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模拟退火算法与快速连锁作图在遗传图谱构建中的比较。

Comparison between simulated annealing algorithms and rapid chain delineation in the construction of genetic maps.

机构信息

Departamento de Estatística, Universidade Federal de Viçosa, Viçosa, MG Brazil.

出版信息

Genet Mol Biol. 2010 Apr;33(2):398-407. doi: 10.1590/S1415-47572010005000033. Epub 2010 Jun 1.

DOI:10.1590/S1415-47572010005000033
PMID:21637501
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3036851/
Abstract

The efficiency of simulated annealing algorithms and rapid chain delineation in establishing the best linkage order, when constructing genetic maps, was evaluated. Linkage refers to the phenomenon by which two or more genes, or even more molecular markers, can be present in the same chromosome or linkage group. In order to evaluate the capacity of algorithms, four F(2) co-dominant populations, 50, 100, 200 and 1000 in size, were simulated. For each population, a genome with four linkage groups (100 cM) was generated. The linkage groups possessed 51, 21, 11 and 6 marks, respectively, and a corresponding distance of 2, 5, 10 and 20 cM between adjacent marks, thereby causing various degrees of saturation. For very saturated groups, with an adjacent distance between marks of 2 cM and in greater number, i.e., 51, the method based upon stochastic simulation by simulated annealing presented orders with distances equivalent to or lower than rapid chain delineation. Otherwise, the two methods were commensurate through presenting the same SARF distance.

摘要

评估了模拟退火算法和快速连锁作图在建立最佳连锁顺序方面的效率,连锁是指两个或更多基因甚至更多分子标记存在于同一染色体或连锁群中的现象。为了评估算法的能力,模拟了四个 F2 共显性群体,大小分别为 50、100、200 和 1000。对于每个群体,生成一个具有四个连锁群(100cM)的基因组。连锁群分别具有 51、21、11 和 6 个标记,相邻标记之间的相应距离为 2、5、10 和 20cM,从而导致不同程度的饱和。对于非常饱和的群体,标记之间的相邻距离为 2cM 且数量更多,即 51,则基于模拟退火的随机模拟的方法提供的顺序具有与快速连锁作图相当或更低的距离。否则,两种方法通过呈现相同的 SARF 距离来相称。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c63/3036851/2c06fd5000ba/gmb-33-2-398-gfig8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c63/3036851/f2ccc4a2b776/gmb-33-2-398-gfig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c63/3036851/3ed80788a34c/gmb-33-2-398-gfig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c63/3036851/1550f1a915ba/gmb-33-2-398-gfig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c63/3036851/64ceb751869c/gmb-33-2-398-gfig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c63/3036851/b84e2b6c1fc6/gmb-33-2-398-gfig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c63/3036851/559870401c7c/gmb-33-2-398-gfig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c63/3036851/9436a39ff961/gmb-33-2-398-gfig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c63/3036851/2c06fd5000ba/gmb-33-2-398-gfig8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c63/3036851/f2ccc4a2b776/gmb-33-2-398-gfig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c63/3036851/3ed80788a34c/gmb-33-2-398-gfig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c63/3036851/1550f1a915ba/gmb-33-2-398-gfig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c63/3036851/64ceb751869c/gmb-33-2-398-gfig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c63/3036851/b84e2b6c1fc6/gmb-33-2-398-gfig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c63/3036851/559870401c7c/gmb-33-2-398-gfig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c63/3036851/9436a39ff961/gmb-33-2-398-gfig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c63/3036851/2c06fd5000ba/gmb-33-2-398-gfig8.jpg

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