Skip to main content
SpringerLink
Log in

Parameter Advising for the Opal Aligner

  • Chapter
  • First Online:
Parameter Advising for Multiple Sequence Alignment

Part of the book series: Computational Biology ((COBO,volume 26))

Abstract

Chapters 1 through 5 described several approaches to constructing a parameter advisor. This chapter demonstrates the performance of the resulting advisors, learned for the Opal aligner, trained on a suite of benchmark reference alignments. Advising performance is compared against the optimal default parameter choice, as well as advisors learned using various accuracy estimators. The results show that Facet yields the best advising accuracy of any estimator currently available, and that by using estimator-aware advisor sets we can significantly increase advising accuracy over using estimator-oblivious oracle sets.

Adapted from publications [24, 26, 33, 56].

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

Access this chapter

Log in via an institution

Institutional subscriptions

References

  1. Ahola, V., Aittokallio, T., Vihinen, M., Uusipaikka, E.: Model-based prediction of sequence alignment quality. Bioinformatics 24(19), 2165–2171 (2008)

    Article  MATH  Google Scholar 

  2. Bahr, A., Thompson, J.D., Thierry, J.C., Poch, O.: BAliBASE (Benchmark Alignment dataBASE): enhancements for repeats, transmembrane sequences and circular permutations. Nucleic Acids Res. 29(1), 323–326 (2001)

    Google Scholar 

  3. Balaji, S., Sujatha, S., Kumar, S.S.C., Srinivasan, N.: PALI: a database of Phylogeny and ALIgnment of homologous protein structures. Nucleic Acids Res. 29(1), 61–65 (2001)

    Google Scholar 

  4. Carrillo, H., Lipman, D.: The multiple sequence alignment problem in biology. SIAM J. Appl. Math. 48(5), 1073–1082 (1988)

    Article  MathSciNet  MATH  Google Scholar 

  5. Chang, J.M., Tommaso, P.D., Notredame, C.: TCS: a new multiple sequence alignment reliability measure to estimate alignment accuracy and improve phylogenetic tree reconstruction. Mol. Biol. Evol. 31(6), 1625–1637 (2014)

    Google Scholar 

  6. DeBlasio, D., Kececioglu, J.: Learning parameter sets for alignment advising. In: Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB), pp. 230–239 (2014)

    Google Scholar 

  7. DeBlasio, D., Kececioglu, J.: Ensemble multiple sequence alignment via advising. In: Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB), pp. 452–461 (2015)

    Google Scholar 

  8. DeBlasio, D.F., Wheeler, T.J., Kececioglu, J.D.: Estimating the accuracy of multiple alignments and its use in parameter advising. In: Proceedings of the 16th Conference on Research in Computational Molecular Biology (RECOMB), pp. 45–59 (2012)

    Google Scholar 

  9. Edgar, R.C.: BENCH (2009). http://www.drive5.com/bench

  10. Gotoh, O.: An improved algorithm for matching biological sequences. J. Mol. Biol. 162(3), 705–508 (1982)

    Article  Google Scholar 

  11. Henikoff, S., Henikoff, J.G.: Amino acid substitution matrices from protein blocks. Proc. Natl. Acad. Sci. U. S. A. 89(22), 10915–10919 (1992)

    Article  Google Scholar 

  12. Kececioglu, J., DeBlasio, D.: Accuracy estimation and parameter advising for protein multiple sequence alignment. J. Comput. Biol. 20(4), 259–279 (2013)

    Article  Google Scholar 

  13. Kececioglu, J., Kim, E.: Simple and fast inverse alignment. In: Proceedings of the 10th Conference on Research in Computational Molecular Biology (RECOMB), pp. 441–455 (2006)

    Google Scholar 

  14. Kececioglu, J., Starrett, D.: Aligning alignments exactly. In: Proceedings of the 8th Conference on Research in Computational Molecular Biology (RECOMB), pp. 85–96. ACM (2004)

    Google Scholar 

  15. Kim, E., Kececioglu, J.: Learning scoring schemes for sequence alignment from partial examples. IEEE/ACM Trans. Comput. Biol. Bioinform. 5(4), 546–556 (2008)

    Article  Google Scholar 

  16. Kim, J., Ma, J.: PSAR: measuring multiple sequence alignment reliability by probabilistic sampling. Nucleic Acids Res. 39(15), 6359–6368 (2011)

    Google Scholar 

  17. Landan, G., Graur, D.: Heads or tails: a simple reliability check for multiple sequence alignments. Mol. Biol. Evol. 24(6), 1380–1383 (2007)

    Article  Google Scholar 

  18. Lassmann, T., Sonnhammer, E.L.L.: Automatic assessment of alignment quality. Nucleic Acids Res. 33(22), 7120–7128 (2005)

    Article  Google Scholar 

  19. Müller, T., Spang, R., Vingron, M.: Estimating amino acid substitution models: a comparison of Dayhoff’s estimator, the resolvent approach and a maximum likelihood method. Mol. Biol. Evol. 19(1), 8–13 (2002)

    Article  Google Scholar 

  20. Notredame, C., Holm, L., Higgins, D.G.: COFFEE: an objective function for multiple sequence alignments. Bioinformatics 14(5), 407–422 (1998)

    Google Scholar 

  21. Pei, J., Grishin, N.V.: AL2CO: calculation of positional conservation in a protein sequence alignment. Bioinformatics 17(8), 700–712 (2001)

    Google Scholar 

  22. Penn, O., Privman, E., Landan, G., Graur, D., Pupko, T.: An alignment confidence score capturing robustness to guide tree uncertainty. Mol. Biol. Evol. 27(8), 1759–1767 (2010)

    Article  Google Scholar 

  23. Raghava, G., Searle, S.M., Audley, P.C., Barber, J.D., Barton, G.J.: OXBench: a benchmark for evaluation of protein multiple sequence alignment accuracy. BMC Bioinform. 4(1), 1–23 (2003)

    Google Scholar 

  24. Thompson, J.D., Plewniak, F., Ripp, R., Thierry, J.C., Poch, O.: Towards a reliable objective function for multiple sequence alignments. J. Mol. Biol. 314(4), 937–951 (2001)

    Article  Google Scholar 

  25. Van Walle, I., Lasters, I., Wyns, L.: SABmark: a benchmark for sequence alignment that covers the entire known fold space. Bioinformatics 21(7), 1267–1268 (2005)

    Google Scholar 

  26. Wheeler, T.J., Kececioglu, J.D.: Multiple alignment by aligning alignments. In: Proceedings of the 15th ISCB Conference on Intelligent Systems for Molecular Biology (ISMB), Bioinformatics, vol. 23(13), pp. i559–i568 (2007)

    Google Scholar 

  27. Wheeler, T.J., Kececioglu, J.D.: Opal: software for aligning multiple biological sequences (version 2.1.0) (2012). http://opal.cs.arizona.edu

Download references

Author information

Authors and Affiliations

  1. Computational Biology Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA

    Dan DeBlasio

  2. Department of Computer Science, The University of Arizona, Tucson, Arizona, USA

    John Kececioglu

Authors
  1. Dan DeBlasio
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. John Kececioglu
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

DeBlasio, D., Kececioglu, J. (2017). Parameter Advising for the Opal Aligner. In: Parameter Advising for Multiple Sequence Alignment. Computational Biology, vol 26. Springer, Cham. https://doi.org/10.1007/978-3-319-64918-4_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-64918-4_6

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64917-7

  • Online ISBN: 978-3-319-64918-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation