Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Advertisement

Nature Precedings
  • View all journals
  • Search
  • My Account Login
  • Content Explore content
  • About the journal
  • RSS feed
  1. nature
  2. nature precedings
  3. articles
  4. article
Statistical Modeling of Epistasis and Linkage Decay using Logic Regression
Download PDF
Download PDF
  • Manuscript
  • Open access
  • Published: 20 November 2008

Statistical Modeling of Epistasis and Linkage Decay using Logic Regression

  • Thomas Parker1,
  • Peter Szucs1,
  • Walt Mahaffee1,
  • Jean-Luc Jannink1 &
  • …
  • John Henning2 

Nature Precedings (2008)Cite this article

  • 271 Accesses

  • Metrics details

Abstract

Logic regression has been recognized as a tool that can identify and model non-additive genetic interactions using Boolean logic groups. Logic regression, TASSEL-GLM and SAS-GLM were compared for analytical precision using a previously characterized model system to identify the best genetic model explaining epistatic interaction of vernalization-sensitivity in barley. A genetic model containing two molecular markers identified in vernalization response in barley was selected using logic regression while both TASSEL-GLM and SAS-GLM included spurious associations in their models. The results also suggest the logic regression can be used to identify dominant/recessive relationships between epistatic alleles through its use of conjugateoperators.

Similar content being viewed by others

Extremely sparse models of linkage disequilibrium in ancestrally diverse association studies

Article 28 August 2023

Epistatic Net allows the sparse spectral regularization of deep neural networks for inferring fitness functions

Article Open access 01 September 2021

Relative importance of composition structures and biologically meaningful logics in bipartite Boolean models of gene regulation

Article Open access 28 October 2022

Article PDF

Author information

Authors and Affiliations

  1. USDA-ARS https://www.nature.com/nature

    Thomas Parker, Peter Szucs, Walt Mahaffee & Jean-Luc Jannink

  2. Oregon State University https://www.nature.com/nature

    John Henning

Authors
  1. Thomas Parker
    View author publications

    Search author on:PubMed Google Scholar

  2. Peter Szucs
    View author publications

    Search author on:PubMed Google Scholar

  3. Walt Mahaffee
    View author publications

    Search author on:PubMed Google Scholar

  4. Jean-Luc Jannink
    View author publications

    Search author on:PubMed Google Scholar

  5. John Henning
    View author publications

    Search author on:PubMed Google Scholar

Corresponding author

Correspondence to Thomas Parker.

Rights and permissions

Creative Commons Attribution 3.0 License.

Reprints and permissions

About this article

Cite this article

Parker, T., Szucs, P., Mahaffee, W. et al. Statistical Modeling of Epistasis and Linkage Decay using Logic Regression. Nat Prec (2008). https://doi.org/10.1038/npre.2008.1386.2

Download citation

  • Received: 18 November 2008

  • Accepted: 20 November 2008

  • Published: 20 November 2008

  • DOI: https://doi.org/10.1038/npre.2008.1386.2

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Keywords

  • Epistasis
  • Barley
  • Boolean
  • logic
  • vernalization
Download PDF

Advertisement

Explore content

  • Research articles
  • News & Comment
  • Sign up for alerts
  • RSS feed

About the journal

  • Journal Information

Search

Advanced search

Quick links

  • Explore articles by subject
  • Find a job
  • Guide to authors
  • Editorial policies

Nature Precedings (Nat Preced)

nature.com sitemap

About Nature Portfolio

  • About us
  • Press releases
  • Press office
  • Contact us

Discover content

  • Journals A-Z
  • Articles by subject
  • protocols.io
  • Nature Index

Publishing policies

  • Nature portfolio policies
  • Open access

Author & Researcher services

  • Reprints & permissions
  • Research data
  • Language editing
  • Scientific editing
  • Nature Masterclasses
  • Research Solutions

Libraries & institutions

  • Librarian service & tools
  • Librarian portal
  • Open research
  • Recommend to library

Advertising & partnerships

  • Advertising
  • Partnerships & Services
  • Media kits
  • Branded content

Professional development

  • Nature Awards
  • Nature Careers
  • Nature Conferences

Regional websites

  • Nature Africa
  • Nature China
  • Nature India
  • Nature Japan
  • Nature Middle East
  • Privacy Policy
  • Use of cookies
  • Legal notice
  • Accessibility statement
  • Terms & Conditions
  • Your US state privacy rights
Springer Nature

© 2025 Springer Nature Limited

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing