ArticleAnalytical chemistry2019
High-Throughput Single Cell Proteomics Enabled by Multiplex Isobaric Labeling in a Nanodroplet Sample Preparation Platform.
Article in Analytical chemistry, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 95 papers, 1 of them a synthesis 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
95 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Graph neural networks for single-cell omics data: a review of approaches and applications.Briefings in bioinformatics · 2025Pooled it
- Single-cell proteomic landscape of the developing human brain.Nature biotechnology · 2026Article
- Reproducible-by-design: Romics Processor, a FAIR ecosystem for multi-omics and spatial-omics analysis.bioRxiv : the preprint server for biology · 2026Article
- Spatial omics in high-grade glioma: study design, analytical pitfalls, and standards for reproducible neuro-oncology.Acta neuropathologica communications · 2026Review
- Proteoform profiling of endogenous single cells from rat hippocampus at scale.Nature biotechnology · 2026Article
- scProfiterole: Clustering of Single-Cell Proteomic Data Using Graph Contrastive Learning via Spectral Filters.bioRxiv : the preprint server for biology · 2026Article
- DECODE: deep learning-based common deconvolution framework for various omics data.Nature methods · 2026Article
- Single-Cell Proteomics of Human Peripheral Blood Mononuclear Cells Exceeding 600 Cells per Day.bioRxiv : the preprint server for biology · 2026Article
- The pursuit of ultrasensitive phosphoproteomics to unravel signalling in rare cells.Communications biology · 2025Review
- OmicsTweezer: A distribution-independent cell deconvolution model for multi-omics Data.Cell genomics · 2025Article
- Deciphering Cell Type Abundance in Proteomics Data Through Graph Neural Networks.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Multiplexed phosphoproteomics of low cell numbers using SPARCE.Communications biology · 2025Article
- Are We There Yet? Assessing the Readiness of Single-Cell Proteomics to Answer Biological Hypotheses.Journal of proteome research · 2025Review
- Increasing Proteome Coverage Through a Reduction in Analyte Complexity in Single-Cell Equivalent Samples.Journal of proteome research · 2025Article
- Trends in Mass Spectrometry-Based Single-Cell Proteomics.Analytical chemistry · 2025Review
- Robust collection and processing for label-free single voxel proteomics.Nature communications · 2025Article
- Data acquisition approaches for single cell proteomics.Proteomics · 2025Review
- Digital Microfluidics for Sample Preparation in Low-Input Proteomics.Small methods · 2025Review
- Coupling Microdroplet-Based Sample Preparation, Multiplexed Isobaric Labeling, and Nanoflow Peptide Fractionation for Deep Proteome Profiling of the Tissue Microenvironment.Analytical chemistry · 2024Article
- Rescoring Peptide Spectrum Matches: Boosting Proteomics Performance by Integrating Peptide Property Predictors Into Peptide Identification.Molecular & cellular proteomics : MCP · 2024Review
35 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
Abstract
Effective extension of mass spectrometry-based proteomics to single cells remains challenging. Herein we combined microfluidic nanodroplet technology with tandem mass tag (TMT) isobaric labeling to significantly improve analysis throughput and proteome coverage for single mammalian cells. Isobaric labeling facilitated multiplex analysis of single cell-sized protein quantities to a depth of ∼1 600 proteins with a median CV of 10.9% and correlation coefficient of 0.98. To demonstrate in-depth high throughput single cell analysis, the platform was applied to measure protein expression in 72 single cells from three murine cell populations (epithelial, immune, and endothelial cells) in <2 days instrument time with over 2 300 proteins identified. Principal component analysis grouped the single cells into three distinct populations based on protein expression with each population characterized by well-known cell-type specific markers. Our platform enables high throughput and unbiased characterization of single cell heterogeneity at the proteome level.
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Identifiers
What Socratic 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 Socratic graph.