Rubert Diego P, Doerr Daniel, Braga Marília D V
Faculdade de Computação, Universidade Federal de Mato Grosso do Sul, Campo Grande, Brazil.
Faculty of Medicine, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
J Bioinform Comput Biol. 2021 Dec;19(6):2140014. doi: 10.1142/S021972002140014X. Epub 2021 Nov 13.
Recently, we proposed an efficient ILP formulation [Rubert DP, Martinez FV, Braga MDV, Natural family-free genomic distance, :4, 2021] for exactly computing the rearrangement distance of two genomes in a setting. In such a setting, neither prior classification of genes into families, nor further restrictions on the genomes are imposed. Given two genomes, the mentioned ILP computes an optimal matching of the genes taking into account simultaneously local mutations, given by gene similarities, and large-scale genome rearrangements. Here, we explore the potential of using this ILP for inferring groups of orthologs across several species. More precisely, given a set of genomes, our method first computes all pairwise optimal gene matchings, which are then integrated into gene families in the second step. Our approach is implemented into a pipeline incorporating the pre-computation of gene similarities. It can be downloaded from gitlab.ub.uni-bielefeld.de/gi/FFGC. We obtained promising results with experiments on both simulated and real data.
最近，我们提出了一种高效的整数线性规划（ILP）公式[鲁伯特·DP，马丁内斯·FV，布拉加·MDV，无自然家族的基因组距离，：4，2021]，用于精确计算在一种情况下两个基因组的重排距离。在这种情况下，既不对基因进行预先的家族分类，也不对基因组施加进一步的限制。给定两个基因组，上述ILP会在考虑由基因相似性给出的局部突变以及大规模基因组重排的同时，计算基因的最优匹配。在此，我们探索使用这种ILP推断多个物种间直系同源基因簇的潜力。更确切地说，给定一组基因组，我们的方法首先计算所有成对的最优基因匹配，然后在第二步中将其整合到基因家族中。我们的方法被实现为一个包含基因相似性预计算的流程。它可以从gitlab.ub.uni-bielefeld.de/gi/FFGC下载。我们在模拟数据和真实数据上的实验都取得了有前景的结果。
