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

Multiple testing for SNP-SNP interactions.

Anne-Laure Boulesteix1, Carolin Strobl, Stefan Weidinger

  • 1Sylvia Lawry Centre and Institute for Medical Statistics and Epidemiology, Technical University of Munich. boulesteix@slcmsr.org

Statistical Applications in Genetics and Molecular Biology
|January 4, 2008
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

STrategies for developing REseArch Methods guidance (STREAM): Protocol.

Journal of clinical epidemiology·2026
Same author

The statistical software revolution in pharmaceutical development: challenges and opportunities in open source.

Drug discovery today·2026
Same author

On "Confirmatory" Methodological Research in Statistics and Related Fields.

Statistics in medicine·2025
Same author

ChatGPT as a Tool for Biostatisticians: A Tutorial on Applications, Opportunities, and Limitations.

Statistics in medicine·2025
Same author

Rethinking the Handling of Method Failure in Comparison Studies.

Statistics in medicine·2025
Same author

Comparing supervised machine learning algorithms for the prediction of partial arterial pressure of oxygen during craniotomy.

BMC medical informatics and decision making·2025
Same journal

Annealed variational mixtures for disease subtyping and biomarker discovery.

Statistical applications in genetics and molecular biology·2026
Same journal

Performance of the permutation test approach with base calling errors for detecting changes in variant allele frequencies in ctDNA for a single patient.

Statistical applications in genetics and molecular biology·2026
Same journal

BLOG: Bayesian longitudinal omics with group constraints.

Statistical applications in genetics and molecular biology·2026
Same journal

AI-driven risk prediction and categorization in cystic fibrosis leveraging AttentiveLSTM and Fox Wolf Optimizer.

Statistical applications in genetics and molecular biology·2026
Same journal

Perfect collinearity not created equal: measuring and visualizing the severity of multi-collinearity of modern omics data.

Statistical applications in genetics and molecular biology·2026
Same journal

Corrigendum to: Choice of baseline hazards in joint modeling of longitudinal and time-to-event cancer survival data.

Statistical applications in genetics and molecular biology·2025
See all related articles

This study introduces a new statistical method for analyzing complex genetic diseases by examining combinations of single nucleotide polymorphisms (SNPs). The approach effectively controls for multiple comparisons when identifying significant SNP-SNP interactions.

Area of Science:

  • Genetics
  • Biostatistics
  • Computational Biology

Background:

  • Complex genetic diseases often result from combinations of single nucleotide polymorphisms (SNPs), not individual ones.
  • Identifying SNP-SNP interactions using logical operators is a common approach, but poses multiple testing challenges.
  • Existing methods for high-dimensional settings may not adequately address optimal logic expression selection within fixed SNP subsets.

Purpose of the Study:

  • To propose a general asymptotic approach for deriving the distribution of the maximally selected chi-square statistic.
  • To develop a method for testing SNP-SNP interaction patterns while controlling for multiple comparisons.
  • To provide a statistical tool for analyzing complex genetic diseases associated with combinations of SNPs.

Main Methods:

Related Experiment Videos

  • Developed a general asymptotic approach for the maximally selected chi-square statistic.
  • Applied this approach to test logic expressions, specifically SNP-SNP interaction patterns.
  • Utilized simulations to validate the multiple testing adjustments and demonstrated with a real dataset (KORA study).

Main Results:

  • The proposed method provides accurate multiple testing adjustments when the logic expression is chosen to maximize the statistic.
  • The method effectively controls for comparisons in testing SNP-SNP interactions.
  • Demonstrated utility in a real-world population-based study on allergy and asthma.

Conclusions:

  • The developed asymptotic approach is effective for testing logic expressions and SNP-SNP interactions under multiple comparison constraints.
  • The R package 'SNPmaxsel' provides a practical implementation of this novel statistical method.
  • This work advances the analysis of complex genetic diseases by offering a robust tool for identifying significant genetic combinations.