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

False discovery rate paradigms for statistical analyses of microarray gene expression data.

Cheng Cheng1, Stan Pounds

  • 1Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN, USA. Cheng.Cheng@STJUDE.ORG

Bioinformation
|June 29, 2007
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

Egg recognition and chick discrimination in colonial breeding birds.

Behavioural processes·2019
Same author

Association of total sedentary behaviour and television viewing with risk of overweight/obesity, type 2 diabetes and hypertension: A dose-response meta-analysis.

Diabetes, obesity & metabolism·2019
Same author

AAV-ie enables safe and efficient gene transfer to inner ear cells.

Nature communications·2019
Same author

The effect of the overexpression of miR-490 on the biological function of prostate cancer cell PC-3.

Journal of B.U.ON. : official journal of the Balkan Union of Oncology·2019
Same author

Treatment response and outcome of children with T-cell acute lymphoblastic leukemia expressing the gamma-delta T-cell receptor.

Oncoimmunology·2019
Same author

Hypertension is a modifiable risk factor for osteonecrosis in acute lymphoblastic leukemia.

Blood·2019
Same journal

Assessment of lower incisor position and symphysis dimensions among different skeletal patterns in the Chhattisgarh population.

Bioinformation·2026
Same journal

Low T3 syndrome and short-term outcomes in patients with acute decompensated heart failure: A retrospective observational study.

Bioinformation·2026
Same journal

Cardiovascular risk prevention awareness and practices in type 2 diabetes: Linking HbA1c and lipid levels.

Bioinformation·2026
Same journal

Assessment of periodontal condition using basic periodontal examination scores: A retrospective clinical study.

Bioinformation·2026
Same journal

Comparative evaluation of osseointegration among different surface modification techniques in dental implants.

Bioinformation·2026
Same journal

Micro-osteoperforations' impact on orthodontic tooth movement rate: Split mouth research.

Bioinformation·2026
See all related articles

This survey reviews statistical methods for massive multiple hypothesis testing, focusing on controlling the false discovery rate (FDR) and related concepts. It highlights key developments and applications in gene expression analysis.

Area of Science:

  • Biostatistics
  • Genomics
  • Statistical Genetics

Background:

  • Microarray gene expression studies generate massive datasets necessitating advanced statistical methods.
  • Massive multiple hypothesis testing is a significant challenge in analyzing high-dimensional biological data.

Purpose of the Study:

  • To provide a technical survey of false discovery rate (FDR)-related paradigms in massive multiple hypothesis testing.
  • To review the current state of statistical methodologies for FDR control and estimation.
  • To emphasize problem formulation, error measurement concepts, and application considerations.

Main Methods:

  • Review of statistical literature on FDR control and estimation.
  • Technical survey focusing on FDR-related paradigms.

Related Experiment Videos

  • Analysis of error measurement concepts and application considerations.

    • Main Results:

    • Identified five main paradigms for massive multiple hypothesis testing: FDR control, FDR estimation, significance threshold criteria, FWER/gFWER control, and empirical Bayes approaches.
    • Detailed the developments within FDR-related paradigms.
    • Provided a focused review rather than an exhaustive survey.

    Conclusions:

    • The field of massive multiple hypothesis testing has seen significant statistical research driven by gene expression applications.
    • Understanding FDR-related paradigms is crucial for accurate interpretation of high-dimensional data.
    • Further research and precise application considerations are needed for robust statistical inference.