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

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...
Chi-square Analysis02:46

Chi-square Analysis

The chi-square test is a statistical hypothesis test. It is used to check whether there is a significant difference between an expected value and an observed value. In the context of genetics, it enables us to either accept or reject a hypothesis, based on how much the observed values deviate from the expected values.
The chi-square test was developed by Pearson in 1990.
The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...

You might also read

Related Articles

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

Sort by
Same author

Analysis of longitudinal zero-inflated count data using overall marginalized hurdle models.

Statistical methods in medical research·2026
Same author

Leveraging Innovative Electronic Health Record Data to Characterize Social Determinants of Health Among Survivors of Cancer in Persistent Poverty Areas: Cross-Sectional Study.

JMIR cancer·2026
Same author

Integrating Docking, Dynamics, and Assays to Predict Antimicrobial Peptide Interactions with Mycolic Acid Membranes in <i>Mycobacterium tuberculosis</i>.

ACS measurement science au·2025
Same author

Assessing the Impact of External and Internal Factors on Emergency Department Overcrowding.

Healthcare (Basel, Switzerland)·2025
Same author

An Artificial Intelligence-Based Framework for Predicting Emergency Department Overcrowding: Development and Evaluation Study.

JMIR medical informatics·2025
Same author

Examining the role of phonological and semantic mechanisms during morphological processing of sentences in 7-year-old children.

Cerebral cortex (New York, N.Y. : 1991)·2025

Related Experiment Video

Updated: Jul 15, 2026

DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning
09:27

DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning

Published on: March 15, 2011

Normalization of dye bias in microarray data using the mixture of splines model.

Yongsung Joo1, George Casella, James Booth

  • 1University of Florida, USA. yjoo@phhp.ufl.edu

Statistical Applications in Genetics and Molecular Biology
|April 4, 2007
PubMed
Summary

This study introduces a novel normalization method for microarray data to address dye biases missed by conventional techniques. A new gene comparison test is also presented to complement this advanced normalization approach.

More Related Videos

Microarray Analysis for Saccharomyces cerevisiae
13:17

Microarray Analysis for Saccharomyces cerevisiae

Published on: April 7, 2011

Using Microarrays to Interrogate Microenvironmental Impact on Cellular Phenotypes in Cancer
08:20

Using Microarrays to Interrogate Microenvironmental Impact on Cellular Phenotypes in Cancer

Published on: May 21, 2019

Related Experiment Videos

Last Updated: Jul 15, 2026

DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning
09:27

DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning

Published on: March 15, 2011

Microarray Analysis for Saccharomyces cerevisiae
13:17

Microarray Analysis for Saccharomyces cerevisiae

Published on: April 7, 2011

Using Microarrays to Interrogate Microenvironmental Impact on Cellular Phenotypes in Cancer
08:20

Using Microarrays to Interrogate Microenvironmental Impact on Cellular Phenotypes in Cancer

Published on: May 21, 2019

Area of Science:

  • Bioinformatics
  • Genomics
  • Statistical Modeling

Background:

  • Microarray data analysis is crucial for gene expression studies.
  • Conventional normalization methods may not fully correct for dye biases.
  • Dye biases can significantly impact the accuracy of gene expression comparisons.

Purpose of the Study:

  • To address limitations of current normalization methods in microarray analysis.
  • To propose a novel normalization technique for handling dye biases.
  • To develop a statistical test for gene comparisons compatible with the new method.

Main Methods:

  • A mixture of splines model is proposed for normalization.
  • The method specifically targets characteristics of dye biases.
  • A new statistical test for between-group gene comparisons is developed.

Main Results:

  • The proposed method effectively handles specific dye biases in microarray data.
  • The developed statistical test is designed for use with the new normalization technique.
  • Improved accuracy in gene expression analysis is anticipated.

Conclusions:

  • The novel normalization method offers an improvement for microarray data analysis.
  • The associated gene comparison test enhances the utility of the proposed method.
  • This work contributes to more reliable gene expression profiling.