Efficient and accurate construction of genetic linkage maps from the minimum spanning tree of a graph.
Efficient and accurate construction of genetic linkage maps from the minimum spanning tree of a graph.
复制标题
从图的最小生成树上有效，准确地构造了遗传连锁图。
DOI：
10.1371/journal.pgen.1000212
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发表时间：
2008-10
期刊：
影响因子：
4.5
通讯作者：
Lonardi, Stefano
中科院分区：
文献类型：
--
作者：
Wu, Yonghui;Bhat, Prasanna R.;Close, Timothy J.;Lonardi, Stefano
遗传连锁图谱是生物技术广泛应用的基石，包括图位辅助育种、关联遗传学和图位辅助基因克隆。在过去的几年里，高通量基因分型技术的采用伴随着遗传标记密度和多样性的大幅增加。为了有效地处理这些大数据集并准确地构建高密度遗传图谱，需要新的遗传作图算法。在本文中，我们介绍了一种新的算法，以命令标记的遗传连锁图。我们的方法是基于一个简单而基本的数学性质，我们证明在相当一般的假设。这个属性的有效性允许一个有效地确定正确的顺序标记通过计算最小生成树的相关图。我们的经验研究获得的基因分型数据的三个映射群体的大麦（大麦），以及广泛的模拟合成数据，表明我们的算法始终优于最好的方法在文献中，特别是当输入数据是嘈杂的或不完整的。实现我们的算法的软件是在公共领域作为一个Web工具的名称MSTmap。遗传连锁图是生物技术广泛应用的基石。近年来，新的高通量基因分型技术大大增加了遗传标记的密度和多样性，为计算生物学家带来了新的算法挑战。在本文中，我们提出了一种新的算法方法来构建遗传图谱的基础上一个新的理论见解。我们的方法优于科学文献中可用的最佳方法，特别是当输入数据有噪声或不完整时。
Genetic linkage maps are cornerstones of a wide spectrum of biotechnology applications, including map-assisted breeding, association genetics, and map-assisted gene cloning. During the past several years, the adoption of high-throughput genotyping technologies has been paralleled by a substantial increase in the density and diversity of genetic markers. New genetic mapping algorithms are needed in order to efficiently process these large datasets and accurately construct high-density genetic maps. In this paper, we introduce a novel algorithm to order markers on a genetic linkage map. Our method is based on a simple yet fundamental mathematical property that we prove under rather general assumptions. The validity of this property allows one to determine efficiently the correct order of markers by computing the minimum spanning tree of an associated graph. Our empirical studies obtained on genotyping data for three mapping populations of barley (Hordeum vulgare), as well as extensive simulations on synthetic data, show that our algorithm consistently outperforms the best available methods in the literature, particularly when the input data are noisy or incomplete. The software implementing our algorithm is available in the public domain as a web tool under the name MSTmap. Genetic linkage maps are cornerstones of a wide spectrum of biotechnology applications. In recent years, new high-throughput genotyping technologies have substantially increased the density and diversity of genetic markers, creating new algorithmic challenges for computational biologists. In this paper, we present a novel algorithmic method to construct genetic maps based on a new theoretical insight. Our approach outperforms the best methods available in the scientific literature, particularly when the input data are noisy or incomplete.
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影响因子：
2.1
作者：
FALK, CT
通讯作者：
FALK, CT
DOI：
10.1073/pnas.84.8.2363
发表时间：
1987-04-01
影响因子：
11.1
作者：
LANDER, ES;GREEN, P
通讯作者：
GREEN, P
影响因子：
3.3
作者：
Cartwright, Dustin A.;Troggio, Michela;Gutin, Alexander
通讯作者：
Gutin, Alexander
影响因子：
5.4
作者：
Jansen, J;de Jong, AG;van Ooijen, JW
通讯作者：
van Ooijen, JW
影响因子：
--
作者：
Sturtevant, AH
通讯作者：
Sturtevant, AH