Efficient alignment of next generation sequencing data using MapReduce on the cloud

Rawan Alsaad, Qutaibah Malluhi, Mohamed Abouelhoda

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a methodology for running NGS read mapping tools in the cloud environment based on the MapReduce programming paradigm. As a demonstration, the recently developed and robust sequence alignment tool, BFAST, is used within our methodology to handle massive datasets. The results of our experiments show that the transformation of existing read mapping tools to run within the MapReduce framework dramatically reduces the total execution time and enables the user to utilize the resources provided by the cloud.

Original languageEnglish
Title of host publication2012 Cairo International Biomedical Engineering Conference, CIBEC 2012
Pages18-22
Number of pages5
DOIs
Publication statusPublished - 1 Dec 2012
Event2012 Cairo International Biomedical Engineering Conference, CIBEC 2012 - Giza, Egypt
Duration: 20 Dec 201222 Dec 2012

Publication series

Name2012 Cairo International Biomedical Engineering Conference, CIBEC 2012

Other

Other2012 Cairo International Biomedical Engineering Conference, CIBEC 2012
CountryEgypt
CityGiza
Period20/12/1222/12/12

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Keywords

  • Cloud computing
  • MapReduce
  • bioinformatics
  • sequence alignment

ASJC Scopus subject areas

  • Biomedical Engineering

Cite this

Alsaad, R., Malluhi, Q., & Abouelhoda, M. (2012). Efficient alignment of next generation sequencing data using MapReduce on the cloud. In 2012 Cairo International Biomedical Engineering Conference, CIBEC 2012 (pp. 18-22). [6473312] (2012 Cairo International Biomedical Engineering Conference, CIBEC 2012). https://doi.org/10.1109/CIBEC.2012.6473312