The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
False Discovery Rates and Related Statistical Concepts in Mass Spectrometry-Based Proteomics
Abstract
Development of statistical methods for assessing the significance of peptide assignments to tandem mass spectra obtained using database searching remains an important problem. In the past several years, several different approaches have emerged, including the concept of expectation values, target-decoy strategy, and the probability mixture modeling approach of PeptideProphet. In this work, we provide a background on statistical significance analysis in the field of mass spectrometry-based proteomics, and present our perspective on the current and future developments in this area.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Elias, J. E., & Gygi, S. P. (2007) · Nature Methods · doi:10.1038/nmeth1019 · Cited by 3,925
Interpretation of Shotgun Proteomic Data
Nesvizhskii, A. I., & Aebersold, R. (2005) · Molecular & Cellular Proteomics · doi:10.1074/mcp.r500012-mcp200 · Cited by 1,025
Self-citationAssigning Significance to Peptides Identified by Tandem Mass Spectrometry Using Decoy Databases
Käll, L., Storey, J. D., MacCoss, M. J., & Noble, W. S. (2008) · Journal of Proteome Research · doi:10.1021/pr700600n · Cited by 607
Cited by
A guided tour of the Trans‐Proteomic Pipeline
Deutsch, E. W., Mendoza, L., Shteynberg, D., Farrah, T., Lam, H., Tasman, N., Sun, Z., Nilsson, E., Pratt, B., Prazen, B., et al. (2010) · PROTEOMICS · doi:10.1002/pmic.200900375 · Cited by 745
Self-citationA practical guide to methods controlling false discoveries in computational biology
Korthauer, K., Kimes, P. K., Duvallet, C., Reyes, A., Subramanian, A., Teng, M., Shukla, C., Alm, E. J., & Hicks, S. C. (2019) · Genome Biology · doi:10.1186/s13059-019-1716-1 · Cited by 436
Posterior Error Probabilities and False Discovery Rates: Two Sides of the Same Coin
Käll, L., Storey, J. D., MacCoss, M. J., & Noble, W. S. (2008) · Journal of Proteome Research · doi:10.1021/pr700739d · Cited by 293
Bioinformatics Methods for Mass Spectrometry-Based Proteomics Data Analysis
Chen, C., Hou, J., Tanner, J. J., & Cheng, J. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21082873 · Cited by 280
MultipleTesting.com: A tool for life science researchers for multiple hypothesis testing correction
Menyhart, O., Weltz, B., & Győrffy, B. (2021) · PLOS ONE · doi:10.1371/journal.pone.0245824 · Cited by 216
Metadata
- Authors
- Choi, H., & Nesvizhskii, A. I.
- Venue
- Journal of Proteome Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2007-12-08
- Volume
- 7
- Issue
- 1
- Pages
- 47-50
- ISSN
- 1535-3893 (ISSN-L)
- 1535-3907
- OpenAlex
- W2058015510
- Cited by
- 217
- References
- 3
- FWCI
- 6.39
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: False Discovery Rates and Related Statistical Concepts in Mass Spectrometry-Based Proteomics. https://app.cochat.ai/papers/10.1021/pr700747q
- The paper
- Choi, H., & Nesvizhskii, A. I. (2008). False Discovery Rates and Related Statistical Concepts in Mass Spectrometry-Based Proteomics. Journal of Proteome Research. https://doi.org/10.1021/pr700747q
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.