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Parallelization of general-linkage analysis problems

S Dwarkadas1, A A Schäffer, R W Cottingham

  • 1Department of Computer Science, Rice University, Houston, Tex.

Human Heredity
|May 1, 1994
PubMed
Summary
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A new parallel genetic linkage analysis program offers significant speed improvements. This computational tool enhances genetic analysis efficiency across various hardware platforms, from standard networks to advanced multiprocessors.

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Genetics

Background:

  • Genetic linkage analysis is crucial for identifying disease-associated genes.
  • Efficient computational methods are needed to handle large genetic datasets.
  • Parallel computing offers a promising approach to accelerate complex genetic analyses.

Purpose of the Study:

  • To develop and evaluate a parallel implementation of a genetic linkage analysis program.
  • To assess the performance and scalability of the parallel program on different hardware architectures.
  • To demonstrate significant speed improvements in genetic linkage analysis.

Main Methods:

  • A shared-memory programming style was employed for the parallel implementation.
  • The program was tested on three distinct platforms: Ethernet network, ATM network, and shared-memory multiprocessor.

Related Experiment Videos

  • Performance was evaluated based on speedup achieved with 8 processors.

    • Main Results:

    • Speedups ranging from 3.5 to 5 were observed on the Ethernet network.
    • Speedups between 4.8 and 6 were achieved on the ATM network.
    • Speedups of 5.5 to 6.5 were obtained on the shared-memory multiprocessor.

    Conclusions:

    • The parallel genetic linkage analysis program demonstrates substantial speed improvements across diverse computing environments.
    • The implementation is effective even for single pedigree analyses, offering flexibility.
    • The study highlights the benefits of parallel computing for accelerating genetic linkage analysis.