Research note: A high performance multiple sequence alignment system for pyrosequencing reads from multiple reference genomes

  • Authors:

  • Fahad Saeed;Alan Perez-Rathke;Jaroslaw Gwarnicki;Tanya Berger-Wolf;Ashfaq Khokhar

  • Affiliations:

  • The National Heart Lung and Blood Institute (NHLBI), National Institutes of Health (NIH) Bethesda MD, USA;Department of Computer Science, University of Illinois at Chicago, IL, USA;Department of Computer Science, University of Illinois at Chicago, IL, USA;Department of Computer Science, University of Illinois at Chicago, IL, USA;Department of Electrical and Computer Engineering, University of Illinois at Chicago, IL, USA

  • Venue:
  • Journal of Parallel and Distributed Computing
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

Genome resequencing with short reads generated from pyrosequencing generally relies on mapping the short reads against a single reference genome. However, mapping of reads from multiple reference genomes is not possible using a pairwise mapping algorithm. In order to align the reads w.r.t each other and the reference genomes, existing multiple sequence alignment(MSA) methods cannot be used because they do not take into account the position of these short reads with respect to the genome, and are highly inefficient for a large number of sequences. In this paper, we develop a highly scalable parallel algorithm based on domain decomposition, referred to as P-Pyro-Align, to align such a large number of reads from single or multiple reference genomes. The proposed alignment algorithm accurately aligns the erroneous reads, and has been implemented on a cluster of workstations using MPI library. Experimental results for different problem sizes are analyzed in terms of execution time, quality of the alignments, and the ability of the algorithm to handle reads from multiple haplotypes. We report high quality multiple alignment of up to 0.5 million reads. The algorithm is shown to be highly scalable and exhibits super-linear speedups with increasing number of processors.