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一种用于多点似然计算的更快且更通用的隐马尔可夫模型算法。

A faster and more general hidden Markov model algorithm for multipoint likelihood calculations.

作者信息

Idury R M, Elston R C

机构信息

Sequana Therapeutics, La Jolla, Calif., USA.

出版信息

Hum Hered. 1997 Jul-Aug;47(4):197-202. doi: 10.1159/000154413.

Abstract

There are two basic algorithms for calculating multipoint linkage likelihoods: in one the computational effort increases linearly with the number of pedigree members and exponentially with the number of markers, in the other the effort increases exponentially with the number of persons but linearly with the number of markers. We describe a faster version of the latter algorithm for which there is no penalty in making the recombination fraction meiosis specific. This can lead to faster and potentially more powerful linkage analysis whenever the number of nonfounder meioses in a pedigree is not too large.

摘要

计算多点连锁似然性有两种基本算法

一种算法中,计算量随家系成员数量呈线性增加,随标记数量呈指数增加;另一种算法中,计算量随个体数量呈指数增加,但随标记数量呈线性增加。我们描述了后一种算法的一个更快版本,对于该版本,使重组分数具有减数分裂特异性不会带来不利影响。只要家系中非奠基者减数分裂的数量不是太大,这就能实现更快且可能更强大的连锁分析。

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