Design of multiple sequence alignment algorithms on parallel, distributed memory supercomputers

The challenge of comparing two or more genomes that have undergone recombination and substantial amounts of segmental loss and gain has recently been addressed for small numbers of genomes. However, datasets of hundreds of genomes are now common and their sizes will only increase in the future. Mult...

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Veröffentlicht in:2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society Jg. 2011; S. 924 - 927
Hauptverfasser: Church, Philip C., Goscinski, Andrzej, Holt, Kathryn, Inouye, Michael, Ghoting, Amol, Makarychev, Konstantin, Reumann, Matthias
Format: Tagungsbericht Journal Article
Sprache:Englisch
Veröffentlicht: United States IEEE 01.01.2011
Schlagworte:
Algorithm design and analysis
Algorithms
Base Sequence
Bioinformatics
Computers, Mainframe
DNA, Bacterial - genetics
Educational institutions
Genome, Bacterial - genetics
Genomics
Hidden Markov models
Molecular Sequence Data
Random access memory
Sequence Alignment - methods
Sequence Analysis, DNA - methods
Software
Software Design
Supercomputers
ISBN:9781424441211, 1424441218
ISSN:1094-687X, 1557-170X, 2694-0604, 2694-0604
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Zusammenfassung:The challenge of comparing two or more genomes that have undergone recombination and substantial amounts of segmental loss and gain has recently been addressed for small numbers of genomes. However, datasets of hundreds of genomes are now common and their sizes will only increase in the future. Multiple sequence alignment of hundreds of genomes remains an intractable problem due to quadratic increases in compute time and memory footprint. To date, most alignment algorithms are designed for commodity clusters without parallelism. Hence, we propose the design of a multiple sequence alignment algorithm on massively parallel, distributed memory supercomputers to enable research into comparative genomics on large data sets. Following the methodology of the sequential progressiveMauve algorithm, we design data structures including sequences and sorted k-mer lists on the IBM Blue Gene/P supercomputer (BG/P). Preliminary results show that we can reduce the memory footprint so that we can potentially align over 250 bacterial genomes on a single BG/P compute node. We verify our results on a dataset of E.coli, Shigella and S.pneumoniae genomes. Our implementation returns results matching those of the original algorithm but in 1/2 the time and with 1/4 the memory footprint for scaffold building. In this study, we have laid the basis for multiple sequence alignment of large-scale datasets on a massively parallel, distributed memory supercomputer, thus enabling comparison of hundreds instead of a few genome sequences within reasonable time.
Bibliographie:ObjectType-Article-1
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content type line 23
ISBN:9781424441211
1424441218
ISSN:1094-687X
1557-170X
2694-0604
2694-0604
DOI:10.1109/IEMBS.2011.6090208