Next Article in Journal
Causes and Consequences of Age-Related Changes in DNA Methylation: A Role for ROS?
Previous Article in Journal
The Effect of Nutritional Status in the Pathogenesis of Critical Illness Myopathy (CIM)
Previous Article in Special Issue
On-Beads Digestion in Conjunction with Data-Dependent Mass Spectrometry: A Shortcut to Quantitative and Dynamic Interaction Proteomics
Biology 2014, 3(2), 383-402; doi:10.3390/biology3020383
Article

Data Pre-Processing for Label-Free Multiple Reaction Monitoring (MRM) Experiments

1
,
2
 and
1,*
Received: 17 March 2014 / Revised: 16 April 2014 / Accepted: 10 May 2014 / Published: 5 June 2014
(This article belongs to the Special Issue Advances in Proteomics Methods)
View Full-Text   |   Download PDF [708 KB, uploaded 5 June 2014]   |   Browse Figures

Abstract

Multiple Reaction Monitoring (MRM) conducted on a triple quadrupole mass spectrometer allows researchers to quantify the expression levels of a set of target proteins. Each protein is often characterized by several unique peptides that can be detected by monitoring predetermined fragment ions, called transitions, for each peptide. Concatenating large numbers of MRM transitions into a single assay enables simultaneous quantification of hundreds of peptides and proteins. In recognition of the important role that MRM can play in hypothesis-driven research and its increasing impact on clinical proteomics, targeted proteomics such as MRM was recently selected as the Nature Method of the Year. However, there are many challenges in MRM applications, especially data pre‑processing where many steps still rely on manual inspection of each observation in practice. In this paper, we discuss an analysis pipeline to automate MRM data pre‑processing. This pipeline includes data quality assessment across replicated samples, outlier detection, identification of inaccurate transitions, and data normalization. We demonstrate the utility of our pipeline through its applications to several real MRM data sets.
Keywords: multiple reaction monitoring; label-free; quality assessment; data normalization; proteomics; peptide; transition multiple reaction monitoring; label-free; quality assessment; data normalization; proteomics; peptide; transition
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Share & Cite This Article

Further Mendeley | CiteULike
Export to BibTeX |
EndNote
MDPI and ACS Style

Chung, L.M.; Colangelo, C.M.; Zhao, H. Data Pre-Processing for Label-Free Multiple Reaction Monitoring (MRM) Experiments. Biology 2014, 3, 383-402.

View more citation formats

Related Articles

Article Metrics

Comments

Citing Articles

[Return to top]
Biology EISSN 2079-7737 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert