The University of Southampton
University of Southampton Institutional Repository

Mining whole sample mass spectrometry proteomics data for biomarkers: an overview

Mining whole sample mass spectrometry proteomics data for biomarkers: an overview
Mining whole sample mass spectrometry proteomics data for biomarkers: an overview
In this paper we aim to provide a concise overview of designing and conducting an MS proteomics experiment in such a way as to allow statistical analysis that may lead to the discovery of novel biomarkers. We provide a summary of the various stages that make up such an experiment, highlighting the need for experimental goals to be decided upon in advance. We discuss issues in experimental design at the sample collection stage, and good practise for standardising protocols within the proteomics laboratory. We then describe approaches to the data mining stage of the experiment, including the processing steps that transform a raw mass spectrum into a useable form. We propose a permutation-based procedure for determining the significance of reported error rates. Finally, because of its general advantages in speed and cost, we suggest that MS proteomics may be a good candidate for an early primary screening approach to disease diagnosis, identifying areas of risk and making referrals for more specific tests without necessarily making a diagnosis in its own right. Our discussion is illustrated with examples drawn from experiments on bovine blood serum conducted in the Centre for Proteomic Research (CPR) at Southampton University.
0957-4174
5333-5340
McDonald, R
158c6fe6-ed9a-4f59-98df-e8ba72720a57
Skipp, Paul
1ba7dcf6-9fe7-4b5c-a9d0-e32ed7f42aa5
Potts, Chris N.
58c36fe5-3bcb-4320-a018-509844d4ccff
Thomas, Lyn C.
a3ce3068-328b-4bce-889f-965b0b9d2362
O'Connor, David
7c29ec66-081e-46f0-8be8-bac6a7dc8de8
Bennell, J.
38d924bc-c870-4641-9448-1ac8dd663a30
McDonald, R
158c6fe6-ed9a-4f59-98df-e8ba72720a57
Skipp, Paul
1ba7dcf6-9fe7-4b5c-a9d0-e32ed7f42aa5
Potts, Chris N.
58c36fe5-3bcb-4320-a018-509844d4ccff
Thomas, Lyn C.
a3ce3068-328b-4bce-889f-965b0b9d2362
O'Connor, David
7c29ec66-081e-46f0-8be8-bac6a7dc8de8
Bennell, J.
38d924bc-c870-4641-9448-1ac8dd663a30

McDonald, R, Skipp, Paul, Potts, Chris N., Thomas, Lyn C., O'Connor, David and Bennell, J. (2009) Mining whole sample mass spectrometry proteomics data for biomarkers: an overview. Expert Systems with Applications, 36 (3), 5333-5340. (doi:10.1016/j.eswa.2008.06.133).

Record type: Article

Abstract

In this paper we aim to provide a concise overview of designing and conducting an MS proteomics experiment in such a way as to allow statistical analysis that may lead to the discovery of novel biomarkers. We provide a summary of the various stages that make up such an experiment, highlighting the need for experimental goals to be decided upon in advance. We discuss issues in experimental design at the sample collection stage, and good practise for standardising protocols within the proteomics laboratory. We then describe approaches to the data mining stage of the experiment, including the processing steps that transform a raw mass spectrum into a useable form. We propose a permutation-based procedure for determining the significance of reported error rates. Finally, because of its general advantages in speed and cost, we suggest that MS proteomics may be a good candidate for an early primary screening approach to disease diagnosis, identifying areas of risk and making referrals for more specific tests without necessarily making a diagnosis in its own right. Our discussion is illustrated with examples drawn from experiments on bovine blood serum conducted in the Centre for Proteomic Research (CPR) at Southampton University.

Text
ExpertSystemsPaper.pdf - Other
Download (126kB)

More information

Published date: 2009

Identifiers

Local EPrints ID: 155037
URI: http://eprints.soton.ac.uk/id/eprint/155037
ISSN: 0957-4174
PURE UUID: cbfb7a14-2eee-4fca-a0fd-2fe9253d091b
ORCID for Paul Skipp: ORCID iD orcid.org/0000-0002-2995-2959

Catalogue record

Date deposited: 02 Jun 2010 14:20
Last modified: 09 Jan 2022 02:41

Export record

Altmetrics

Contributors

Author: R McDonald
Author: Paul Skipp ORCID iD
Author: Chris N. Potts
Author: Lyn C. Thomas
Author: David O'Connor
Author: J. Bennell

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×