ArticleMolecular & cellular proteomics : MCP2023
MSstatsPTM: Statistical Relative Quantification of Posttranslational Modifications in Bottom-Up Mass Spectrometry-Based Proteomics.
Article in Molecular & cellular proteomics : MCP, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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Who cites it
36 citing papers in PubMed, 46 citations in OpenAlex.
- Integrated Analysis of Posttranslational Modifications and Total Proteome: Methods for Distinguishing Abundance from Usage Changes.Methods in molecular biology (Clifton, N.J.) · 2027Article
- Post‑translational modifications in atherosclerosis: Roles, mechanisms and therapeutic potential (Review).International journal of molecular medicine · 2026Review
- ProteoMeter: a pipeline for integrating multi-PTM and limited proteolysis data to reveal modification-structure coupling at the residue level.NAR genomics and bioinformatics · 2026Article
- GlycoDiveR: A Modular R Framework to Analyze and Visualize Highly Dimensional Glycoproteomics Data.ACS measurement science au · 2026Article
- Proteomic investigation of signaling dynamics: from static maps to network rewiring.Bioscience reports · 2026Review
- E3 Ubiquitin Ligase Mind Bomb 1 is a Novel Negative Regulator of Tumor-Suppressive BMP Signaling.Cancer research communications · 2026Article
- DiaReport: reproducible workflow for differential expression analysis and interactive reporting in DIA-based proteomics.Bioinformatics (Oxford, England) · 2026Article
- Systematic optimization and benchmarking of synchro-PASEF for high-throughput phosphoproteome profiling.bioRxiv : the preprint server for biology · 2026Article
- Host Proteome Remodeling During Group A Streptococcus Skin Infection.Molecular & cellular proteomics : MCP · 2026Article
- GlycoDiveR: a modular R framework to analyze and visualize highly dimensional glycoproteomics data.bioRxiv : the preprint server for biology · 2026Article
- LC-MS profiling ofbioRxiv : the preprint server for biology · 2026Article
- Mistranslating tRNA variants impact the proteome and phosphoproteome of Saccharomyces cerevisiae.G3 (Bethesda, Md.) · 2026Article
- PTMs_Closed_Search: Multiple Post-Translational Modification Closed Search Using Reduced Search Space and Transferred FDR.Proteomes · 2026Article
- Regulation of vacuole fusion in stomata by dephosphorylation of the HOPS subunit VPS39.The Plant journal : for cell and molecular biology · 2025Article
- VRK1 co-delivery mitigates DNA clustering by BAF in TFAMoplex transfection.Materials today. Bio · 2025Article
- Rational design of potent small-molecule SMARCA2/A4 degraders acting via the recruitment of FBXO22.Nature communications · 2025Article
- ATM promotes reversed fork processing during DNA interstrand cross-link repair.bioRxiv : the preprint server for biology · 2025Article
- Mistranslating tRNA variants impact the proteome and phosphoproteome ofbioRxiv : the preprint server for biology · 2025Article
- Carboxy-Methylation of the Catalytic Subunit of Protein Phosphatase 2A (PP2Ac) Integrates Methionine Availability with Methionine Addicted Cancer Cell Proliferation.Biomolecules · 2025Article
- Screening of Protein Carbonylation Sites in Human Serum by Ion Mobility Mass Spectrometry.Journal of proteome research · 2025Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Liquid chromatography coupled with bottom-up mass spectrometry (LC-MS/MS)-based proteomics is increasingly used to detect changes in posttranslational modifications (PTMs) in samples from different conditions. Analysis of data from such experiments faces numerous statistical challenges. These include the low abundance of modified proteoforms, the small number of observed peptides that span modification sites, and confounding between changes in the abundance of PTM and the overall changes in the protein abundance. Therefore, statistical approaches for detecting differential PTM abundance must integrate all the available information pertaining to a PTM site and consider all the relevant sources of confounding and variation. In this manuscript, we propose such a statistical framework, which is versatile, accurate, and leads to reproducible results. The framework requires an experimental design, which quantifies, for each sample, both peptides with PTMs and peptides from the same proteins with no modification sites. The proposed framework supports both label-free and tandem mass tag-based LC-MS/MS acquisitions. The statistical methodology separately summarizes the abundances of peptides with and without the modification sites, by fitting separate linear mixed effects models appropriate for the experimental design. Next, model-based inferences regarding the PTM and the protein-level abundances are combined to account for the confounding between these two sources. Evaluations on computer simulations, a spike-in experiment with known ground truth, and three biological experiments with different organisms, modification types, and data acquisition types demonstrate the improved fold change estimation and detection of differential PTM abundance, as compared to currently used approaches. The proposed framework is implemented in the free and open-source R/Bioconductor package MSstatsPTM.
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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.