Fast Computation of Genetic Likelihoods on
Human Pedigree Data
Tushar M. Goradia, Kenneth Lange, Perry L. Miller,
Prakash M. Nadkarni
Human Heredity, 42, 42-62 (1992)
Abstract
Gene mapping and genetic epidemiology require large-scale
computation of likelihoods based on human pedigree data.
Although computation of such likelihoods has become
increasingly sophisticated, fast calculations are still
impeded by complex pedigree structures, by models with
many underlying loci and by missing observations on key
family members. The current paper "introduces" a new method
of array factorization that substantially accelerates linkage
calculations with large numbers of markers. This method
is not limited to nuclear families or to families with
complete phenotyping.
Vectorization and parallelization are two general-purpose
hardware techniques for accelerating computations. These
techniques can assist in the rapid calculation of genetic
likelihoods. We describe our experience using both of these
methods with the existing program MENDEL. A vectorized
version of MENDEL was run on an IBM 3090 supercomputer.
A parallelized version of MENDEL was run on parallel
machines of different architectures and on a network
of workstations. Applying these revised versions of
MENDEL to two challenging linkage problems yields
substantial improvements in computational speed.
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