利用 SRMA 对短读长下一代测序数据进行局部重比对以提高变异发现。
Improved variant discovery through local re-alignment of short-read next-generation sequencing data using SRMA.
机构信息
Department of Computer Science, University of California, Los Angeles, Boelter Hall, Los Angeles, CA 90095, USA.
出版信息
Genome Biol. 2010;11(10):R99. doi: 10.1186/gb-2010-11-10-r99. Epub 2010 Oct 8.
A primary component of next-generation sequencing analysis is to align short reads to a reference genome, with each read aligned independently. However, reads that observe the same non-reference DNA sequence are highly correlated and can be used to better model the true variation in the target genome. A novel short-read micro realigner, SRMA, that leverages this correlation to better resolve a consensus of the underlying DNA sequence of the targeted genome is described here.
新一代测序分析的一个主要组成部分是将短读段比对到参考基因组上,每个读段都是独立比对的。然而,观察到相同的非参考 DNA 序列的读段高度相关,可以用来更好地模拟目标基因组中的真实变异。本文描述了一种新的短读段微重对齐方法 SRMA,它利用这种相关性来更好地确定目标基因组的潜在 DNA 序列的共识。
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