research-article

AlignMR: mass spectrometry peak alignment using Hadoop MapReduce

Authors:

Urmi Bhayani,

John SpringerAuthors Info & Claims

BCB '14: Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics

Pages 670 - 672

https://doi.org/10.1145/2649387.2660823

Published: 20 September 2014 Publication History

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Abstract

Proteomics is the study of the structure and behavior of proteins, and one of the primary approaches to protein identification and quantification is through the analysis of Mass Spectrometry (MS) data. This analysis typically involves a series of different computational steps, and the Purdue University Bindley Bioscience Center employs a computational workflow system, the Omics Discovery Pipeline (ODP), to assist in its analysis of MS data. One of the ODP's stages entails aligning the peaks in the MS data across multiple subjects, and due to the large number of subjects that may be used in a study and the large number of peaks found in each subject's corresponding MS data, the alignment step qualifies as a data intensive computation. This research focuses on using Apache Hadoop MapReduce to align the processed MS data in a computationally faster manner than the serial approach currently used in the ODP.

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Cited By

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Bhayani USpringer J(2015)Toward an analytical framework for proteomics softwareProceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics10.1145/2808719.2812221(582-588)Online publication date: 9-Sep-2015
https://dl.acm.org/doi/10.1145/2808719.2812221

Index Terms

AlignMR: mass spectrometry peak alignment using Hadoop MapReduce

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Published In

BCB '14: Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics

September 2014

851 pages

ISBN:9781450328944

DOI:10.1145/2649387

General Chairs:
Pierre Baldi
University of California, Irvine
,
Wei Wang
University of California, Los Angeles

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

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Published: 20 September 2014

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SIGBio

BCB '14: ACM-BCB '14

September 20 - 23, 2014

California, Newport Beach

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Overall Acceptance Rate 254 of 885 submissions, 29%

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Bhayani USpringer J(2015)Toward an analytical framework for proteomics softwareProceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics10.1145/2808719.2812221(582-588)Online publication date: 9-Sep-2015
https://dl.acm.org/doi/10.1145/2808719.2812221

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