Long Read Alignment with Parallel MapReduce Cloud Platform
Joint Authors
Al-Absi, Ahmed Abdulhakim
Kang, Dae-Ki
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-12-29
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Genomic sequence alignment is an important technique to decode genome sequences in bioinformatics.
Next-Generation Sequencing technologies produce genomic data of longer reads.
Cloud platforms are adopted to address the problems arising from storage and analysis of large genomic data.
Existing genes sequencing tools for cloud platforms predominantly consider short read gene sequences and adopt the Hadoop MapReduce framework for computation.
However, serial execution of map and reduce phases is a problem in such systems.
Therefore, in this paper, we introduce Burrows-Wheeler Aligner’s Smith-Waterman Alignment on Parallel MapReduce (BWASW-PMR) cloud platform for long sequence alignment.
The proposed cloud platform adopts a widely accepted and accurate BWA-SW algorithm for long sequence alignment.
A custom MapReduce platform is developed to overcome the drawbacks of the Hadoop framework.
A parallel execution strategy of the MapReduce phases and optimization of Smith-Waterman algorithm are considered.
Performance evaluation results exhibit an average speed-up of 6.7 considering BWASW-PMR compared with the state-of-the-art Bwasw-Cloud.
An average reduction of 30% in the map phase makespan is reported across all experiments comparing BWASW-PMR with Bwasw-Cloud.
Optimization of Smith-Waterman results in reducing the execution time by 91.8%.
The experimental study proves the efficiency of BWASW-PMR for aligning long genomic sequences on cloud platforms.
American Psychological Association (APA)
Al-Absi, Ahmed Abdulhakim& Kang, Dae-Ki. 2015. Long Read Alignment with Parallel MapReduce Cloud Platform. BioMed Research International،Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1056798
Modern Language Association (MLA)
Al-Absi, Ahmed Abdulhakim& Kang, Dae-Ki. Long Read Alignment with Parallel MapReduce Cloud Platform. BioMed Research International No. 2015 (2015), pp.1-13.
https://search.emarefa.net/detail/BIM-1056798
American Medical Association (AMA)
Al-Absi, Ahmed Abdulhakim& Kang, Dae-Ki. Long Read Alignment with Parallel MapReduce Cloud Platform. BioMed Research International. 2015. Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1056798
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1056798