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Machine learning approaches to explore digenic inheritance.

Atsuko Okazaki1, Jurg Ott2

  • 1Department of Diagnostics and Therapeutics of Intractable Diseases, Juntendo University, Bunkyo-ku, Tokyo 113-8421, Japan; Laboratory of Statistical Genetics, Rockefeller University, New York, NY 10065, USA.

Trends in Genetics : TIG
|May 17, 2022
PubMed
Summary

Digenic inheritance, where two DNA variants cause rare genetic disorders, is increasingly studied using machine learning. This convergence of human genetics and Big Data methods helps uncover combined variant effects on disease.

Keywords:
digenic inheritanceepistasismachine learningmodifier variantsstatistical genetics

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Area of Science:

  • Human Genetics
  • Machine Learning
  • Big Data Analytics

Background:

  • Rare genetic disorders like retinitis pigmentosa and Alport syndrome can arise from digenic inheritance, involving co-inherited DNA variants at two loci.
  • Statistical methods in human genetics have been developed to analyze these complex inheritance patterns.
  • Independent advancements in machine learning, particularly for Big Data, have paralleled these developments.

Purpose of the Study:

  • To provide an overview of statistical methods in human genetics for analyzing digenic inheritance.
  • To highlight the convergence of human genetics and machine learning fields.
  • To focus on machine learning approaches for identifying combined effects of DNA variant pairs in human diseases.

Main Methods:

  • Review of statistical methods used in human genetics for digenic inheritance.
  • Exploration of machine learning techniques applicable to Big Data.
  • Focus on methods designed to uncover interactive effects of genetic variants.

Main Results:

  • The study reviews established statistical approaches in human genetics.
  • It identifies analogous developments in machine learning for analyzing complex data.
  • The convergence of these fields offers new potential for understanding digenic diseases.

Conclusions:

  • The integration of human genetics and machine learning is crucial for understanding digenic inheritance.
  • Machine learning methods provide powerful tools for analyzing combined DNA variant effects.
  • Further research in this converged field can advance the study of rare genetic disorders.