PRSice-2: Polygenic Risk Score software for biobank-scale data
PRSice-2: Polygenic Risk Score software for biobank-scale data
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DOI：
10.1093/gigascience/giz082
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发表时间：
2019-07-01
期刊：
影响因子：
9.2
通讯作者：
O'Reilly, Paul F.
中科院分区：
文献类型：
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作者：
Choi, Shing Wan;O'Reilly, Paul F.
t背景：多基因风险评分（PRS）分析已成为生物医学研究的一个组成部分，用于深入了解性状之间的共同病因，控制实验研究中的基因组图谱，以及加强因果推理等一系列应用。目前，生物库项目正在投入大量的努力，以收集大量的遗传和表型数据，为遗传发现和应用提供前所未有的机会。为了处理这种生物库资源提供的大规模数据，需要高效和可扩展的方法和软件。结果：在这里，我们介绍PRSice-2，一个有效的和可扩展的软件程序，用于自动化和简化大规模数据的PRS分析。PRSice-2处理基因分型和插补数据，提供经验关联P值，不受过度拟合导致的通货膨胀的影响，支持不同的遗传模型，并且可以同时评估多个连续和二元目标性状。我们证明，PRSice-2是显着更快，更高效的内存比PRSice-1和替代PRS软件，LDpred和lassosum，同时具有相当的预测能力。结论：随着数据量的增长和PRS的应用变得更加复杂，PRSice-2的效率和功率组合将变得越来越重要，例如，当结合到高维或基于基因集的分析中时。PRSice-2是用C++编写的，带有一个用于绘图的R脚本，可以从http://PRSice.info免费下载。
t Background: Polygenic risk score (PRS) analyses have become an integral part of biomedical research, exploited to gain insights into shared aetiology among traits, to control for genomic profile in experimental studies, and to strengthen causal inference, among a range of applications. Substantial efforts are now devoted to biobank projects to collect large genetic and phenotypic data, providing unprecedented opportunity for genetic discovery and applications. To process the large-scale data provided by such biobank resources, highly efficient and scalable methods and software are required. Results: Here we introduce PRSice-2, an efficient and scalable software program for automating and simplifying PRS analyses on large-scale data. PRSice-2 handles both genotyped and imputed data, provides empirical association P-values free from inflation due to overfitting, supports different inheritance models, and can evaluate multiple continuous and binary target traits simultaneously. We demonstrate that PRSice-2 is dramatically faster and more memory-efficient than PRSice-1 and alternative PRS software, LDpred and lassosum, while having comparable predictive power. Conclusion: PRSice-2's combination of efficiency and power will be increasingly important as data sizes grow and as the applications of PRS become more sophisticated, e.g., when incorporated into high-dimensional or gene set-based analyses. PRSice-2 is written in C++, with an R script for plotting, and is freely available for download from http://PRSice.info.