Exploring effective approaches for haplotype block phasing
Exploring effective approaches for haplotype block phasing
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DOI：
10.1186/s12859-019-3095-8
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发表时间：
2019-10-30
影响因子：
3
通讯作者：
Goudey, Benjamin
中科院分区：
文献类型：
--
作者：
Al Bkhetan, Ziad;Zobel, Justin;Goudey, Benjamin
背景资料：相位的知识，同源染色体的每个拷贝上的特定等位基因序列，越来越多地被认为是检测某些类型的疾病相关突变的关键。检测此类突变的一种方法是通过定相单倍型关联分析。虽然基因型数据定相方法的准确性已被广泛探索，但在单倍型块尺度上的定相准确性却很少受到关注。了解相控工具的准确性和用于确定单倍型块内的错误率确定blocks.Results的方法相结合的影响是必不可少的进行准确的单倍型analysis.Results：我们提出了一个系统的研究，探索七个广泛使用的定相方法和两个常见的方法确定单倍型块之间的关系。评估的重点是被错误定相的单倍型块的数量。从这些结果的见解是用来开发一个单倍型估计的基础上达成共识的三个工具。共识估计量在所有应用的测试中实现了最准确的定相。个别地，EAGLE 2、BEAGLE和SHAPEIT 2在不同场景中交替成为最佳性能工具。与滑动窗口方法相比，基于连锁不平衡确定单倍型块导致更正确的定相块。我们发现，与整条染色体的定相相比，基因组（例如基因）的定相部分之间几乎没有差异。最后，我们表明，定相误差的位置不同时，工具被应用到相同的数据几次，一个发现，可能是重要的下游analysis.Conclusions：定相和块确定算法的选择和它们的相互作用影响的准确性相单倍型块。这项工作提供了指导和证据，不同的设计选择需要使用单倍型块进行分析。这项研究强调了一些问题，可能限制了以前的单倍型分析的可复制性。
Background: Knowledge of phase, the specific allele sequence on each copy of homologous chromosomes, is increasingly recognized as critical for detecting certain classes of disease-associated mutations. One approach for detecting such mutations is through phased haplotype association analysis. While the accuracy of methods for phasing genotype data has been widely explored, there has been little attention given to phasing accuracy at haplotype block scale. Understanding the combined impact of the accuracy of phasing tool and the method used to determine haplotype blocks on the error rate within the determined blocks is essential to conduct accurate haplotype analyses.Results: We present a systematic study exploring the relationship between seven widely used phasing methods and two common methods for determining haplotype blocks. The evaluation focuses on the number of haplotype blocks that are incorrectly phased. Insights from these results are used to develop a haplotype estimator based on a consensus of three tools. The consensus estimator achieved the most accurate phasing in all applied tests. Individually, EAGLE2, BEAGLE and SHAPEIT2 alternate in being the best performing tool in different scenarios. Determining haplotype blocks based on linkage disequilibrium leads to more correctly phased blocks compared to a sliding window approach. We find that there is little difference between phasing sections of a genome (e.g. a gene) compared to phasing entire chromosomes. Finally, we show that the location of phasing error varies when the tools are applied to the same data several times, a finding that could be important for downstream analyses.Conclusions: The choice of phasing and block determination algorithms and their interaction impacts the accuracy of phased haplotype blocks. This work provides guidance and evidence for the different design choices needed for analyses using haplotype blocks. The study highlights a number of issues that may have limited the replicability of previous haplotype analysis.