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Documents authored by Braga, Marília D. V.

Document
DOI: 10.4230/LIPIcs.WABI.2022.13
A Linear Time Algorithm for an Extended Version of the Breakpoint Double Distance

Authors: Marília D. V. Braga, Leonie R. Brockmann, Katharina Klerx, and Jens Stoye

Published in: LIPIcs, Volume 242, 22nd International Workshop on Algorithms in Bioinformatics (WABI 2022)

Abstract
Two genomes over the same set of gene families form a canonical pair when each of them has exactly one gene from each family. A genome is circular when it contains only circular chromosomes. Different distances of canonical circular genomes can be derived from a structure called breakpoint graph, which represents the relation between the two given genomes as a collection of cycles of even length. Then, the breakpoint distance is equal to n-c_2, where n is the number of genes and c_2 is the number of cycles of length 2. Similarly, when the considered rearrangements are those modeled by the double-cut-and-join (DCJ) operation, the rearrangement distance is n-c, where c is the total number of cycles. The distance problem is a basic unit for several other combinatorial problems related to genome evolution and ancestral reconstruction, such as median or double distance. Interestingly, both median and double distance problems can be solved in polynomial time for the breakpoint distance, while they are NP-hard for the rearrangement distance. One way of exploring the complexity space between these two extremes is to consider a σ_k distance, defined to be n-(c_2+c_4+…+c_k), and increasingly investigate the complexities of median and double distance for the σ₄ distance, then the σ₆ distance, and so on. While for the median much effort was done in our and in other research groups but no progress was obtained even for the σ₄ distance, for solving the double distance under σ₄ and σ₆ distances we could devise linear time algorithms, which we present here.
Cite as

Marília D. V. Braga, Leonie R. Brockmann, Katharina Klerx, and Jens Stoye. A Linear Time Algorithm for an Extended Version of the Breakpoint Double Distance. In 22nd International Workshop on Algorithms in Bioinformatics (WABI 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 242, pp. 13:1-13:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{braga_et_al:LIPIcs.WABI.2022.13,
  author =	{Braga, Mar{\'\i}lia D. V. and Brockmann, Leonie R. and Klerx, Katharina and Stoye, Jens},
  title =	{{A Linear Time Algorithm for an Extended Version of the Breakpoint Double Distance}},
  booktitle =	{22nd International Workshop on Algorithms in Bioinformatics (WABI 2022)},
  pages =	{13:1--13:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-243-3},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{242},
  editor =	{Boucher, Christina and Rahmann, Sven},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2022.13},
  URN =		{urn:nbn:de:0030-drops-170472},
  doi =		{10.4230/LIPIcs.WABI.2022.13},
  annote =	{Keywords: Comparative genomics, genome rearrangement, breakpoint distance, double-cut-and-join (DCJ) distance, double distance}
}
Document
DOI: 10.4230/LIPIcs.WABI.2022.24
Gene Orthology Inference via Large-Scale Rearrangements for Partially Assembled Genomes

Authors: Diego P. Rubert and Marília D. V. Braga

Published in: LIPIcs, Volume 242, 22nd International Workshop on Algorithms in Bioinformatics (WABI 2022)

Abstract
Recently we developed a gene orthology inference tool based on genome rearrangements (Journal of Bioinformatics and Computational Biology 19:6, 2021). Given a set of genomes our method first computes all pairwise gene similarities. Then it runs pairwise ILP comparisons to compute optimal gene matchings, which minimize, by taking the similarities into account, the weighted rearrangement distance between the analyzed genomes (a problem that is NP-hard). The gene matchings are then integrated into gene families in the final step. Although the ILP is quite efficient and could conceptually analyze genomes that are not completely assembled but split in several contigs, our tool failed in completing that task. The main reason is that each ILP pairwise comparison includes an optimal capping that connects each end of a linear segment of one genome to an end of a linear segment in the other genome, producing an exponential increase of the search space. In this work, we design and implement a heuristic capping algorithm that replaces the optimal capping by clustering (based on their gene content intersections) the linear segments into m ≥ 1 subsets, whose ends are capped independently. Furthermore, in each subset, instead of allowing all possible connections, we let only the ends of content-related segments be connected. Although there is no guarantee that m is much bigger than one, and with the possible side effect of resulting in sub-optimal instead of optimal gene matchings, the heuristic works very well in practice, from both the speed performance and the quality of computed solutions. Our experiments on real data show that we can now efficiently analyze fruit fly genomes with unfinished assemblies distributed in hundreds or even thousands of contigs, obtaining orthologies that are more similar to FlyBase orthologies when compared to orthologies computed by other inference tools. Moreover, for complete assemblies the version with heuristic capping reports orthologies that are very similar to the orthologies computed by the optimal version of our tool. Our approach is implemented into a pipeline incorporating the pre-computation of gene similarities.
Cite as

