A flexible statistical model for alignment of label-free proteomics data – incorporating ion mobility and product ion information

BMC Bioinformatics

Ashlee M Benjamin³  J Will Thompson³  Erik J Soderblom³  Scott J Geromanos⁴  Ricardo Henao³  Virginia B Kraus²  M Arthur Moseley³  Joseph E Lucas¹ 

[1] Quintiles, Durham, North Carolina, USA

[2] Department of Medicine, Duke University Medical Center, Durham, North Carolina, USA

[3] Institute for Genome Sciences and Policy, Duke University Medical Center, Durham, North Carolina, USA

[4] Waters Corporation, Milford, Massachusetts, USA

关键词: Product ions;    Matching;    Data alignment;    Ion mobility;    Proteomics;   

Others  :  1087674
DOI  :  10.1186/1471-2105-14-364

 received in 2013-05-30, accepted in 2013-12-06,  发布年份 2013

【 摘 要 】

Background

The goal of many proteomics experiments is to determine the abundance of proteins in biological samples, and the variation thereof in various physiological conditions. High-throughput quantitative proteomics, specifically label-free LC-MS/MS, allows rapid measurement of thousands of proteins, enabling large-scale studies of various biological systems. Prior to analyzing these information-rich datasets, raw data must undergo several computational processing steps. We present a method to address one of the essential steps in proteomics data processing - the matching of peptide measurements across samples.

Results

We describe a novel method for label-free proteomics data alignment with the ability to incorporate previously unused aspects of the data, particularly ion mobility drift times and product ion information. We compare the results of our alignment method to PEPPeR and OpenMS, and compare alignment accuracy achieved by different versions of our method utilizing various data characteristics. Our method results in increased match recall rates and similar or improved mismatch rates compared to PEPPeR and OpenMS feature-based alignment. We also show that the inclusion of drift time and product ion information results in higher recall rates and more confident matches, without increases in error rates.

Conclusions

Based on the results presented here, we argue that the incorporation of ion mobility drift time and product ion information are worthy pursuits. Alignment methods should be flexible enough to utilize all available data, particularly with recent advancements in experimental separation methods.

【 授权许可】

   
2013 Benjamin et al.; licensee BioMed Central Ltd.

【 图 表 】

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