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.
Highlights
For over a decade, Sanger sequencing has been the cornerstone of genome sequencing including that of microbial genomes
It is a non-cloning pyrosequencing based platform that is capable of generating 1 million overlapping reads in a single run. Multitude of factors, such as relatively short read lengths as compared to Sanger, lack of a paired end protocol, and limited accuracy of individual reads for repetitive DNA, in the case of monopolymer repeats, present many computational challenges [1] to make pyrosequencing useful for biology and bioinformatics applications
We present a solution to the problem of aligning pyroreads from multiple genomes using a multiple alignment methodology on multiprocessor platforms
Summary
Sanger sequencing has been the cornerstone of genome sequencing including that of microbial genomes. One of the most widely employed pre processing step for many applications, including haplotype reconstruction [2] [3], analysis of microbial community analysis [4], analysis of genes for diseases [5], is the alignment of these reads with the wild type For important applications such as viral population estimation or haplotype reconstruction of various viruses e.g., HIV in a population, scientists usually have the information about the wild type genome of the virus. To this date, numerous tools have been suggested for mapping short reads to the single reference genome. These strategies are usually at the cost of simplifying the mapping problem and not allowing complex alignments, including gaps or alignment with multiple reference genomes
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