AI 中文总结
针对阿尔茨海默病位点的序列-功能分析输入构建问题，提出HaploPerturb方法，基于群体单倍型的低秩copula构建，在AlphaGenome基准中显著提升小胶质细胞富集度，证明群体知情序列构建的重要性。
AI 中文摘要
序列-功能模型可从完整序列窗口预测分子表型。然而，在全基因组关联研究位点中，主流设计仅扰动参考基因组上的先导变异，即便该先导变异常通过连锁不平衡与附近变异相关联。这种单变异扰动隐含地将所有连锁等位基因固定在参考基因组状态，因此可能产生罕见或未观测到的群体单倍型。我们在38个阿尔茨海默病位点研究该输入构建问题。我们提出HaploPerturb，其使用分阶段的ROS/MAP基因型或欧洲1000 Genomes面板拟合固定边际潜高斯因子模型，并基于每个先导等位基因对伴侣构型进行排序。在严格连锁不平衡阈值下，公共面板构建与供体面板在所有位点一致；在更宽松阈值且限定于共享伴侣时，37个位点中的36个一致。真实模拟显示，在强连锁不平衡下可精确恢复主导构型，并揭示错误设定的单因子模型下存在持续的残留相关性。在针对细胞类型特异性ROS/MAP eQTL的AlphaGenome基准测试中，更广泛的公共面板单倍型产生小胶质细胞富集度为2.07（95%全位点自举百分位区间1.48--3.60），而仅先导编辑的富集度为1.43（0.69--2.29）。经验模式和LD信号背景产生2.20（1.60--3.64），与HaploPerturb的顶部构型相比无显著优势或劣势。因此，在该应用中，群体知情的序列构建很重要，而合理主导单倍型规则之间的选择，其重要性低于单倍型与仅先导参考背景之间的选择。
英文摘要
Sequence-to-function models predict molecular phenotypes from complete sequence windows. At genome-wide association study loci, however, the prevailing design perturbs only the lead variant on the reference genome, even though the lead is often correlated with nearby variants through linkage disequilibrium. This single-variant perturbation implicitly fixes all linked alleles at their reference-genome states and may therefore create an uncommon or unobserved population haplotype. We study this input-construction problem at 38 Alzheimer's disease loci. We introduce HaploPerturb, which uses phased ROS/MAP genotypes or the European 1000 Genomes panel to fit a fixed-margin latent Gaussian factor model and rank partner configurations conditional on each lead allele. The leading public-panel construction agrees with the donor-panel construction at all loci under a strict linkage-disequilibrium threshold and 36 of 37 loci under a broader threshold after restricting to shared partners. Known-truth simulations show exact recovery of the dominant configuration under strong linkage disequilibrium and expose persistent residual correlation under a misspecified one-factor model. In an AlphaGenome benchmark against cell-type-specific ROS/MAP eQTLs, broader-set public-panel haplotypes yield microglial enrichment of 2.07 (95\% whole-locus bootstrap percentile interval 1.48--3.60), compared with 1.43 (0.69--2.29) for a lead-only edit. Empirical-mode and LD-sign backgrounds yield 2.20 (1.60--3.64), with no detectable advantage or loss relative to the HaploPerturb top configuration. Thus population-informed sequence construction matters in this application, while the choice among reasonable leading haplotype rules is less consequential than the choice between a haplotype and a lead-only reference background.
