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Numerical compression schemes for proteomics mass spectrometry data.

Teleman, Johan; Dowsey, Andrew W; Gonzalez-Galarza, Faviel F; Perkins, Simon; Pratt, Brian; Rost, Hannes; Malmstrom, Lars; Malmström, Johan LU ; Jones, Andrew R and Deutsch, Eric W, et al. (2014) In Molecular & Cellular Proteomics 13(6). p.1537-1542
Abstract
The open XML format mzML, used for representation of mass spectrometry (MS) data, is pivotal for the development of platform-independent MS analysis software. Although conversion from vendor formats to mzML must take place on a platform on which the vendor libraries are available (i.e. Windows), once mzML files have been generated, they can be used on any platform. However, the mzML format has turned out to be less efficient than vendor formats. In many cases, the naive mzML representation is 4-fold or even up to 18-fold larger compared to the original vendor file. In disk I/O limited setups, a larger data file also leads to longer processing times, which is a problem given the data production rates of modern mass spectrometers. In an... (More)
The open XML format mzML, used for representation of mass spectrometry (MS) data, is pivotal for the development of platform-independent MS analysis software. Although conversion from vendor formats to mzML must take place on a platform on which the vendor libraries are available (i.e. Windows), once mzML files have been generated, they can be used on any platform. However, the mzML format has turned out to be less efficient than vendor formats. In many cases, the naive mzML representation is 4-fold or even up to 18-fold larger compared to the original vendor file. In disk I/O limited setups, a larger data file also leads to longer processing times, which is a problem given the data production rates of modern mass spectrometers. In an attempt to reduce this problem, we here present a family of numerical compression algorithms called MS-Numpress, intended for efficient compression of MS data. To facilitate ease of adoption, the algorithms target the binary data in the mzML standard, and support in main proteomics tools is already available. Using a test set of 10 representative MS data files we demonstrate typical file size decreases of 90% when combined with traditional compression, as well as read time decreases of up to 50%. It is envisaged that these improvements will be beneficial for data handling within the MS community. (Less)
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Molecular & Cellular Proteomics
volume
13
issue
6
pages
1537 - 1542
publisher
American Society for Biochemistry and Molecular Biology
external identifiers
  • pmid:24677029
  • wos:000337239500011
  • scopus:84901931503
ISSN
1535-9484
DOI
10.1074/mcp.O114.037879
language
English
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yes
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ec893db5-4f8a-4acd-8d29-d234fd9c5efe (old id 4379548)
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http://www.ncbi.nlm.nih.gov/pubmed/24677029?dopt=Abstract
date added to LUP
2014-04-04 20:39:00
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2017-09-03 03:17:00
@article{ec893db5-4f8a-4acd-8d29-d234fd9c5efe,
  abstract     = {The open XML format mzML, used for representation of mass spectrometry (MS) data, is pivotal for the development of platform-independent MS analysis software. Although conversion from vendor formats to mzML must take place on a platform on which the vendor libraries are available (i.e. Windows), once mzML files have been generated, they can be used on any platform. However, the mzML format has turned out to be less efficient than vendor formats. In many cases, the naive mzML representation is 4-fold or even up to 18-fold larger compared to the original vendor file. In disk I/O limited setups, a larger data file also leads to longer processing times, which is a problem given the data production rates of modern mass spectrometers. In an attempt to reduce this problem, we here present a family of numerical compression algorithms called MS-Numpress, intended for efficient compression of MS data. To facilitate ease of adoption, the algorithms target the binary data in the mzML standard, and support in main proteomics tools is already available. Using a test set of 10 representative MS data files we demonstrate typical file size decreases of 90% when combined with traditional compression, as well as read time decreases of up to 50%. It is envisaged that these improvements will be beneficial for data handling within the MS community.},
  author       = {Teleman, Johan and Dowsey, Andrew W and Gonzalez-Galarza, Faviel F and Perkins, Simon and Pratt, Brian and Rost, Hannes and Malmstrom, Lars and Malmström, Johan and Jones, Andrew R and Deutsch, Eric W and Levander, Fredrik},
  issn         = {1535-9484},
  language     = {eng},
  number       = {6},
  pages        = {1537--1542},
  publisher    = {American Society for Biochemistry and Molecular Biology},
  series       = {Molecular & Cellular Proteomics},
  title        = {Numerical compression schemes for proteomics mass spectrometry data.},
  url          = {http://dx.doi.org/10.1074/mcp.O114.037879},
  volume       = {13},
  year         = {2014},
}