False Discovery Rate Estimation for Hybrid Mass Spectral Library Search Identifications in Bottom-up Proteomics
Meghan C. Burke, Zheng Zhang, Yuri A. Mirokhin, Dmitrii V. Tchekhovskoi, Yuxue Liang, Stephen E. Stein
We present a method for FDR estimation of mass spectral library search identifications made by a recently developed method for peptide identification, the hybrid search, based on an extension of the target-decoy approach. In addition to estimating confidence for a given identification, this allows users to compare and integrate identifications from the hybrid mass spectral library search method with other peptide identification methods, such as a sequence database-based method. In addition to a score, each hybrid score is associated with a ΔMass value, which is the difference in mass of the search and library peptide, which can correspond to the mass of a modification. We explored the relation between FDR and ΔMass using 100 concatenated random decoy libraries, and discovered that a small number of ΔMass values were especially likely to result from decoy searches. Using these values, FDR values could be adjusted for these specific values, and a reliable FDR generated for any ΔMass value. Finally, using this method, we find and examine common, reliable identifications made by the hybrid search for a range of proteomic studies.
, Zhang, Z.
, Mirokhin, Y.
, Tchekhovskoi, D.
, Liang, Y.
and Stein, S.
False Discovery Rate Estimation for Hybrid Mass Spectral Library Search Identifications in Bottom-up Proteomics, ACS Journal of Proteome Research, [online], https://doi.org/10.1021/acs.jproteome.8b00863
(Accessed August 13, 2022)