HKU-BGI Bioinformatics Algorithms Research Laboratory and Department of Computer Science, University of Hong Kong.
L3 Bioinformatics Limited.
Bioinformatics. 2015 Dec 15;31(24):4035-7. doi: 10.1093/bioinformatics/btv500. Epub 2015 Aug 26.
Rapid advances of next-generation sequencing technology have led to the integration of genetic information with clinical care. Genetic basis of diseases and response to drugs provide new ways of disease diagnosis and safer drug usage. This integration reveals the urgent need for effective and accurate tools to analyze genetic variants. Due to the number and diversity of sources for annotation, automating variant analysis is a challenging task. Here, we present database.bio, a web application that combines variant annotation, prioritization and visualization so as to support insight into the individual genetic characteristics. It enhances annotation speed by preprocessing data on a supercomputer, and reduces database space via a unified database representation with compressed fields.
Freely available at https://database.bio.
下一代测序技术的快速发展导致遗传信息与临床护理的结合。疾病的遗传基础和对药物的反应为疾病诊断和更安全的药物使用提供了新的途径。这种整合凸显了对有效和准确的工具来分析遗传变异的迫切需求。由于注释的来源数量和多样性，自动化变异分析是一项具有挑战性的任务。在这里，我们展示了 database.bio，这是一个将变异注释、优先级排序和可视化相结合的网络应用程序，以支持对个体遗传特征的深入了解。它通过在超级计算机上预处理数据来提高注释速度，并通过使用压缩字段的统一数据库表示来减少数据库空间。
可在 https://database.bio 上免费获得。
