CVhaplot: a consensus tool for statistical haplotyping
CVhaplot: a consensus tool for statistical haplotyping
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DOI：
10.1111/j.1755-0998.2010.02843.x
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发表时间：
2010-11
影响因子：
7.7
通讯作者：
Zushi Huang;De-Xing Zhang
中科院分区：
文献类型：
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作者：
Zushi Huang;De-Xing Zhang
单倍型包含谱系信息，在种群遗传和进化研究中发挥着重要作用。然而，单倍型推断是一个复杂的统计问题，表现出相当大的内部算法变异性和算法之间的不一致性。因此，单倍型推断的统计算法往往包含隐藏的不确定性，这可能会复杂化，甚至误导下游分析。一致性策略是提高单倍型可信度的有效手段之一。在这里，我们提出了一个共识工具，CVhaplot包，自动化的单倍型推断的共识技术。它从竞争算法的推断中产生共识单体型，以增加单体型推断结果的置信度，同时通过考虑其内部变异性来提高单个算法的性能。它可以有效地识别可能与推理错误相关的不确定单倍型。此外，该工具允许几种流行算法的文件格式转换，并将一些算法的适用性扩展到包含三等位基因多态性位点的复杂数据。CVhaplot是用PERL编写的，可以在http://www.ioz.ac.cn/department/agripest/group/zhangdx/CVhaplot.htm上免费获得。
Haplotypes contain genealogical information and play a prominent part in population genetic and evolutionary studies. However, haplotype inference is a complex statistical problem, showing considerable internal algorithm variability and among‐algorithm discordance. Thus, haplotypes inferred by statistical algorithms often contain hidden uncertainties, which may complicate and even mislead downstream analysis. Consensus strategy is one of the effective means to increase the confidence of inferred haplotypes. Here, we present a consensus tool, the CVhaplot package, to automate consensus techniques for haplotype inference. It generates consensus haplotypes from inferrals of competing algorithms to increase the confidence of haplotype inference results, while improving the performance of individual algorithms by considering their internal variability. It can effectively identify uncertain haplotypes potentially associated with inference errors. In addition, this tool allows file format conversion for several popular algorithms and extends the applicability of some algorithms to complex data containing triallelic polymorphic sites. CVhaplot is written in PERL and freely available at http://www.ioz.ac.cn/department/agripest/group/zhangdx/CVhaplot.htm.