Overcoming bias and systematic errors in next generation sequencing data
Overcoming bias and systematic errors in next generation sequencing data
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DOI：
10.1186/gm208
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发表时间：
2010-01-01
期刊：
影响因子：
12.3
通讯作者：
Irizarry, Rafael A.
中科院分区：
文献类型：
--
作者：
Taub, Margaret A.;Bravo, Hector Corrada;Irizarry, Rafael A.
人们花费了大量的时间和精力来开发分析和质量评估方法，以允许在临床环境中使用微阵列。与微阵列和其他高通量技术的情况一样，来自新高通量测序技术的数据会受到技术和生物学偏差以及系统错误的影响，从而影响下游分析。只有当这些问题能够容易地识别并可靠地调整时，这些新技术的临床应用才可行。尽管该领域仍有许多工作要做，但我们描述了在分析高通量测序数据时应考虑到的一致观察到的偏差。在本文中，我们回顾了有关这些偏差的当前知识，讨论了它们对分析结果的影响，并提出了解决方案。
Considerable time and effort has been spent in developing analysis and quality assessment methods to allow the use of microarrays in a clinical setting. As is the case for microarrays and other high-throughput technologies, data from new high-throughput sequencing technologies are subject to technological and biological biases and systematic errors that can impact downstream analyses. Only when these issues can be readily identified and reliably adjusted for will clinical applications of these new technologies be feasible. Although much work remains to be done in this area, we describe consistently observed biases that should be taken into account when analyzing high-throughput sequencing data. In this article, we review current knowledge about these biases, discuss their impact on analysis results, and propose solutions.