A heuristic method for fast and accurate phasing and imputation of single-nucleotide polymorphism data in bi-parental plant populations.
A heuristic method for fast and accurate phasing and imputation of single-nucleotide polymorphism data in bi-parental plant populations.
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DOI：
10.1007/s00122-018-3156-9
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发表时间：
2018-11
期刊：
影响因子：
--
通讯作者：
Hickey JM
中科院分区：
文献类型：
--
作者：
Gonen S;Wimmer V;Gaynor RC;Byrne E;Gorjanc G;Hickey JM
关键信息 用于二倍体双亲本植物群体中 SNP 芯片基因型定相和估算的快速准确新方法。 本文提出了一种新的启发式方法，用于二倍体植物物种基因组数据的定相和插补。我们的方法称为 AlphaPlantImpute，明确利用植物育种计划的特征来最大限度地提高插补的准确性。其特征是亲本数量较少，可以近亲交配，通常具有高密度基因组数据，并且很少有重组将亲本与低密度基因分型的焦点个体（即作为插补目标的后代）分开。 AlphaPlantImpute 的工作原理大致分为三个步骤。首先，它鉴定了父母中信息丰富的低密度基因型标记。其次，它跟踪父母等位基因和单倍型向信息标记处的焦点个体的遗传。最后，它使用这种低密度信息作为锚点将焦点个体归因于高密度。我们在不同场景的模拟双亲群体中测试了 AlphaPlantImpute 的插补准确性。我们还将其准确性与名为 PlantImpute 的现有软件进行了比较。一般来说，AlphaPlantImpute 具有比 PlantImpute 更好或相同的插补精度。与 PlantImpute 相比，AlphaPlantImpute 的计算时间和内存需求很小。例如，对于双亲均近交并在每条染色体 25,000 个标记处进行基因分型且焦点 F2 个体在每条染色体上使用 50 个标记进行基因分型的情况，插补准确度为 0.96。此场景的最大内存要求为 0.08 GB，需要 37 秒才能完成。
Key message New fast and accurate method for phasing and imputation of SNP chip genotypes within diploid bi-parental plant populations. This paper presents a new heuristic method for phasing and imputation of genomic data in diploid plant species. Our method, called AlphaPlantImpute, explicitly leverages features of plant breeding programmes to maximise the accuracy of imputation. The features are a small number of parents, which can be inbred and usually have high-density genomic data, and few recombinations separating parents and focal individuals genotyped at low density (i.e. descendants that are the imputation targets). AlphaPlantImpute works roughly in three steps. First, it identifies informative low-density genotype markers in parents. Second, it tracks the inheritance of parental alleles and haplotypes to focal individuals at informative markers. Finally, it uses this low-density information as anchor points to impute focal individuals to high density. We tested the imputation accuracy of AlphaPlantImpute in simulated bi-parental populations across different scenarios. We also compared its accuracy to existing software called PlantImpute. In general, AlphaPlantImpute had better or equal imputation accuracy as PlantImpute. The computational time and memory requirements of AlphaPlantImpute were tiny compared to PlantImpute. For example, accuracy of imputation was 0.96 for a scenario where both parents were inbred and genotyped at 25,000 markers per chromosome and a focal F2 individual was genotyped with 50 markers per chromosome. The maximum memory requirement for this scenario was 0.08 GB and took 37 s to complete.
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影响因子：
2.9
作者：
VanRaden PM;Sun C;O'Connell JR
通讯作者：
O'Connell JR
DOI：
10.1186/1297-9686-43-12
发表时间：
2011-03-10
期刊：
Genetics, selection, evolution : GSE
影响因子：
--
作者：
Hickey JM;Kinghorn BP;Tier B;Wilson JF;Dunstan N;van der Werf JH
通讯作者：
van der Werf JH
影响因子：
30.8
作者：
Loh, Po-Ru;Danecek, Petr;Palamara, Pier Francesco;Fuchsberger, Christian;Reshef, Yakir A.;Finucane, Hilary K.;Schoenherr, Sebastian;Forer, Lukas;McCarthy, Shane;Abecasis, Goncalo R.;Durbin, Richard;Price, Alkes L.
通讯作者：
Price, Alkes L.
影响因子：
2.3
作者：
Jacobson, Amy;Lian, Lian;Bernardo, Rex
通讯作者：
Bernardo, Rex
影响因子：
2.1
作者：
Li, Yun;Willer, Cristen J.;Ding, Jun;Scheet, Paul;Abecasis, Goncalo R.
通讯作者：
Abecasis, Goncalo R.