Computational quantification of peptides from LC-MS data

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
Ole Schulz-TrieglaffKnut Reinert

Abstract

Liquid chromatography coupled to mass spectrometry (LC-MS) has become a major tool for the study of biological processes. High-throughput LC-MS experiments are frequently conducted in modern laboratories, generating an enormous amount of data per day. A manual inspection is therefore no longer a feasible task. Consequently, there is a need for computational tools that can rapidly provide information about mass, elution time, and abundance of the compounds in a LC-MS sample. We present an algorithm for the detection and quantification of peptides in LC-MS data. Our approach is flexible and independent of the MS technology in use. It is based on a combination of the sweep line paradigm with a novel wavelet function tailored to detect isotopic patterns of peptides. We propose a simple voting schema to use the redundant information in consecutive scans for an accurate determination of monoisotopic masses and charge states. By explicitly modeling the instrument inaccuracy, we are also able to cope with data sets of different quality and resolution. We evaluate our technique on data from different instruments and show that we can rapidly estimate mass, centroid of retention time, and abundance of peptides in a sound algorithmic frame...Continue Reading

References

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Citations

Mar 23, 2011·Journal of Computational Biology : a Journal of Computational Molecular Cell Biology·Karin NoyDaniel Fasulo
Nov 4, 2010·Proteomics·Andrew W DowseyMichael J Dunn
Feb 8, 2011·Proteomics·Marianne SandinFredrik Levander
Jan 18, 2011·Proteomics·Rune MatthiesenAna Sofia Carvalho

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