Genomic dark matter: the reliability of short read mapping illustrated by the genome mappability score.
Genomic dark matter: the reliability of short read mapping illustrated by the genome mappability score.
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基因组暗物质：基因组映射分数所说明的简读映射的可靠性。
DOI：
10.1093/bioinformatics/bts330
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发表时间：
2012-08-15
期刊：
影响因子：
--
通讯作者：
Schatz MC
中科院分区：
文献类型：
--
作者：
Lee H;Schatz MC
动机：基因组重测序和短读图谱是基因组学的两个主要工具，并被用于许多重要的应用。目前最先进的测绘方法是使用质量值和测绘质量分数来评估测绘的可靠性。然而，这些属性被分配给单独的读数，并不直接测量整个基因组中有问题的重复。在这里，我们提出了基因组可映射性分数(GMS)作为一种新的衡量基因组重新测序复杂性的指标。GMS是一个加权概率，即任何读数都可以明确地映射到给定的位置，从而衡量基因组本身的整体组成。结果：我们开发了基因组图谱分析仪，可以计算基因组中每个位置的GMS。它利用云计算的并行性来分析大型基因组，并使我们能够识别出5%-14%的人类、老鼠、苍蝇和酵母基因组，这些基因组很难通过短读取来分析。我们在GMS的背景下检查了广泛使用的BWA/SamTools多态发现管道的准确性，发现发现错误以假阴性为主，特别是在GMS较差的地区。这些错误是测绘过程的基础，不能通过扩大覆盖面来克服。因此，在每个重新测序项目中都应该考虑GMS，以精确定位基因组的“暗物质”，包括这些区域中已知的临床相关变异。可获得性：几种模式生物的源代码和概况可在http://gma-bio.sourceforge.net上获得联系方式：hlee@cshl.edu补充信息：补充数据可在生物信息学在线上获得。
Motivation: Genome resequencing and short read mapping are two of the primary tools of genomics and are used for many important applications. The current state-of-the-art in mapping uses the quality values and mapping quality scores to evaluate the reliability of the mapping. These attributes, however, are assigned to individual reads and do not directly measure the problematic repeats across the genome. Here, we present the Genome Mappability Score (GMS) as a novel measure of the complexity of resequencing a genome. The GMS is a weighted probability that any read could be unambiguously mapped to a given position and thus measures the overall composition of the genome itself. Results: We have developed the Genome Mappability Analyzer to compute the GMS of every position in a genome. It leverages the parallelism of cloud computing to analyze large genomes, and enabled us to identify the 5–14% of the human, mouse, fly and yeast genomes that are difficult to analyze with short reads. We examined the accuracy of the widely used BWA/SAMtools polymorphism discovery pipeline in the context of the GMS, and found discovery errors are dominated by false negatives, especially in regions with poor GMS. These errors are fundamental to the mapping process and cannot be overcome by increasing coverage. As such, the GMS should be considered in every resequencing project to pinpoint the ‘dark matter’ of the genome, including of known clinically relevant variations in these regions. Availability: The source code and profiles of several model organisms are available at http://gma-bio.sourceforge.net Contact: hlee@cshl.edu Supplementary Information: Supplementary data are available at Bioinformatics online.
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