Illumina, 9885 Towne Centre Drive, San Diego, CA 92121, USA.
Science. 2011 Feb 11;331(6018):728-9. doi: 10.1126/science.1197891.
Many of the challenges in genomics derive from the informatics needed to store and analyze the raw sequencing data that is available from highly multiplexed sequencing technologies. Because single week-long sequencing runs today can produce as much data as did entire genome centers a few years ago, the need to process terabytes of information has become de rigueur for many labs engaged in genomic research. The availability of deep (and large) genomic data sets raises concerns over information access, data security, and subject/patient privacy that must be addressed for the field to continue its rapid advances.
基因组学面临的许多挑战都源于存储和分析高通量测序技术所产生的原始测序数据所需的信息学技术。由于如今一个为期一周的测序实验所产生的数据量，已经与几年前整个基因组中心的数据量相当，因此处理 TB 级信息已经成为从事基因组学研究的许多实验室的必要条件。深度（和大型）基因组数据集的出现引发了人们对信息访问、数据安全和受试者/患者隐私的关注，这些问题必须得到解决，该领域才能继续快速发展。
