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Open Access Publications from the University of California

On E-values for Tandem MS Scoring Schemes

  • Author(s): Segal, Mark R
  • et al.

In a recent article in this journal, Khatun, Hamlett, and Giddings (2008) (KHG) advance a new scoring scheme for use in conjunction with tandem mass spectrometry (MS/MS) based peptide identification. As they note, such identifications are fundamental to much proteomics research but, due to MS/MS data complexity and the scale of attendant database searches, their accuracy is limited. The scoring technique they propose, which employs a hidden Markov model (HMM) over a set of states that represent key features of MS/MS data, is convincingly motivated and exhibits good performance. The purpose of this brief note is to critique the method chosen for calibrating the HMM scores, rather than the genesis of the scores themselves.

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