Skip to main content

Unique Least Common Ancestors and Clusters in Directed Acyclic Graphs

  • Conference paper
  • First Online:
Algorithms and Discrete Applied Mathematics (CALDAM 2024)

Abstract

We investigate the connections between clusters and least common ancestors (LCAs) in directed acyclic graphs (DAGs). We focus on the class of DAGs having unique least common ancestors for certain subsets of their minimal elements since these are of interest, particularly as models of phylogenetic networks. Here, we use the close connection between the canonical k-ary transit function and the closure function on a set system to show that pre-k-ary clustering systems are exactly those that derive from a class of DAGs with unique LCAs. Moreover, we show that k-ary \(\mathscr {T}\)-systems and k-weak hierarchies are associated with DAGs that satisfy stronger conditions on the existence of unique LCAs for sets of size at most k.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 59.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 74.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Bandelt, H.J., Dress, A.W.M.: Weak hierarchies associated with similarity measures – an additive clustering technique. Bull. Math. Biol. 51, 133–166 (1989). https://doi.org/10.1007/BF02458841

    Article  MathSciNet  Google Scholar 

  2. Bandelt, H.J., Dress, A.W.M.: An order theoretic framework for overlapping clustering. Discret. Math. 136, 21–37 (1994). https://doi.org/10.1016/0012-365X(94)00105-R

    Article  MathSciNet  Google Scholar 

  3. Barthélemy, J.P., Brucker, F.: Binary clustering. Discret. Appl. Math. 156(8), 1237–1250 (2008). https://doi.org/10.1016/j.dam.2007.05.024

    Article  MathSciNet  Google Scholar 

  4. Bender, M.A., Pemmasani, G., Skiena, S., Sumazin, P.: Finding least common ancestors in directed acyclic graphs. In: Proceedings of the 12th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2001, pp. 845–853. Society for Industrial and Applied Mathematics, Washington, D.C., USA (2001). https://doi.org/10.5555/365411.365795

  5. Bertrand, P., Diatta, J.: Multilevel clustering models and interval convexities. Discret. Appl. Math. 222, 54–66 (2017). https://doi.org/10.1016/j.dam.2016.12.019

    Article  MathSciNet  Google Scholar 

  6. Changat, M., Mathews, J., Peterin, I., Narasimha-Shenoi, P.G.: \(n\)-ary transit functions in graphs. Discussiones Math. Graph Th. 30(4), 671–685 (2010). https://eudml.org/doc/270794

  7. Changat, M., Narasimha-Shenoi, P.G., Stadler, P.F.: Axiomatic characterization of transit functions of weak hierarchies. Art Discret. Appl. Math. 2, P1.01 (2019). https://doi.org/10.26493/2590-9770.1260.989

  8. Changat, M., Shanavas, A.V., Stadler, P.F.: Transit functions and pyramid-like binary clustering systems. Technical report. 2212.08721, arXiv (2023). https://doi.org/10.48550/arXiv.2212.08721

  9. Dress, A.: Towards a theory of holistic clustering. In: Mirkin, B., McMorris, F.R., Roberts, F.S., Rzhetsky, A. (eds.) Mathematical Hierarchies and Biology. DIMACS Series in Discrete Mathematics and Theoretical Computer Science, vol. 37, pp. 271–290. American Mathematical Society (1996)

    Google Scholar 

  10. Hellmuth, M., Schaller, D., Stadler, P.F.: Clustering systems of phylogenetic networks. Theory Biosci. 142(4), 301–358 (2023). https://doi.org/10.1007/s12064-023-00398-w

    Article  Google Scholar 

  11. Huson, D.H., Scornavacca, C.: A survey of combinatorial methods for phylogenetic networks. Genome Biol. Evol. 3, 23–35 (2011). https://doi.org/10.1093/gbe/evq077

    Article  Google Scholar 

  12. Nakhleh, L., Wang, L.-S.: Phylogenetic networks: properties and relationship to trees and clusters. In: Priami, C., Zelikovsky, A. (eds.) Transactions on Computational Systems Biology II. LNCS, vol. 3680, pp. 82–99. Springer, Heidelberg (2005). https://doi.org/10.1007/11567752_6

    Chapter  Google Scholar 

  13. Nebeský, L.: On a certain numbering of the vertices of a hypergraph. Czechoslovak Math. J. 33, 1–6 (1983). https://doi.org/10.21136/CMJ.1983.101849

Download references

Acknowledgments

AVS acknowledges the financial support from the CSIR-HRDG for the Senior Research Fellowship (09/0102(12336)/2021-EMR-I).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Manoj Changat .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Shanavas, A.V., Changat, M., Hellmuth, M., Stadler, P.F. (2024). Unique Least Common Ancestors and Clusters in Directed Acyclic Graphs. In: Kalyanasundaram, S., Maheshwari, A. (eds) Algorithms and Discrete Applied Mathematics. CALDAM 2024. Lecture Notes in Computer Science, vol 14508. Springer, Cham. https://doi.org/10.1007/978-3-031-52213-0_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-52213-0_11

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-52212-3

  • Online ISBN: 978-3-031-52213-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics