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Building consensus spectral libraries for peptide identification in proteomics


Spectral searching has drawn increasing interest as an alternative to sequence-database searching in proteomics. We developed and validated an open-source software toolkit, SpectraST, to enable proteomics researchers to build spectral libraries and to integrate this promising approach in their data-analysis pipeline. It allows individual researchers to condense raw data into spectral libraries, summarizing information about observed proteomes into a concise and retrievable format for future data analyses.

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Figure 1: Library building functionalities of SpectraST.
Figure 2: Effects of library quality level and consensus spectrum creation.
Figure 3: Effects of library spectrum simplification.


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We thank all the data contributors to PeptideAtlas who have made this study possible. This study was supported in part by the US National Heart, Lung and Blood Institute, National Institutes of Health (N01-HV-28179).

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Authors and Affiliations



H.L. developed the SpectraST software, performed all library building and validation studies and wrote the manuscript. E.W.D. built the Human Plasma PeptideAtlas from which the data were drawn for this study. J.S.E., J.K.E. and S.E.S. contributed ideas to algorithm development and library format design. R.A. conceived and supervised the project. All authors discussed the results and commented on the manuscript.

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Correspondence to Henry Lam.

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Supplementary Figures 1–4, Supplementary Tables 1–4, Supplementary Methods (PDF 286 kb)

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Lam, H., Deutsch, E., Eddes, J. et al. Building consensus spectral libraries for peptide identification in proteomics. Nat Methods 5, 873–875 (2008).

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