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

Determining significant fold differences in gene expression analysis.

A J Butte1, J Ye, H U Häring

  • 1Children's Hospital Informatics Program, Boston, MA 02115, USA.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|March 27, 2001
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

Serum tryptophan metabolites are associated with erosive hand osteoarthritis and pain: results from the DIGICOD cohort.

Osteoarthritis and cartilage·2023
Same author

Androgen-deprivation therapy and SARS-CoV-2 in men with prostate cancer: findings from the University of California Health System registry.

Annals of oncology : official journal of the European Society for Medical Oncology·2021
Same author

The phenotypical implications of immune dysregulation in fragile X syndrome.

European journal of neurology·2020
Same author

Comprehensive transcriptomic analysis of cell lines as models of primary tumors across 22 tumor types.

Nature communications·2019
Same author

Glucose tolerance and insulin sensitivity define adipocyte transcriptional programs in human obesity.

Molecular metabolism·2018
Same author

Integrating Clinical Phenotype and Gene Expression Data to Prioritize Novel Drug Uses.

CPT: pharmacometrics & systems pharmacology·2016
Same journal

Trust, Reproducibility, and Progress: The Roles of Independent Blind Prediction and Assessment and Benchmarking in Computational Biology.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
Same journal

The Evolving Cyberinfrastructure at the National Institutes of Health to Support Data and AI in Biomedical Research.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
Same journal

Applications of AI & ML in Biomanufacturing of Cell and Gene Therapies.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
Same journal

AI for Health: Leveraging Artificial Intelligence to Revolutionize Healthcare.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
Same journal

Workshop Introduction: Advances of AI Methods in Single Cell Spatial Omics.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
Same journal

DRIVE-KG: Enhancing variant-phenotype association discovery in understudied complex diseases using heterogeneous knowledge graphs.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
See all related articles

Reproducing entire gene expression experiments is crucial for reliable results. This study models fold difference reproducibility to establish significance thresholds, ensuring accurate identification of significant gene expression changes.

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • RNA expression microarrays are commonly used to compare gene expression between two groups.
  • Previous studies have not fully addressed the reproducibility of fold differences when entire experiments are duplicated.

Purpose of the Study:

  • To develop a statistical model for the significance of fold differences in gene expression data.
  • To maximize the number of expressed sequence tags (ESTs) exceeding a defined significance threshold.
  • To improve the reliability of identifying significant gene expression changes.

Main Methods:

  • Duplicated entire gene expression experiments were performed.
  • Fold differences were calculated and their distribution modeled.
  • Strategies were employed to filter noise and decrease significance requirements.

Related Experiment Videos

Main Results:

  • Fold differences showed less consistency in duplicated experiments compared to duplicate measurements within an experiment.
  • A model was successfully created to predict the distribution of duplicated fold differences.
  • Specific fold difference levels required for statistical significance were calculated.

Conclusions:

  • Replicating experiments is critical for validating significant gene expression findings.
  • The developed model allows for the calculation of significance thresholds without a priori assumptions.
  • This approach enhances the robustness of significance assessment in gene expression studies.