ArticleMolecular & cellular proteomics : MCP2016
Systematic Errors in Peptide and Protein Identification and Quantification by Modified Peptides.
Article in Molecular & cellular proteomics : MCP, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
35 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Mapping protein states and interactions across the tree of life with co-fractionation mass spectrometry.Nature communications · 2023Pooled it
- Meta-analysis defines principles for the design and analysis of co-fractionation mass spectrometry experiments.Nature methods · 2021Pooled it
- A nonparametric statistical method for deconvolving densities in the analysis of proteomic data.BMC bioinformatics · 2026Article
- Article
- Article
- pyRBDome: a comprehensive computational platform for enhancing RNA-binding proteome data.Life science alliance · 2024Article
- Article
- Demystifying PTM Identification Using MODplus: Best Practices and Pitfalls.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Fast alignment of mass spectra in large proteomics datasets, capturing dissimilarities arising from multiple complex modifications of peptides.BMC bioinformatics · 2023Article
- Quantitative Proteomic Analysis of Cyanide and Mercury Detoxification by Pseudomonas pseudoalcaligenes CECT 5344.Microbiology spectrum · 2023Article
- MSBooster: improving peptide identification rates using deep learning-based features.Nature communications · 2023Article
- Proteomic Analysis of Arsenic Resistance during Cyanide Assimilation byInternational journal of molecular sciences · 2023Article
- Peptidomics.Nature reviews. Methods primers · 2023Article
- Holistic view of biological nitrogen fixation and phosphorus mobilization inFrontiers in microbiology · 2023Article
- Investigating pathological epigenetic aberrations by epi-proteomics.Clinical epigenetics · 2022Review
- Uncovering the impacts of alternative splicing on the proteome with current omics techniques.Wiley interdisciplinary reviews. RNA · 2022Review
- Multiaspect Examinations of Possible Alternative Mappings of Identified Variant Peptides: A Case Study on the HEK293 Cell Line.ACS omega · 2022Article
- Mechanisms and Minimization of False Discovery of Metabolic Bioorthogonal Noncanonical Amino Acid Proteomics.Rejuvenation research · 2022Article
- Biochemical Mapping ofInternational journal of molecular sciences · 2021Article
- Clipper: p-value-free FDR control on high-throughput data from two conditions.Genome biology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The principle of shotgun proteomics is to use peptide mass spectra in order to identify corresponding sequences in a protein database. The quality of peptide and protein identification and quantification critically depends on the sensitivity and specificity of this assignment process. Many peptides in proteomic samples carry biochemical modifications, and a large fraction of unassigned spectra arise from modified peptides. Spectra derived from modified peptides can erroneously be assigned to wrong amino acid sequences. However, the impact of this problem on proteomic data has not yet been investigated systematically. Here we use combinations of different database searches to show that modified peptides can be responsible for 20-50% of false positive identifications in deep proteomic data sets. These false positive hits are particularly problematic as they have significantly higher scores and higher intensities than other false positive matches. Furthermore, these wrong peptide assignments lead to hundreds of false protein identifications and systematic biases in protein quantification. We devise a "cleaned search" strategy to address this problem and show that this considerably improves the sensitivity and specificity of proteomic data. In summary, we show that modified peptides cause systematic errors in peptide and protein identification and quantification and should therefore be considered to further improve the quality of proteomic data annotation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.