Diego P. Rubert and Marília D. V. Braga. Gene Orthology Inference via Large-Scale Rearrangements for Partially Assembled Genomes. In 22nd International Workshop on Algorithms in Bioinformatics (WABI 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 242, pp. 24:1-24:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{rubert_et_al:LIPIcs.WABI.2022.24,
  author =	{Rubert, Diego P. and Braga, Mar{\'\i}lia D. V.},
  title =	{{Gene Orthology Inference via Large-Scale Rearrangements for Partially Assembled Genomes}},
  booktitle =	{22nd International Workshop on Algorithms in Bioinformatics (WABI 2022)},
  pages =	{24:1--24:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-243-3},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{242},
  editor =	{Boucher, Christina and Rahmann, Sven},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2022.24},
  URN =		{urn:nbn:de:0030-drops-170586},
  doi =		{10.4230/LIPIcs.WABI.2022.24},
  annote =	{Keywords: Comparative genomics, double-cut-and-join, indels, gene orthology}
}
Document
DOI: 10.4230/LIPIcs.WABI.2020.3
Natural Family-Free Genomic Distance

Authors: Diego P. Rubert, Fábio V. Martinez, and Marília D. V. Braga

Published in: LIPIcs, Volume 172, 20th International Workshop on Algorithms in Bioinformatics (WABI 2020)

Abstract
A classical problem in comparative genomics is to compute the rearrangement distance, that is the minimum number of large-scale rearrangements required to transform a given genome into another given genome. While the most traditional approaches in this area are family-based, i.e., require the classification of DNA fragments of both genomes into families, more recently an alternative model was proposed, which, instead of family classification, simply uses the pairwise similarities between DNA fragments of both genomes to compute their rearrangement distance. This model represents structural rearrangements by the generic double cut and join (DCJ) operation and is then called family-free DCJ distance. It computes the DCJ distance between the two genomes by searching for a matching of their genes based on the given pairwise similarities, therefore helping to find gene homologies. The drawback is that its computation is NP-hard. Another point is that the family-free DCJ distance must correspond to a maximal matching of the genes, due to the fact that unmatched genes are just ignored: maximizing the matching prevents the free lunch artifact of having empty or almost empty matchings giving the smaller distances. In this paper, besides DCJ operations, we allow content-modifying operations of insertions and deletions of DNA segments and propose a new and more general family-free genomic distance. In our model we use the pairwise similarities to assign weights to both matched and unmatched genes, so that an optimal solution does not necessarily maximize the matching. Our model then results in a natural family-free genomic distance, that takes into consideration all given genes and has a search space composed of matchings of any size. We provide an efficient ILP formulation to solve it, by extending the previous formulations for computing family-based genomic distances from Shao et al. (J. Comput. Biol., 2015) and Bohnenkämper et al. (Proc. of RECOMB, 2020). Our experiments show that the ILP can handle not only bacterial genomes, but also fungi and insects, or sets of chromosomes of mammals and plants. In a comparison study of six fruit fly genomes, we obtained accurate results.
Cite as

Diego P. Rubert, Fábio V. Martinez, and Marília D. V. Braga. Natural Family-Free Genomic Distance. In 20th International Workshop on Algorithms in Bioinformatics (WABI 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 172, pp. 3:1-3:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{rubert_et_al:LIPIcs.WABI.2020.3,
  author =	{Rubert, Diego P. and Martinez, F\'{a}bio V. and Braga, Mar{\'\i}lia D. V.},
  title =	{{Natural Family-Free Genomic Distance}},
  booktitle =	{20th International Workshop on Algorithms in Bioinformatics (WABI 2020)},
  pages =	{3:1--3:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-161-0},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{172},
  editor =	{Kingsford, Carl and Pisanti, Nadia},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2020.3},
  URN =		{urn:nbn:de:0030-drops-127926},
  doi =		{10.4230/LIPIcs.WABI.2020.3},
  annote =	{Keywords: Comparative genomics, Genome rearrangement, DCJ-indel distance}
}
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