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An Enrichment Method for Mapping Ambiguous Reads to the Reference Genome for NGS Analysis

机译:用于将模糊读数映射到NGS分析的参考基因组的富集方法

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Mapping short reads to a reference genome is an essential step in many next-generation sequencing (NGS) analysis. In plants with large genomes, a large fraction of the reads can align to multiple locations of the genome with equally good alignment scores. How to map these ambiguous reads to the genome is a challenging problem with big impacts in the downstream analysis. Traditionally, the default method is to assign an ambiguous read randomly to one of the many potential locations. In this study, we explore an enrichment method that assigns an ambiguous read to the location that has produced the most reads among all the potential locations. Our results show that the enrichment method produced better results than the default random method in the discovery of single nucleotide polymorphisms (SNPs). Not only did it produce more SNP markers, but it also produced markers with better quality, which was demonstrated by higher trait-marker correlation in genome-wide association studies (GWAS).
机译:映射短读取到参考基因组是许多下一代测序(NGS)分析中的重要步骤。在具有大基因组的植物中,大部分读数可以与基因组的多个位置对准,具有同样良好的对准分数。如何将这些暧昧的读数映射到基因组是一个具有挑战性的问题,对下游分析的影响很大。传统上,默认方法是随机分配给许多潜在位置之一的模糊读取。在这项研究中,我们探讨了一种丰富的方法,该方法为所有潜在位置中产生最多读数的位置分配了模糊的读取。我们的研究结果表明,富集方法比发现单核苷酸多态性(SNPS)的默认随机方法产生了更好的结果。它不仅产生了更多的SNP标记,而且还产生了具有更好质量的标记,这是通过在基因组 - 宽协会研究(GWAS)中的具有更高的性状标记相关性的表明。

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