Institute for Systems Biology, Seattle, WA 98109, USA.
Bioinformatics. 2011 Nov 15;27(22):3216-7. doi: 10.1093/bioinformatics/btr540. Epub 2011 Sep 28.
With the rapidly expanding availability of data from personal genomes, exomes and transcriptomes, medical researchers will frequently need to test whether observed genomic variants are novel or known. This task requires downloading and handling large and diverse datasets from a variety of sources, and processing them with bioinformatics tools and pipelines. Alternatively, researchers can upload data to online tools, which may conflict with privacy requirements. We present here Kaviar, a tool that greatly simplifies the assessment of novel variants. Kaviar includes: (i) an integrated and growing database of genomic variation from diverse sources, including over 55 million variants from personal genomes, family genomes, transcriptomes, SNV databases and population surveys; and (ii) software for querying the database efficiently.
随着个人基因组、外显子组和转录组数据的迅速增加,医学研究人员将经常需要测试观察到的基因组变体是否为新的或已知的。这项任务需要从各种来源下载和处理大量且不同的数据集,并使用生物信息学工具和管道对其进行处理。或者,研究人员可以将数据上传到在线工具,这可能会与隐私要求相冲突。我们在这里介绍 Kaviar,这是一种大大简化新型变体评估的工具。Kaviar 包括:(i) 来自不同来源的基因组变异的集成和不断增长的数据库,包括来自个人基因组、家系基因组、转录组、单核苷酸变异数据库和人群调查的超过 5500 万个变异;以及 (ii) 用于高效查询数据库的软件。