A systematic model of the LC-MS proteomics pipeline

BMC Genomics

Research

Ulisses Braga-Neto¹  Edward R Dougherty²  Youting Sun³ 

[1] Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA;Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA;Computational Biology Division, Translational Genomics Research Institution, Phoenix, AZ, USA;Department of Bioinformatics and Computational Biology, University of Texas M.D. Anderson Cancer Center, Houston, TX, USA;Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA;Department of Pathology, University of Texas M.D. Anderson Cancer Center, Houston, TX, USA;

关键词: Peptide;    Mass Spectrometry Data;    Linear Dynamic Range;    Quantification Accuracy;    Mass Spectrometry Instrument;   

DOI  :  10.1186/1471-2164-13-S6-S2

来源: Springer

【 摘 要 】

MotivationMass spectrometry is a complex technique used for large-scale protein profiling with clinical and pharmaceutical applications. While individual components in the system have been studied extensively, little work has been done to integrate various modules and evaluate them from a systems point of view.ResultsIn this work, we investigate this problem by putting together the different modules in a typical proteomics work flow, in order to capture and analyze key factors that impact the number of identified peptides and quantified proteins, protein quantification error, differential expression results, and classification performance. The proposed proteomics pipeline model can be used to optimize the work flow as well as to pinpoint critical bottlenecks worth investing time and resources into for improving performance. Using the model-based approach proposed here, one can study systematically the critical problem of proteomic biomarker discovery, by means of simulation using ground-truthed synthetic MS data.

【 授权许可】

Unknown   
© Sun et al.; licensee BioMed Central Ltd. 2012. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.