Accurate Assignment of Significance to Neuropeptide Identifications Using Monte Carlo K-Permuted Decoy Databases

Malik N Akhtar, Bruce R Southey, Per E Andrén, Jonathan V Sweedler and Sandra L Rodriguez-Zas

PLOS ONE, 2014, vol. 9, issue 10, 1-13

Abstract: In support of accurate neuropeptide identification in mass spectrometry experiments, novel Monte Carlo permutation testing was used to compute significance values. Testing was based on k-permuted decoy databases, where k denotes the number of permutations. These databases were integrated with a range of peptide identification indicators from three popular open-source database search software (OMSSA, Crux, and X! Tandem) to assess the statistical significance of neuropeptide spectra matches. Significance p-values were computed as the fraction of the sequences in the database with match indicator value better than or equal to the true target spectra. When applied to a test-bed of all known manually annotated mouse neuropeptides, permutation tests with k-permuted decoy databases identified up to 100% of the neuropeptides at p-value

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0111112

DOI: 10.1371/journal.pone.0111112

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