Fast and Robust Identity-by-Descent Inference with the Templated Positional Burrows-Wheeler Transform.
Fast and Robust Identity-by-Descent Inference with the Templated Positional Burrows-Wheeler Transform.
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DOI：
10.1093/molbev/msaa328
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发表时间：
2021-05-04
影响因子：
10.7
通讯作者：
Auton A
中科院分区：
文献类型：
--
作者：
Freyman WA;McManus KF;Shringarpure SS;Jewett EM;Bryc K;23 and Me Research Team;Auton A
在许多遗传分析中，估计个体间血统相同（IBD）片段的基因组位置和长度是至关重要的一步。然而，生物库和直接面向消费者的基因数据集的规模呈指数级增长，使得准确的IBD推断成为一个重大的计算挑战。在这里，我们提出了模板定位Burrows-Wheeler变换（TPBWT），使快速IBD估计对基因型和相位误差具有鲁棒性。通过对具有真实基因分型和相位误差的谱系进行单倍型数据模拟，我们发现TPBWT在速度和准确性方面优于其他最先进的IBD推理算法。对于每一种相位感知方法，我们探索了通过片段长度推断IBD的假阳性和假阴性率，并描述了常见的错误类型。我们的结果突出了大多数阶段性IBD推理方法的脆弱性；IBD估计的准确性可能对单倍型相位的质量高度敏感。此外，我们比较了TPBWT与广泛使用的无相位IBD推理方法的性能，该方法对相位误差具有鲁棒性。我们介绍了样本内和样本外基于tpbwt的IBD推理算法，并展示了它们在具有数百万样本的大规模数据集上的计算效率。此外，我们描述了tpbwt压缩单倍型的二进制文件格式，可以针对非常大的队列面板快速有效地计算样本外IBD。最后，我们在一个简短的实证分析中展示了TPBWT的效用，探索了墨西哥境内单倍型共享的地理模式。墨西哥各地区共有IBD的分层聚类揭示了地理结构的单倍型共享和距离隔离的强烈信号。我们的TPBWT软件实现可以在代码库（https://github.com/23andMe/phasedibd，最后一次访问于2021年1月11日）中免费用于非商业用途。
Estimating the genomic location and length of identical-by-descent (IBD) segments among individuals is a crucial step in many genetic analyses. However, the exponential growth in the size of biobank and direct-to-consumer genetic data sets makes accurate IBD inference a significant computational challenge. Here we present the templated positional Burrows–Wheeler transform (TPBWT) to make fast IBD estimates robust to genotype and phasing errors. Using haplotype data simulated over pedigrees with realistic genotyping and phasing errors, we show that the TPBWT outperforms other state-of-the-art IBD inference algorithms in terms of speed and accuracy. For each phase-aware method, we explore the false positive and false negative rates of inferring IBD by segment length and characterize the types of error commonly found. Our results highlight the fragility of most phased IBD inference methods; the accuracy of IBD estimates can be highly sensitive to the quality of haplotype phasing. Additionally, we compare the performance of the TPBWT against a widely used phase-free IBD inference approach that is robust to phasing errors. We introduce both in-sample and out-of-sample TPBWT-based IBD inference algorithms and demonstrate their computational efficiency on massive-scale data sets with millions of samples. Furthermore, we describe the binary file format for TPBWT-compressed haplotypes that results in fast and efficient out-of-sample IBD computes against very large cohort panels. Finally, we demonstrate the utility of the TPBWT in a brief empirical analysis, exploring geographic patterns of haplotype sharing within Mexico. Hierarchical clustering of IBD shared across regions within Mexico reveals geographically structured haplotype sharing and a strong signal of isolation by distance. Our software implementation of the TPBWT is freely available for noncommercial use in the code repository (https://github.com/23andMe/phasedibd, last accessed January 11, 2021).
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DOI：
10.1126/science.1251688
发表时间：
2014-06-13
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Moreno-Estrada A;Gignoux CR;Fernández-López JC;Zakharia F;Sikora M;Contreras AV;Acuña-Alonzo V;Sandoval K;Eng C;Romero-Hidalgo S;Ortiz-Tello P;Robles V;Kenny EE;Nuño-Arana I;Barquera-Lozano R;Macín-Pérez G;Granados-Arriola J;Huntsman S;Galanter JM;Via M;Ford JG;Chapela R;Rodriguez-Cintron W;Rodríguez-Santana JR;Romieu I;Sienra-Monge JJ;del Rio Navarro B;London SJ;Ruiz-Linares A;Garcia-Herrera R;Estrada K;Hidalgo-Miranda A;Jimenez-Sanchez G;Carnevale A;Soberón X;Canizales-Quinteros S;Rangel-Villalobos H;Silva-Zolezzi I;Burchard EG;Bustamante CD
通讯作者：
Bustamante CD
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.
逐渐映射的身份映射以检测稀有变体，赋予多发性硬化症的敏感性。
影响因子：
3.7
作者：
Lin R;Charlesworth J;Stankovich J;Perreau VM;Brown MA;ANZgene Consortium;Taylor BV
通讯作者：
Taylor BV
影响因子：
7
作者：
Li, Heng;Ruan, Jue;Durbin, Richard
通讯作者：
Durbin, Richard
影响因子：
2.6
作者：
Chiang, Charleston W. K.;Ralph, Peter;Novembre, John
通讯作者：
Novembre, John