Recent sequencing of the human and other mammalian genomes has brought about the necessity to align them, to identify and characterize their commonalities and differences. Programs that align whole genomes generally use a seed-and-extend technique, starting from exact or near-exact matches and selecting a reliable subset of these, called anchors, and then filling in the remaining portions between the anchors using a combination of local and global alignment algorithms, but their choices for the parameters so far have been primarily heuristic. We present a statistical framework and practical methods for selecting a set of matches that is both sensitive and specific and can constitute a reliable set of anchors for a one-to-one mapping of two genomes from which a whole-genome alignment can be built. Starting from exact matches, we introduce a novel per-base repeat annotation, the $Z$-score, from which noise and repeat filtering conditions are explored. Dynamic programming-based chaining algorithms are also evaluated as context-based filters. We apply the methods described here to the comparison of two progressive assemblies of the human genome, NCBI build 28 and build 34 http://genome.ucsc.edu), and show that a significant portion of the two genomes can be found in selected exact matches, with very limited amount of sequence duplication.
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机译：人类和其他哺乳动物基因组的最新测序带来了对它们进行比对，鉴定和表征其共性和差异的必要性。对齐整个基因组的程序通常使用种子扩展技术，从精确或接近精确的匹配开始，选择一个可靠的子集，称为锚，然后使用局部和局部组合填充锚之间的其余部分。全局对齐算法，但到目前为止，它们对参数的选择主要是启发式的。我们提供了一个统计框架和实用的方法，用于选择一组既敏感又特异的匹配项，可以构成一组可靠的锚，用于两个基因组的一对一映射，从中可以构建全基因组比对。从完全匹配开始，我们介绍了一种新颖的每碱基重复注释，即$ Z $分数，从中可以探讨噪声和重复过滤条件。基于动态编程的链接算法也被评估为基于上下文的过滤器。我们将此处描述的方法用于比较人类基因组的两个渐进装配，即NCBI build 28和build 34 http://genome.ucsc.edu ），并表明在选定的精确匹配中可以找到两个基因组，序列重复的数量非常有限。
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