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Updated: Jul 5, 2026

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Haplotyping for disease association: a combinatorial approach.

Giuseppe Lancia1, R Ravi, Romeo Rizzi

  • 1Dipartimento di Matematica e Informatica, University of Udine, Udine, Italy. lancia@dimi.uniud.it

IEEE/ACM Transactions on Computational Biology and Bioinformatics
|May 3, 2008
PubMed
Summary

This study addresses the challenge of inferring genetic "good" and "bad" haplotypes from population data to understand disease inheritance. A simple solution exists for this NP-complete problem if data meet a minimal requirement.

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Area of Science:

  • Computational Biology
  • Genetics
  • Bioinformatics

Background:

  • Haplotyping is crucial for understanding genetic disease transmission.
  • Distinguishing between healthy and diseased individuals based on genotypes is complex.
  • Inferring haplotype contributions to disease status requires robust methods.

Purpose of the Study:

  • To formulate and solve a combinatorial problem for inferring disease-associated haplotypes.
  • To determine the computational complexity of haplotype inference for genetic diseases.
  • To identify conditions under which a simple solution for haplotyping is feasible.

Main Methods:

  • Formulation of a combinatorial problem based on population genotype data and disease status.
  • Analysis of the decision problem associated with inferring "good" and "bad" haplotypes.
  • Proof of NP-completeness for the general problem.
  • Development of a simple solution under specific data constraints.

Main Results:

  • The problem of inferring disease-related haplotypes is proven to be NP-complete.
  • A straightforward algorithm can solve the haplotyping problem.
  • The solution is contingent upon a minimal, weak data requirement.

Conclusions:

  • Despite the NP-complete nature of the general problem, efficient haplotyping is achievable.
  • The findings provide a practical approach for genetic disease analysis using population data.
  • This work contributes to the understanding of genotype-phenotype relationships in inherited diseases.