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Submitted on May 11, 2005
Systems Biology Group, Institut Pasteur, Paris, Paris 75015
Corresponding Author: benno{at}pasteur.fr
Mass spectrometry-based proteomics experiments, in combination with liquid chromatography-based separation, can be used to compare complex biological samples across multiple conditions. These comparisons are usually performed on the level of protein lists generated from individual experiments. Unfortunately, given the current technologies, these lists typically cover only a small fraction of the total protein content, which makes global comparisons extremely limited. Recently, approaches have been suggested that are built on the comparison of computationally built feature lists, instead of protein identifications. While these approaches promise to capture a bigger spectrum of the proteins present in a complex mixture, their success is strongly dependent on the correctness of the identified features, and the aligned retention times of these features across multiple experiments. In this experimental-computational study, we go one step further, and perform the comparisons directly on the signal level. First, signal maps are constructed, which associate the experimental signals across multiple experiments. Only then a feature detection algorithm uses this integrated information to identify those features that are discriminating or common across multiple experiments. At the core of our approach is a score function that faithfully recognizes mass spectra from similar peptide mixtures and an algorithm that produces an optimal alignment (time warping) of the liquid chromatography experiments on the basis of raw MS signal, making minimal assumptions on the underlying data. We provide experimental evidence that suggests uniqueness and correctness of the resulting signal maps, even on low-accuracy mass spectrometers. These maps can be employed for a variety of proteomics analyses. In this paper we illustrate the use of signal maps for the discovery of diagnostic biomarkers. An implementation of our algorithm is available on the CHAMS Web server at http://www.systemsbiology.fr/chams.
Revised on October 31, 2005
Accepted on November 3, 2005
Signal maps for mass spectrometry-based comparative proteomics
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