小柯机器人

美国麻省理工学院和哈佛大学布罗德研究所Luke J. O’Connor、Pouria Salehi Nowbandegani和Anthony Wilder Wohns小组合作取得一项新成果。他们研发出祖先多样性关联研究中连锁不平衡（LD）的极稀疏模型。相关论文于2023年8月28日发表在《自然-遗传学》杂志上。

在本研究中，研究人员引入了LD图形模型（LDGMs），这是LD的一种极稀疏和有效的表示。LDGM中等位基因之间的统计关系对应于单倍体之间的谱系关系。研究揭示了五个人群组中1800万个常见变体（次要等位基因频率>1）的LDGM和种群特异性LDGM精密矩阵，并验证了它们的准确性，实现了常用LD矩阵计算运行时间数量级的改进。

研究人员采用了一种极快的多祖先多基因预测方法BLUPx-ldgm，该方法的性能优于基于参考LD相关矩阵的类似方法。LDGMs可实现复杂分析，并可运用到数百万个变异和个体祖先多样性的遗传关联数据分析。

研究人员表示，连锁不平衡揭示了相邻遗传变异之间的相关性。在遗传关联研究中，LD通常使用大型相关矩阵进行建模，但这种方法效率低下，特别是在祖先多样化研究中。

附：英文原文

Title: Extremely sparse models of linkage disequilibrium in ancestrally diverse association studies

Author: Salehi Nowbandegani, Pouria, Wohns, Anthony Wilder, Ballard, Jenna L., Lander, Eric S., Bloemendal, Alex, Neale, Benjamin M., OConnor, Luke J.

Issue&Volume: 2023-08-28

Abstract: Linkage disequilibrium (LD) is the correlation among nearby genetic variants. In genetic association studies, LD is often modeled using large correlation matrices, but this approach is inefficient, especially in ancestrally diverse studies. In the present study, we introduce LD graphical models (LDGMs), which are an extremely sparse and efficient representation of LD. LDGMs are derived from genome-wide genealogies; statistical relationships among alleles in the LDGM correspond to genealogical relationships among haplotypes. We published LDGMs and ancestry-specific LDGM precision matrices for 18 million common variants (minor allele frequency >1%) in five ancestry groups, validated their accuracy and demonstrated order-of-magnitude improvements in runtime for commonly used LD matrix computations. We implemented an extremely fast multiancestry polygenic prediction method, BLUPx-ldgm, which performs better than a similar method based on the reference LD correlation matrix. LDGMs will enable sophisticated methods that scale to ancestrally diverse genetic association data across millions of variants and individuals.

DOI: 10.1038/s41588-023-01487-8

Source: https://www.nature.com/articles/s41588-023-01487-8

Nature Genetics：《自然—遗传学》，创刊于1992年。隶属于施普林格·自然出版集团，最新IF：41.307
官方网址：https://www.nature.com/ng/
投稿链接：https://mts-ng.nature.com/cgi-bin/main.plex