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Graphical pan-genome analysis with compressed suffix trees and the Burrows-Wheeler transform

机译:带有压缩后缀树和Burrows-Wheeler变换的图形化全基因组分析

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Motivation: Low-cost genome sequencing gives unprecedented complete information about the genetic structure of populations, and a population graph captures the variations between many individuals of a population. Recently, Marcus et al. proposed to use a compressed de Bruijn graph for representing an entire population of genomes. They devised an O(n log g) time algorithm called splitMEM that constructs this graph directly (i.e. without using the uncompressed de Bruijn graph) based on a suffix tree, where n is the total length of the genomes and g is the length of the longest genome. Since the applicability of their algorithm is limited to rather small datasets, there is a strong need for space-efficient construction algorithms.
机译:动机:低成本的基因组测序可提供有关种群遗传结构的前所未有的完整信息,并且种群图可捕获种群中许多个体之间的变异。最近,Marcus等人。提出使用压缩的de Bruijn图表示整个基因组。他们设计了一种称为splitMEM的O(n log g)时间算法,该算法基于后缀树直接构造该图(即,不使用未压缩的de Bruijn图),其中n是基因组的总长度,g是基因组的长度。最长的基因组。由于其算法的适用性仅限于相当小的数据集,因此非常需要节省空间的构造算法。

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