OPBI: an open pipeline for biomarker identification
OPBI: an open pipeline for biomarker identification
Biomarker discovery is one particular pipeline utilized in shotgun proteomics, which is made up of series of phases starting from a set of mass spectrum files and ending with some significantly expressed proteins that are related to a particular disease condition. Different techniques and tools have been introduced to perform protein identification and biomarker identification, and they still consume days/hours to carry out the processes. Further, they ignore MS1 information and consider only the information included in MS2 spectra. In this paper, we present an open-source, R-based, accurate biomarker identification pipeline, which provides solutions to time consumption problem in current biomarker discovery pipelines and utilizes the information of MS1 spectra. The developed pipeline was validated using three raw datasets of PRIDE database. We observed around 2-4 times speed-up and FDR ranges from 0.0003 to 0.0009. The biomarker identification system is accurate and operates in a considerable speed than commonly used, open-source MaxQuant tool.
biomarkers, Open-source, shotgun-proteomics
1510-1514
Vidanagamachchi, Sugandima
f848309d-09d2-41cf-97bb-efa083558da8
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
12 February 2018
Vidanagamachchi, Sugandima
f848309d-09d2-41cf-97bb-efa083558da8
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
Vidanagamachchi, Sugandima and Niranjan, Mahesan
(2018)
OPBI: an open pipeline for biomarker identification.
In 2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2017.
vol. 2017-December,
IEEE Computer Society.
.
(doi:10.1109/IEEM.2017.8290145).
Record type:
Conference or Workshop Item
(Paper)
Abstract
Biomarker discovery is one particular pipeline utilized in shotgun proteomics, which is made up of series of phases starting from a set of mass spectrum files and ending with some significantly expressed proteins that are related to a particular disease condition. Different techniques and tools have been introduced to perform protein identification and biomarker identification, and they still consume days/hours to carry out the processes. Further, they ignore MS1 information and consider only the information included in MS2 spectra. In this paper, we present an open-source, R-based, accurate biomarker identification pipeline, which provides solutions to time consumption problem in current biomarker discovery pipelines and utilizes the information of MS1 spectra. The developed pipeline was validated using three raw datasets of PRIDE database. We observed around 2-4 times speed-up and FDR ranges from 0.0003 to 0.0009. The biomarker identification system is accurate and operates in a considerable speed than commonly used, open-source MaxQuant tool.
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More information
e-pub ahead of print date: 9 February 2018
Published date: 12 February 2018
Venue - Dates:
2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2017, Singapore, Singapore, 2017-12-10 - 2017-12-13
Keywords:
biomarkers, Open-source, shotgun-proteomics
Identifiers
Local EPrints ID: 420129
URI: https://eprints.soton.ac.uk/id/eprint/420129
PURE UUID: d41f263c-ef1e-4f86-8c65-21b08810efad
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Date deposited: 27 Apr 2018 16:30
Last modified: 13 Mar 2019 18:34
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Contributors
Author:
Sugandima Vidanagamachchi
University divisions
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