathway analysis results.
  • To provide guidelines for optimizing outcomes in analyzing Illumina datasets with small expression changes.

Main Methods:

  • Applied various combinations of normalization strategies and analytical approaches to two Illumina microarray datasets exhibiting modest expression changes.
  • Included traditional statistical methods and an approach based on combinatorial optimization.
  • Assessed concordance across generated gene lists and evaluated subsequent pathway analysis outcomes.

Main Results:

  • Significant differences in gene lists and pathway analysis results were observed based on the chosen normalization strategy and analytical approach.
  • The selection of analytical methods considerably affected study outcomes, highlighting potential for substantial variations in biological interpretation.
  • Analytical artifacts can obscure true biological variation, especially in datasets with small fold changes if normalization is inadequate.

Conclusions:

  • Routine use of a single analytical approach for all microarray datasets may lead to overlooking important biological phenomena.
  • Careful selection and validation of normalization and differential expression analysis strategies are essential for accurate interpretation of Illumina microarray data.
  • Guidelines are provided to optimize outcomes when analyzing Illumina datasets, particularly those with small expression changes.