Data processing methods and quality control strategies for label-free LC-MS protein quantification.
Sandin, Marianne LU ; Teleman, Johan LU ; Malmström, Johan LU
and Levander, Fredrik
LU
(2014)
In Biochimica et Biophysica Acta
1844(1).
p.29-41
- Abstract
- Protein quantification using different LC-MS techniques is becoming a standard practice. However, with a multitude of experimental setups to choose from, as well as a wide array of software solutions for subsequent data processing, it is non-trivial to select the most appropriate workflow for a given biological question. In this review, we highlight different issues that need to be addressed by software for quantitative LC-MS experiments and describe different approaches that are available. With focus on label-free quantification, examples are discussed both for LC-MS/MS and LC-SRM data processing. We further elaborate on current quality control methodology for performing accurate protein quantification experiments. This article is part of... (More)
- Protein quantification using different LC-MS techniques is becoming a standard practice. However, with a multitude of experimental setups to choose from, as well as a wide array of software solutions for subsequent data processing, it is non-trivial to select the most appropriate workflow for a given biological question. In this review, we highlight different issues that need to be addressed by software for quantitative LC-MS experiments and describe different approaches that are available. With focus on label-free quantification, examples are discussed both for LC-MS/MS and LC-SRM data processing. We further elaborate on current quality control methodology for performing accurate protein quantification experiments. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3734008
- author
- Sandin, Marianne
LU
; Teleman, Johan
LU
; Malmström, Johan
LU
and Levander, Fredrik
LU
- organization
- publishing date
- 2014
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Biochimica et Biophysica Acta
- volume
- 1844
- issue
- 1
- pages
- 29 - 41
- publisher
- Elsevier
- external identifiers
-
- pmid:23567904
- wos:000330911400005
- scopus:84890571201
- pmid:23567904
- ISSN
- 0006-3002
- DOI
- 10.1016/j.bbapap.2013.03.026
- language
- English
- LU publication?
- yes
- id
- aee3c50d-0f23-4103-b2a1-2f5ffc885a64 (old id 3734008)
- date added to LUP
- 2016-04-01 13:18:12
- date last changed
- 2022-01-27 18:24:26
@article{aee3c50d-0f23-4103-b2a1-2f5ffc885a64,
abstract = {{Protein quantification using different LC-MS techniques is becoming a standard practice. However, with a multitude of experimental setups to choose from, as well as a wide array of software solutions for subsequent data processing, it is non-trivial to select the most appropriate workflow for a given biological question. In this review, we highlight different issues that need to be addressed by software for quantitative LC-MS experiments and describe different approaches that are available. With focus on label-free quantification, examples are discussed both for LC-MS/MS and LC-SRM data processing. We further elaborate on current quality control methodology for performing accurate protein quantification experiments. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era.}},
author = {{Sandin, Marianne and Teleman, Johan and Malmström, Johan and Levander, Fredrik}},
issn = {{0006-3002}},
language = {{eng}},
number = {{1}},
pages = {{29--41}},
publisher = {{Elsevier}},
series = {{Biochimica et Biophysica Acta}},
title = {{Data processing methods and quality control strategies for label-free LC-MS protein quantification.}},
url = {{http://dx.doi.org/10.1016/j.bbapap.2013.03.026}},
doi = {{10.1016/j.bbapap.2013.03.026}},
volume = {{1844}},
year = {{2014}},
}