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An incremental algorithm for efficient multipoint linkage analysis

R W Kramer1, D E Weeks, D M Chiarulli

  • 1Department of Computer Science, University of Pittsburgh, PA 15260, USA.

Human Heredity
|November 1, 1995
PubMed
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This study introduces an incremental computing method to speed up genetic linkage map construction. The new approach significantly reduces computation time for multipoint likelihood calculations, especially in large pedigrees.

Area of Science:

  • Computational Biology
  • Genetics
  • Bioinformatics

Background:

  • Multipoint likelihood calculations are crucial for genetic linkage map construction.
  • Current algorithms for these calculations present a significant computational bottleneck.

Purpose of the Study:

  • To develop a more efficient computational method for multipoint likelihood calculations.
  • To reduce the time required for iterative computations in genetic mapping.

Main Methods:

  • Utilized incremental processing techniques to store and reuse intermediate computational results.
  • Developed a novel incremental program as an alternative to the CMAP program in the LINKAGE package.
  • Represented intermediate results as rational functions for efficient reevaluation.

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Main Results:

  • The incremental program demonstrated a 3-fold speedup compared to CMAP for single marker locus position likelihood computation in fully typed pedigrees.
  • The computational time did not significantly increase with additional marker locus positions, leading to more pronounced speedups.

Conclusions:

  • Incremental processing offers a substantial improvement in the efficiency of genetic linkage map construction.
  • The developed method effectively addresses the computational bottleneck in multipoint likelihood calculations.