ArticlePLoS computational biology2019
DART-ID increases single-cell proteome coverage.
Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.
What it found
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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
40 citing papers in PubMed, 1 synthesis or guideline pooled it, 78 citations in OpenAlex.
- Initial recommendations for performing, benchmarking and reporting single-cell proteomics experiments.Nature methods · 2023Guideline
- Single-Cell Proteomic Technologies: Tools in the Quest for Principles.Annual review of biophysics · 2026Review
- Article
- Prosit-XL: enhanced cross-linked peptide identification by fragment intensity prediction to study protein interactions and structures.Nature communications · 2025Article
- Mass Spectrometry-based Solutions for Single-cell Proteomics.Genomics, proteomics & bioinformatics · 2025Review
- Dynamics of Single-Cell Protein Covariation during Epithelial-Mesenchymal Transition.Journal of proteome research · 2025Article
- Massively parallel sample preparation for multiplexed single-cell proteomics using nPOP.Nature protocols · 2024Article
- Inferring post-transcriptional regulation within and across cell types in human testis.bioRxiv : the preprint server for biology · 2024Article
- Quality Control in the Mass Spectrometry Proteomics Core: A Practical Primer.Journal of biomolecular techniques : JBT · 2024Article
- mosaicMPI: a framework for modular data integration across cohorts and -omics modalities.Nucleic acids research · 2024Article
- Rescoring Peptide Spectrum Matches: Boosting Proteomics Performance by Integrating Peptide Property Predictors Into Peptide Identification.Molecular & cellular proteomics : MCP · 2024Review
- Dynamics of single-cell protein covariation during epithelial-mesenchymal transition.bioRxiv : the preprint server for biology · 2024Article
- Massively parallel sample preparation for multiplexed single-cell proteomics using nPOP.bioRxiv : the preprint server for biology · 2023Article
- Data-Driven Optimization of DIA Mass Spectrometry by DO-MS.Journal of proteome research · 2023Article
- Data-Driven Optimization of DIA Mass Spectrometry by DO-MS.bioRxiv : the preprint server for biology · 2023Article
- Prioritized mass spectrometry increases the depth, sensitivity and data completeness of single-cell proteomics.Nature methods · 2023Article
- Uncovering biology by single-cell proteomics.Communications biology · 2023Review
- Challenges and Opportunities for Single-cell Computational Proteomics.Molecular & cellular proteomics : MCP · 2023Review
- Strategies for Increasing the Depth and Throughput of Protein Analysis by plexDIA.Journal of proteome research · 2023Review
- Sampling the proteome by emerging single-molecule and mass spectrometry methods.Nature methods · 2023Article
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 at 2 institutions in 1 country.
Funding
Abstract
Analysis by liquid chromatography and tandem mass spectrometry (LC-MS/MS) can identify and quantify thousands of proteins in microgram-level samples, such as those comprised of thousands of cells. This process, however, remains challenging for smaller samples, such as the proteomes of single mammalian cells, because reduced protein levels reduce the number of confidently sequenced peptides. To alleviate this reduction, we developed Data-driven Alignment of Retention Times for IDentification (DART-ID). DART-ID implements principled Bayesian frameworks for global retention time (RT) alignment and for incorporating RT estimates towards improved confidence estimates of peptide-spectrum-matches. When applied to bulk or to single-cell samples, DART-ID increased the number of data points by 30-50% at 1% FDR, and thus decreased missing data. Benchmarks indicate excellent quantification of peptides upgraded by DART-ID and support their utility for quantitative analysis, such as identifying cell types and cell-type specific proteins. The additional datapoints provided by DART-ID boost the statistical power and double the number of proteins identified as differentially abundant in monocytes and T-cells. DART-ID can be applied to diverse experimental designs and is freely available at http://dart-id.slavovlab.net.
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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.