Indexing Similar DNA Sequences

  • Songbo Huang
  • T. W. Lam
  • W. K. Sung
  • S. L. Tam
  • S. M. Yiu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6124)

Abstract

To study the genetic variations of a species, one basic operation is to search for occurrences of patterns in a large number of very similar genomic sequences. To build an indexing data structure on the concatenation of all sequences may require a lot of memory. In this paper, we propose a new scheme to index highly similar sequences by taking advantage of the similarity among the sequences. To store r sequences with k common segments, our index requires only O(n + NlogN) bits of memory, where n is the total length of the common segments and N is the total length of the distinct regions in all texts. The total length of all sequences is rn + N, and any scheme to store these sequences requires Ω(n + N) bits. Searching for a pattern P of length m takes O(m + m logN + m log(rk)psc(P) + occlogn), where psc(P) is the number of prefixes of P that appear as a suffix of some common segments and occ is the number of occurrences of P in all sequences. In practice, rk ≤ N, and psc(P) is usually a small constant. We have implemented our solution and evaluated our solution using real DNA sequences. The experiments show that the memory requirement of our solution is much less than that required by BWT built on the concatenation of all sequences. When compared to the other existing solution (RLCSA), we use less memory with faster searching time.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Briniza, D., He, J., Zelikovsky, A.: Combinatorial search methods for multi-SNP disease association. In: EMBS, pp. 5802–5805 (2006)Google Scholar
  2. 2.
    Burrows, M., Wheeler, D.J.: A block-sorting lossless data compression algorithm. Technical Report 124, Digital Equipment Corporation, California (1994)Google Scholar
  3. 3.
    Emahazion, T., Feuk, L., Jobs, M., Sawyer, S.L., Fredman, D., Clair, D.S., Prince, J.A., Brookes, A.J.: SNP association studies in Alzheimer’s disease highlight problems for complex disease analysis. Trends in Genetics 17(7), 407–413 (2001)CrossRefGoogle Scholar
  4. 4.
    Ferragina, P., Manzini, G.: Opportunistic data structures with applications. In: FOCS, pp. 390–398 (2000)Google Scholar
  5. 5.
    Ferragina, P., Manzini, G.: An experimental study of an opportunistic index. In: SODA, pp. 269–278 (2001)Google Scholar
  6. 6.
    Grossi, R., Vitter, J.S.: Compressed suffix arrays and suffix trees with applications to text indexing and string matching. In: STOC, pp. 397–406 (2000)Google Scholar
  7. 7.
    Gusfield, D.: Algorithms on strings, trees, and sequences. Cambridge University Press, Cambridge (1997)MATHGoogle Scholar
  8. 8.
    Kao, M.-Y. (ed.): Encyclopedia of Algorithms. Springer, Heidelberg (2008)MATHGoogle Scholar
  9. 9.
    Lam, T.W., Sung, W.K., Tam, S.L., Wong, C.K., Yiu, S.M.: Compressed indexing and local alignment of DNA. Bioinformatics 24(6), 791–797 (2008)CrossRefGoogle Scholar
  10. 10.
    Lippert, R.A.: Space-efficient whole genome comparisons with Burrows-Wheeler transforms. Journal of Computational Biology 12(4), 407–415 (2005)CrossRefGoogle Scholar
  11. 11.
    Mäkinen, V., Navarro, G.: Succinct suffix arrays based on run-length encoding. Nordic Journal of Computing 12(1), 40–66 (2005)MathSciNetGoogle Scholar
  12. 12.
    Mäkinen, V., Navarro, G., Sirén, J., Välimäki, N.: Storage and retrieval of individual genomes. In: Batzoglou, S. (ed.) RECOMB 2009. LNCS, vol. 5541, pp. 121–137. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  13. 13.
    Nekrich, Y.: Orthogonal range searching in linear and almost-linear space. Computational Geometry: Theory and Applications 42(4), 342–351 (2009)MATHMathSciNetGoogle Scholar
  14. 14.
    Szpankowski, W.: Probabilistic analysis of generalized suffix trees. In: CPM, pp. 1–14 (1992)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Songbo Huang
    • 1
  • T. W. Lam
    • 1
  • W. K. Sung
    • 2
  • S. L. Tam
    • 1
  • S. M. Yiu
    • 1
  1. 1.Department of Computer ScienceThe University of Hong KongHong Kong
  2. 2.Department of Computer ScienceNational University of SingaporeSingapore

Personalised recommendations