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在基因组距离中的插入缺失的权重。

On the weight of indels in genomic distances.

机构信息

Instituto Nacional de Metrologia, Qualidade e Tecnologia, Duque de Caxias, 25250-020, Brazil.

出版信息

BMC Bioinformatics. 2011 Oct 5;12 Suppl 9(Suppl 9):S13. doi: 10.1186/1471-2105-12-S9-S13.

Abstract

BACKGROUND

Classical approaches to compute the genomic distance are usually limited to genomes with the same content, without duplicated markers. However, differences in the gene content are frequently observed and can reflect important evolutionary aspects. A few polynomial time algorithms that include genome rearrangements, insertions and deletions (or substitutions) were already proposed. These methods often allow a block of contiguous markers to be inserted, deleted or substituted at once but result in distance functions that do not respect the triangular inequality and hence do not constitute metrics.

RESULTS

In the present study we discuss the disruption of the triangular inequality in some of the available methods and give a framework to establish an efficient correction for two models recently proposed, one that includes insertions, deletions and double cut and join (DCJ) operations, and one that includes substitutions and DCJ operations.

CONCLUSIONS

We show that the proposed framework establishes the triangular inequality in both distances, by summing a surcharge on indel operations and on substitutions that depends only on the number of markers affected by these operations. This correction can be applied a posteriori, without interfering with the already available formulas to compute these distances. We claim that this correction leads to distances that are biologically more plausible.

摘要

背景

经典的基因组距离计算方法通常仅限于具有相同内容、没有重复标记的基因组。然而,基因内容的差异经常被观察到,并且可以反映重要的进化方面。已经提出了一些包括基因组重排、插入和缺失(或替换)的多项式时间算法。这些方法通常允许一次插入、删除或替换连续的标记块,但得到的距离函数不遵守三角形不等式,因此不构成度量。

结果

在本研究中,我们讨论了一些现有方法中三角形不等式的破坏,并给出了一个框架,以建立最近提出的两种模型的有效校正,一种包括插入、删除和双切接(DCJ)操作,另一种包括替换和 DCJ 操作。

结论

我们表明,所提出的框架通过对插入缺失操作和替换操作的附加费用求和来建立两个距离的三角形不等式,该附加费用仅取决于这些操作所影响的标记数量。该校正可以在事后应用,而不会干扰已经存在的计算这些距离的公式。我们声称,这种校正导致了更符合生物学的距离。

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