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

A note on using permutation-based false discovery rate estimates to compare different analysis methods for microarray

Yang Xie1, Wei Pan, Arkady B Khodursky

  • 1Division of Biostatistics, School of Public Health, University of Minnesota Minneapolis, MN 55455, USA. yangxie@biostat.umn.ed

Bioinformatics (Oxford, England)
|September 29, 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

Scattering engineering in continuously shaped metasurface: An approach for electromagnetic illusion.

Scientific reports·2016
Same author

2D Metals by Repeated Size Reduction.

Advanced materials (Deerfield Beach, Fla.)·2016
Same author

A Case Report of Inversa Acne and Evaluation for Mutations in the NCSTN, PSENEN, and PSEN1 Genes.

Chinese medical journal·2016
Same author

Highly Luminescent Carbon Dots Synthesized by Microwave-Assisted Pyrolysis and Evaluation of Their Toxicity to Physa acuta.

Journal of nanoscience and nanotechnology·2016
Same author

B7-H3 protein expression in a murine model of osteosarcoma.

Oncology letters·2016
Same author

Positive and negative functions of B lymphocytes in tumors.

Oncotarget·2016
Same journal

Cross-Domain Transfer Learning from Peptides to Metabolites Using a Multi-Property Fine-Tuned LLM.

Bioinformatics (Oxford, England)·2026
Same journal

Biomedical Concept Recognition with Error-aware Negative-enhanced Ranking Framework.

Bioinformatics (Oxford, England)·2026
Same journal

TEDLH: Domain HMMs for sensitive detection of remote homologues.

Bioinformatics (Oxford, England)·2026
Same journal

PLNFGL: Joint Estimation of Multi-Condition Gene Networks from Single-cell RNA-seq Data.

Bioinformatics (Oxford, England)·2026
Same journal

MCFST: Spatial domain identification method based on multi-view graph convolutional network and graph fusion network.

Bioinformatics (Oxford, England)·2026
Same journal

SpaBiT: Enhancing Spatial Transcriptomics Resolution via Bidirectional Attention Transformers.

Bioinformatics (Oxford, England)·2026
See all related articles

The standard permutation method often overestimates the false discovery rate (FDR), potentially biasing evaluations of statistical methods. A modified permutation approach provides a more accurate and fairer FDR estimation for genomic studies.

Area of Science:

  • Genomic studies
  • Statistical method evaluation
  • Bioinformatics

Background:

  • False discovery rate (FDR) is crucial for evaluating statistical methods, especially in genomic research.
  • Permutation methods are commonly used to estimate FDR but may exhibit bias.
  • Accurate FDR estimation is essential for fair comparison of statistical approaches.

Purpose of the Study:

  • To investigate the bias of standard permutation-based FDR estimators.
  • To determine if this bias unfairly favors or disfavors specific statistical methods.
  • To propose a modified permutation method for improved FDR estimation and fairer method evaluation.

Main Methods:

  • Theoretical and empirical investigation of standard permutation FDR estimators.
  • Simulation and real data analysis.

Related Experiment Videos

  • Comparison of sample mean, SAM statistic, and Student's t-statistic performance.
  • Development and validation of a modified permutation-based FDR estimation method.

    • Main Results:

    • The standard permutation method systematically overestimates FDR across tested statistics.
    • Bias severity varied, being most pronounced for the sample mean and least for the t-statistic.
    • The proposed FDR estimation method demonstrated superior performance compared to the standard approach.

    Conclusions:

    • Caution is advised when using standard permutation-based FDR estimates for method comparison due to overestimation.
    • The proposed modified permutation method offers a more accurate and equitable FDR estimation.
    • This improved estimation facilitates fairer evaluation of statistical methods in genomic research.