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

Statistical analysis of microarray data.

Mark Reimers1

  • 1National Institutes of Health, Bethesda, MD 20892, USA. reimersm@mail.nih.gov

Addiction Biology
|April 26, 2005
PubMed
Summary
This summary is machine-generated.

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

Reading the Social Clock: Analyzing Nonverbal Coordination Dynamics in Casual Chat and Conflict.

Annals of the New York Academy of Sciences·2025
Same author

Human resilience depends on distinctively human brain circuitry and development.

Frontiers in behavioral neuroscience·2024
Same author

Safety considerations for dietary supplement manufacturers in the United States.

Regulatory toxicology and pharmacology : RTP·2023
Same author

HPV+ head and neck cancer-derived small extracellular vesicles communicate with TRPV1+ neurons to mediate cancer pain.

Pain·2023
Same author

Phytochemical drug discovery for COVID-19 using high-resolution computational docking and machine learning assisted binder prediction.

Journal of biomolecular structure & dynamics·2022
Same author

Swimming direction of the glass catfish is responsive to magnetic stimulation.

PloS one·2021

This guide simplifies microarray data analysis, covering experimental design, normalization, and differential expression testing. It offers practical solutions for interpreting complex gene expression data from platforms like Affymetrix chips.

Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • Microarrays offer dynamic insights into cellular activity but present significant interpretation challenges.
  • A vast body of literature exists on microarray data analysis, requiring distillation of practical insights.

Purpose of the Study:

  • To provide practical, actionable results from the extensive literature on microarray data analysis.
  • To address common challenges encountered in interpreting and analyzing microarray data.

Main Methods:

  • Focus on pre-processing techniques, including normalization and quality control.
  • Detailed examination of methods for exploratory analysis and differential expression testing.
  • Specialized discussion on low-level analysis for Affymetrix chips and the multiple testing problem.

Related Experiment Videos

Main Results:

  • Key practical considerations for experimental design are highlighted.
  • Effective normalization strategies are presented for robust data pre-processing.
  • Methods for identifying differentially expressed genes are clarified, addressing multiple testing issues.

Conclusions:

  • This article serves as a practical guide to overcome common hurdles in microarray data analysis.
  • Implementing sound pre-processing and differential expression analysis is crucial for reliable biological conclusions.
  • The provided insights aid researchers in effectively utilizing microarray data for biological discovery.