loading page

Precursor deconvolution error estimation: the missing puzzle piece in false discovery rate in top-down proteomics
  • +3
  • Kyowon Jeong,
  • Philipp T. Kaulich,
  • Wonhyeuk Jung,
  • Jihyung Kim,
  • Andreas THOLEY,
  • Oliver Kohlbacher
Kyowon Jeong
Eberhard Karls University Tübingen

Corresponding Author:kyowon.jeong@uni-tuebingen.de

Author Profile
Philipp T. Kaulich
Christian-Albrechts University Kiel
Author Profile
Wonhyeuk Jung
Yale School of Medicine
Author Profile
Jihyung Kim
Eberhard Karls University Tübingen
Author Profile
Andreas THOLEY
Christian-Albrechts University Kiel
Author Profile
Oliver Kohlbacher
Eberhard Karls University Tübingen
Author Profile

Abstract

Top-down proteomics (TDP) directly analyzes intact proteins and thus provides more comprehensive qualitative and quantitative proteoform-level information than conventional bottom-up proteomics that relies on digested peptides and protein inference. While significant advancements have been made in TDP in sample preparation, separation, instrumentation, and data analysis, reliable and reproducible data analysis still remains one of the major bottlenecks in TDP. A key step for robust data analysis is the establishment of an objective estimation of proteoform-level false discovery rate (FDR) in proteoform identification. The most widely used FDR estimation scheme is based on the target-decoy approach (TDA), which has primarily been established for bottom-up proteomics. We present evidence that the TDA-based FDR estimation may not work at the proteoform-level due to an overlooked factor, namely the erroneous deconvolution of precursor masses, which leads to incorrect FDR estimation. We argue that the conventional TDA-based FDR in proteoform identification is in fact protein-level FDR rather than proteoform-level FDR unless precursor deconvolution error rate is taken into account. To address this issue, we propose a formula to correct for proteoform-level FDR bias by combining TDA-based FDR and precursor deconvolution error rate.
26 Apr 2023Submitted to PROTEOMICS
28 Apr 2023Submission Checks Completed
28 Apr 2023Assigned to Editor
28 Apr 2023Review(s) Completed, Editorial Evaluation Pending
28 Apr 2023Reviewer(s) Assigned
22 May 2023Editorial Decision: Revise Minor
21 Sep 2023Review(s) Completed, Editorial Evaluation Pending
21 Sep 20231st Revision Received
22 Sep 2023Reviewer(s) Assigned
08 Nov 2023Editorial Decision: Revise Minor
09 Nov 2023Review(s) Completed, Editorial Evaluation Pending
09 Nov 20232nd Revision Received
13 Nov 2023Editorial Decision: Accept