IDBA – A Practical Iterative de Bruijn Graph De Novo Assembler

  • Yu Peng
  • Henry C. M. Leung
  • S. M. Yiu
  • Francis Y. L. Chin
Conference paper

DOI: 10.1007/978-3-642-12683-3_28

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6044)
Cite this paper as:
Peng Y., Leung H.C.M., Yiu S.M., Chin F.Y.L. (2010) IDBA – A Practical Iterative de Bruijn Graph De Novo Assembler. In: Berger B. (eds) Research in Computational Molecular Biology. RECOMB 2010. Lecture Notes in Computer Science, vol 6044. Springer, Berlin, Heidelberg

Abstract

The de Bruijn graph assembly approach breaks reads into k-mers before assembling them into contigs. The string graph approach forms contigs by connecting two reads with k or more overlapping nucleotides. Both approaches must deal with the following problems: false-positive vertices, due to erroneous reads; gap problem, due to non-uniform coverage; branching problem, due to erroneous reads and repeat regions. A proper choice of k is crucial but for single k there is always a trade-off: a small k favors the situation of erroneous reads and non-uniform coverage, and a large k favors short repeat regions.

We propose an iterative de Bruijn graph approach iterating from small to large k exploring the advantages of the in between values. Our IDBA outperforms the existing algorithms by constructing longer contigs with similar accuracy and using less memory, both with real and simulated data. The running time of the algorithm is comparable to existing algorithms.

Availability: IDBA is available at http://www.cs.hku.hk/~alse/idba/

Keywords

De novo assembly de Bruijn graph string graph mate-pair high throughput short reads 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Yu Peng
    • 1
  • Henry C. M. Leung
    • 1
  • S. M. Yiu
    • 1
  • Francis Y. L. Chin
    • 1
  1. 1.Department of Computer ScienceThe University of Hong KongHong Kong

Personalised recommendations