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This article is part of the supplement: Selected articles from the Twelfth Asia Pacific Bioinformatics Conference (APBC 2014): Genomics

Open Access Proceedings

Spectral probabilities of top-down tandem mass spectra

Xiaowen Liu12*, Matthew W Segar1, Shuai Cheng Li3 and Sangtae Kim4

  • * Corresponding author: Xiaowen Liu

Author Affiliations

1 Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, 535 W. Michigan Street, 46202, Indianapolis, IN, USA

2 Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, 410 West 10th Street, HS 5000, 46202 Indianapolis, IN, USA

3 Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong SAR, China

4 Biological Sciences Division, Pacific Northwest National Laboratory, 902 Battelle Boulevard, 99352 Richland, WA, USA

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BMC Genomics 2014, 15(Suppl 1):S9  doi:10.1186/1471-2164-15-S1-S9

Published: 24 January 2014



In mass spectrometry-based proteomics, the statistical significance of a peptide-spectrum or protein-spectrum match is an important indicator of the correctness of the peptide or protein identification. In bottom-up mass spectrometry, probabilistic models, such as the generating function method, have been successfully applied to compute the statistical significance of peptide-spectrum matches for short peptides containing no post-translational modifications. As top-down mass spectrometry, which often identifies intact proteins with post-translational modifications, becomes available in many laboratories, the estimation of statistical significance of top-down protein identification results has come into great demand.


In this paper, we study an extended generating function method for accurately computing the statistical significance of protein-spectrum matches with post-translational modifications. Experiments show that the extended generating function method achieves high accuracy in computing spectral probabilities and false discovery rates.


The extended generating function method is a non-trivial extension of the generating function method for bottom-up mass spectrometry. It can be used to choose the correct protein-spectrum match from several candidate protein-spectrum matches for a spectrum, as well as separate correct protein-spectrum matches from incorrect ones identified from a large number of tandem mass spectra.

mass spectrometry; spectral probabilities; dynamic programming