ArticleScientific reports2017
Abseq: Ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 154 papers.
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
154 citing papers in PubMed, 281 citations in OpenAlex.
- ConvexGating infers gating strategies from clusters in single cell cytometry data.Nature communications · 2026Article
- An Advanced Single-Cell RNA Sequencing (scRNA-seq) Protocol Utilizing Custom-Designed Multiplexing.Bio-protocol · 2026Article
- Machine learning predictions surpass individual mRNAs as a proxy of single-cell protein expression.Genome biology · 2026Article
- Predicting and interpreting protein and phosphoprotein abundance from pan-cancer and single-cell transcriptomes.iScience · 2026Article
- A protocol for high-quality single-cell RNA sequencing with cell surface protein quantification.Blood science (Baltimore, Md.) · 2026Article
- ImmunoPheno: A Computational Framework for Data-Driven Design and Analysis of Immunophenotyping Experiments.bioRxiv : the preprint server for biology · 2026Article
- PURE-seq integrates FACS and PIP-seq for single-cell genomics of ultra-rare cells.Nature communications · 2026Article
- Advances and Applications of Spatial Proteomics: From Organellar Maps to Clinical Translation.Chembiochem : a European journal of chemical biology · 2026Review
- Single Cell RNA Sequencing in Colorectal Cancer Immunology: Recent Updates, Application, and Emerging Challenges.Current molecular medicine · 2026Review
- Innovative Single-Cell Sequencing Techniques for B cell Analysis and Their Implications for Rational HIV-1 Vaccine Design.Current HIV research · 2026Review
- Editorial: Multiomics advances: bridging gaps in understanding intricate biological systems.Frontiers in plant science · 2026Article
- Comparative benchmarking of single-cell clustering algorithms for transcriptomic and proteomic data.Genome biology · 2025Article
- Droplet-Based Microfluidics in Single-Bacterium Analysis: Advancements in Cultivation, Detection, and Application.Biosensors · 2025Review
- Microbiome Single Cell Atlases Generated with a Commercial Instrument.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- ADTnorm: robust integration of single-cell protein measurement across CITE-seq datasets.Nature communications · 2025Article
- Emerging technologies of single-cell multi-omics.Haematologica · 2025Review
- Assessing the Influence of Selected Permeabilization Methods on Lymphocyte Single-Cell Multi-Omics.Antibodies (Basel, Switzerland) · 2025Article
- High-Throughput Single-Cell Analysis of Local Nascent Protein Deposition in 3D Microenvironments via Extracellular Protein Identification Cytometry (EPIC).Advanced materials (Deerfield Beach, Fla.) · 2025Article
- Multimodal hierarchical classification of CITE-seq data delineates immune cell states across lineages and tissues.Cell reports methods · 2025Article
- inDrops-2: a flexible, versatile and cost-efficient droplet microfluidic approach for high-throughput scRNA-seq of fresh and preserved clinical samples.Nucleic acids research · 2025Article
94 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
5 authors at 2 institutions in 1 country.
Funding
Abstract
Proteins are the primary effectors of cellular function, including cellular metabolism, structural dynamics, and information processing. However, quantitative characterization of proteins at the single-cell level is challenging due to the tiny amount of protein available. Here, we present Abseq, a method to detect and quantitate proteins in single cells at ultrahigh throughput. Like flow and mass cytometry, Abseq uses specific antibodies to detect epitopes of interest; however, unlike these methods, antibodies are labeled with sequence tags that can be read out with microfluidic barcoding and DNA sequencing. We demonstrate this novel approach by characterizing surface proteins of different cell types at the single-cell level and distinguishing between the cells by their protein expression profiles. DNA-tagged antibodies provide multiple advantages for profiling proteins in single cells, including the ability to amplify low-abundance tags to make them detectable with sequencing, to use molecular indices for quantitative results, and essentially limitless multiplexing.
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.