在组织相容性中分布人类白细胞抗原(HLA)数据库:HLA数据管理的转变

Sirine Sayadi, Venceslas Douillard, N. Vince, Mario Südholt, P. Gourraud
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摘要

目的:人类白细胞抗原(HLA)群体遗传学是一个历史领域的集中数据资源。HLA遗传数据库通常有助于获取等位基因、单倍型和基因型格式信息的频率。在众多资源中,等位基因频率网络数据库(AFND)是一个典型的集中式存储库,允许用户研究和分析世界各地不同人群的免疫基因频率。随着医疗数据的大量增加和数据治理法规的加强,为群体遗传学中的历史集中式方法提出一种新的分布式和安全模型变得非常重要。本文提出了一种新的HLA群体遗传资源模型,即HLA数据库的替代分布式版本。它允许用户在不共享原始数据和监控数据访问的情况下与其他远程站点执行相同的研究和分析。方法:新版本采用Master/Worker分布模型,提供了计算等位基因频率、单倍型频率和个体基因型计算的分布式算法。在实验驱动研究网格5000的分布式测试平台上对新模型进行了评估,与研究人员使用的原始集中式方案相比,在精度和执行时间方面取得了良好的效果。结果:将分布式算法应用于HLA群体遗传资源,实现了对资源使用的控制,增强了数据拥有机构的安全框架。对群体免疫遗传学中各种计数方法给出了相同的结果。对于相同频率的估计,它在许多情况下产生更快的计算时间,特别是对于大样本。结论:分配以前集中的资源是一个有趣的视角,可以更好地控制数据共享。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distributing human leukocyte antigen (HLA) database in histocompatibility: a shift in HLA data governance
Aim: Human leukocyte antigen (HLA) population genetics has been a historical field centralizing data resource. HLA genetics databases typically facilitate access to frequencies of allele, haplotype, and genotype format information. Among many resources, the Allele Frequency Net Database (AFND) is a typical centralized repository that allows users to research and analyze immune gene frequencies in different populations around the world. With the massive increase in medical data and the strengthening of data governance laws, the proposal for a new distributed and secure model for the historical centralization method in population genetics has become important. In this paper, a new model of HLA population genetic resources, an alternative distributed version of HLA databases has been developed. It allows users to perform the same research and analysis with other remote sites without sharing their original data and monitoring data access. Methods: This new version uses the Master/Worker distributed model and offers distributed algorithms for the calculation of allelic frequencies, haplotypic frequencies and for individual genotypic calculations. The new model was evaluated on a distributed testbed for experiment-driven research Grid’5000 and has obtained good results of accuracy and execution time compared to the original centralized scheme used by researchers. Results: The results show that distributed algorithm applied to HLA population genetics resources enables usage control and enables enforcing the security framework of the data-owning institution. It gives the same results for all counting methods in population immunogenetics. With the same frequencies’ estimations, it yields a much quicker computation time in many cases, in particular for large samples. Conclusions: Distributing previously centralized resources is an interesting perspective enhancing better control of data sharing.
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