SLIQ：有效重叠支架的简单线性不等式
SLIQ: Simple Linear Inequalities for Efficient Contig Scaffolding
摘要：
支架是“从头”基因组组装中的一个重要子问题，在“从头”基因组组装中，配偶对数据用于构建由缺口分隔的重叠群的线性序列。在这里，我们提出了SLIQ，一组简单的线性不等式，来自重叠群的几何形状的线，可用于预测的相对位置和方向的重叠群从个别配偶对读取，从而产生重叠群有向图。SLIQ不等式还可以过滤掉不可靠的配偶对，并且可以用作任何脚手架算法的预处理步骤。我们测试了SLIQ不等式的五个真实的数据集，从简单的细菌基因组复杂的哺乳动物基因组的复杂性，并比较结果的多数表决程序所使用的许多其他脚手架算法。SLIQ预测重叠群的相对位置和方向，在所有情况下都具有很高的准确性，并且比复杂基因组，特别是人类基因组的多数投票给出了更准确的位置预测。最后，我们提出了一个简单的支架算法，产生线性支架给定的重叠群有向图。我们表明，我们的算法是非常有效的相比，其他脚手架算法，同时保持高精度预测重叠群的位置和方向的真实数据集。
英文摘要：
Scaffolding is an important subproblem in "de novo" genome assembly in which mate pair data are used to construct a linear sequence of contigs separated by gaps. Here we present SLIQ, a set of simple linear inequalities derived from the geometry of contigs on the line that can be used to predict the relative positions and orientations of contigs from individual mate pair reads and thus produce a contig digraph. The SLIQ inequalities can also filter out unreliable mate pairs and can be used as a preprocessing step for any scaffolding algorithm. We tested the SLIQ inequalities on five real data sets ranging in complexity from simple bacterial genomes to complex mammalian genomes and compared the results to the majority voting procedure used by many other scaffolding algorithms. SLIQ predicted the relative positions and orientations of the contigs with high accuracy in all cases and gave more accurate position predictions than majority voting for complex genomes, in particular the human genome. Finally, we present a simple scaffolding algorithm that produces linear scaffolds given a contig digraph. We show that our algorithm is very efficient compared to other scaffolding algorithms while maintaining high accuracy in predicting both contig positions and orientations for real data sets.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
