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 Experiment Videos

Dye bias correction in dual-labeled cDNA microarray gene expression measurements.

Barry A Rosenzweig1, P Scott Pine, Olen E Domon

  • 1Center for Drug Evaluation and Research, Division of Applied Pharmacology Research, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Life Sciences Building 64, Silver Spring, MD 20993, USA. rosenzweigb@cder.fda.gov

Environmental Health Perspectives
|March 23, 2004
PubMed
Summary

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Evaluating miRNA Sequencing and Integrative Proteomics for Identifying Plasma miRNAs as Potential Pharmacodynamic Biomarkers of IFNβ-1a Biologics.

Clinical and translational science·2025
Same author

Urinary Kidney Injury Biomarker Profiles in Healthy Individuals and After Nephrotoxic and Ischemic Injury.

Clinical pharmacology and therapeutics·2025
Same author

ICH S1 prospective evaluation study and weight of evidence assessments: commentary from industry representatives.

Frontiers in toxicology·2024
Same author

Magnitude of Urine Albumin and KIM-1 Changes Can be Used to Differentiate Glomerular Injury From Tubular Injury in Rats.

Toxicologic pathology·2024
Same author

A mechanistic biomarker investigation of fialuridine hepatotoxicity using the chimeric TK-NOG Hu-liver mouse model and in vitro micropatterned hepatocyte cocultures.

Toxicology research·2024
Same author

Early-Onset albuminuria and Associated Renal Pathology in Leucine-Rich Repeat Kinase 2 Knockout Rats.

Toxicologic pathology·2023

Dye bias in dual-labeled cDNA microarrays causes significant signal errors. A new method using split-control microarrays accurately measures and corrects this bias, improving experimental precision and reducing costs.

Area of Science:

  • * Molecular Biology
  • * Genomics
  • * Bioinformatics

Background:

  • * Dual-labeled spotted cDNA microarrays are susceptible to signal errors from dye bias.
  • * Transcript-dependent dye bias arises from differential dye incorporation and hybridization efficiencies.
  • * This bias can lead to substantial false-positive and false-negative results, impacting analytical accuracy.

Purpose of the Study:

  • * To assess and minimize the effects of dye bias on fluorescent hybridization signals in cDNA microarrays.
  • * To develop a more efficient experimental design for cell culture experiments.
  • * To reduce the costs associated with controlling dye bias.

Main Methods:

  • * Measured dye bias at the individual transcript level using replicate dual-labeled split-control sample hybridizations.

Related Experiment Videos

  • * Analyzed transcript-dependent dye bias within concurrently processed arrays.
  • * Developed a mathematical correction method for the measured dye bias.

    • Main Results:

    • * Dye bias was identified as a significant component of fluorescent signal differences.
    • * Transcript-dependent dye bias alone can cause unacceptable rates of false signals.
    • * The bias was found to be consistent within a batch of hybridizations, making it measurable and correctable.
    • * Split-control microarrays effectively measured dye bias, eliminating the need for costly technical dye-swap replicates.

    Conclusions:

    • * A practical and efficient experimental design can measure and correct for dye bias in cDNA microarrays.
    • * Incorporating split-control microarrays reduces costs while maintaining experimental accuracy and precision.
    • * This approach enhances the reliability of data obtained from dual-labeled microarrays.