ArticleMolecular & cellular proteomics : MCP2019
DIAlignR Provides Precise Retention Time Alignment Across Distant Runs in DIA and Targeted Proteomics.
Article in Molecular & cellular proteomics : MCP, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 35 citations in OpenAlex.
- Scoring information integration with statistical quality control enhanced cross-run analysis of data-independent acquisition proteomics data.Communications chemistry · 2025Article
- HLA Ligand Atlas DIA: extending the benign immunopeptidomics resource with increased sensitivity through data-independent acquisition mass spectrometry.Journal for immunotherapy of cancer · 2025Article
- Data Independent Acquisition to Inform the Development of Targeted Proteomics Assays Using a Triple Quadrupole Mass Spectrometer.Journal of proteome research · 2025Article
- Bovine Milk Protein-Derived Preparations and Their Hydrolysates as Sources of ACE-Inhibitory, DPP-IV-Inhibitory, and Antioxidative Peptides Analyzed Using in Silico and in Vitro Protocols.International journal of molecular sciences · 2025Article
- Cross-Run Hybrid Features Improve the Identification of Data-Independent Acquisition Proteomics.ACS omega · 2024Article
- Rescoring Peptide Spectrum Matches: Boosting Proteomics Performance by Integrating Peptide Property Predictors Into Peptide Identification.Molecular & cellular proteomics : MCP · 2024Review
- Multiple Isomers of Photolumazine V Bind MR1 and Differentially Activate MAIT Cells.Journal of immunology (Baltimore, Md. : 1950) · 2024Article
- Data-Independent Acquisition Peptidomics.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Achieving quantitative reproducibility in label-free multisite DIA experiments through multirun alignment.Communications biology · 2023Article
- Article
- DEIMoS: An Open-Source Tool for Processing High-Dimensional Mass Spectrometry Data.Analytical chemistry · 2022Article
- DIAMetAlyzer allows automated false-discovery rate-controlled analysis for data-independent acquisition in metabolomics.Nature communications · 2022Article
- NAguideR: performing and prioritizing missing value imputations for consistent bottom-up proteomic analyses.Nucleic acids research · 2020Article
- Acquiring and Analyzing Data Independent Acquisition Proteomics Experiments without Spectrum Libraries.Molecular & cellular proteomics : MCP · 2020Article
- Simultaneous Improvement in the Precision, Accuracy, and Robustness of Label-free Proteome Quantification by Optimizing Data Manipulation Chains.Molecular & cellular proteomics : MCP · 2019Article
- Proceedings of the EuBIC Winter School 2019.EuPA open proteomics · 2019Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sequential Windowed Acquisition of All Theoretical Fragment Ion Mass Spectra (SWATH-MS) is widely used for proteomics analysis given its high throughput and reproducibility, but ensuring consistent quantification of analytes across large-scale studies of heterogeneous samples such as human plasma remains challenging. Heterogeneity in large-scale studies can be caused by large time intervals between data acquisition, acquisition by different operators or instruments, and intermittent repair or replacement of parts, such as the liquid chromatography column, all of which affect retention time (RT) reproducibility and, successively, performance of SWATH-MS data analysis. Here, we present a novel algorithm for RT alignment of SWATH-MS data based on direct alignment of raw MS2 chromatograms using a hybrid dynamic programming approach. The algorithm does not impose a chronological order of elution and allows for alignment of elution-order-swapped peaks. Furthermore, allowing RT mapping in a certain window around a coarse global fit makes it robust against noise. On a manually validated dataset, this strategy outperformed the current state-of-the-art approaches. In addition, on real-world clinical data, our approach outperformed global alignment methods by mapping 98% of peaks compared with 67% cumulatively. DIAlignR reduced alignment error up to 30-fold for extremely distant runs. The robustness of technical parameters used in this pairwise alignment strategy is also demonstrated. The source code is released under the BSD license at https://github.com/Roestlab/DIAlignR.
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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.