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

Empirical bayes gene screening tool for time-course or dose-response microarray data.

J E Eckel1, C Gennings, V M Chinchilli

  • 1Department of Biostatistics, Virginia Commonwealth University, Richmond, Virginia 23298, USA.

Journal of Biopharmaceutical Statistics
|October 8, 2004
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

Prenatal Pb exposure is associated with reduced abundance of beneficial gut microbial cliques in late childhood: an investigation using Microbial Co-occurrence Analysis (MiCA).

medRxiv : the preprint server for health sciences·2023
Same author

Dietary Methionine and Total Sulfur Amino Acid Restriction in Healthy Adults.

The journal of nutrition, health & aging·2023
Same author

Internalized skin bias: validation study to explore the impact of the internalization of social stigma on those with hidradenitis suppurativa.

Journal of the European Academy of Dermatology and Venereology : JEADV·2022
Same author

Principles of dose-setting in toxicology studies: the importance of kinetics for ensuring human safety.

Archives of toxicology·2021
Same author

Evaluation of the Inherent Toxicity Concept in Environmental Toxicology and Risk Assessment.

Environmental toxicology and chemistry·2020
Same author

Corrigendum to "Convergence of hepcidin deficiency, systemic iron overloading, heme accumulation, and REV-ERBα/β activation in aryl hydrocarbon receptor-elicited hepatotoxicity" [Toxicol. Appl. Pharmacol. 321 (2017) 1-17].

Toxicology and applied pharmacology·2018
Same journal

Correction.

Journal of biopharmaceutical statistics·2026
Same journal

Leveraging external controls in clinical trials: estimands, estimation, assumptions.

Journal of biopharmaceutical statistics·2026
Same journal

Special issue of nonclinical statistics in regulatory applications guest editors' notes.

Journal of biopharmaceutical statistics·2026
Same journal

Comparison of flexible parametric modeling and nonparametric methods to estimate restricted mean survival time: A simulation study.

Journal of biopharmaceutical statistics·2026
Same journal

Simulated treatment comparisons with jackknife pseudo values for estimating population-adjusted marginal treatment effects.

Journal of biopharmaceutical statistics·2026
Same journal

Sample sizes for randomized controlled trials utilizing Bayesian response adaptive randomization for continuous outcomes.

Journal of biopharmaceutical statistics·2026
See all related articles

This study introduces an improved empirical Bayes method for analyzing microarray gene expression data. The new approach efficiently identifies differentially expressed genes in complex time-course experiments, simplifying data analysis.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Statistical Genetics

Background:

  • Microarray experiments generate vast amounts of gene expression data, necessitating efficient dimensionality reduction.
  • Identifying differentially expressed genes is crucial for understanding biological responses to treatments.
  • Existing methods may not fully capture complex experimental designs like time-course studies.

Purpose of the Study:

  • To develop an enhanced empirical Bayes method for screening differentially expressed cDNAs in microarray data.
  • To extend existing methods to handle complex experimental designs, including time-course and dose-response studies.
  • To provide a robust tool for identifying genes with high probabilities of differential expression.

Main Methods:

  • Application of an extension to Efron et al.'s empirical Bayes methods.

Related Experiment Videos

  • Analysis of differential time-course gene expression data with unequally spaced time points.
  • Incorporation of complex experimental designs and multiple design replications.

    • Main Results:

    • The proposed empirical Bayes gene-screening tool effectively identifies a subset of differentially expressed cDNAs.
    • The method allows inference across continuous variables, enhancing its applicability.
    • Comparison with existing methods (Efron et al., adjusted t-value) on a toxicological time-course dataset.

    Conclusions:

    • The developed empirical Bayes tool offers an efficient method for gene expression data dimensionality reduction.
    • This screening tool is adaptable for various microarray experiments, including dose-response studies.
    • The method provides a valuable approach for identifying key genes in complex biological experiments.