ArticleAnalytical chemistry2020
Targeted Single-Cell RNA and DNA Sequencing With Fluorescence-Activated Droplet Merger.
Article in Analytical chemistry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
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Who cites it
9 citing papers in PubMed.
- Droplet-Based Microfluidics in Single-Bacterium Analysis: Advancements in Cultivation, Detection, and Application.Biosensors · 2025Review
- Deterministic Cell Pairing with Simultaneous Microfluidic Merging and Sorting of Droplets.bioRxiv : the preprint server for biology · 2025Article
- From specialization to broad adoption: Key trends in droplet microfluidic innovations enhancing accessibility to non-experts.Biomicrofluidics · 2025Article
- Single-cell sequencing in molecular diagnostics: Transformative yet untapped potential.Frontiers in genetics · 2025Review
- Fluorescence-activated droplet sequencing (FAD-seq) directly provides sequences of screening hits in antibody discovery.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Beyond single cells: microfluidics empowering multiomics analysis.Analytical and bioanalytical chemistry · 2024Review
- spinDrop: a droplet microfluidic platform to maximise single-cell sequencing information content.Nature communications · 2023Article
- Dual-layered hydrogels allow complete genome recovery with nucleic acid cytometry.Biotechnology journal · 2022Article
- Simple One-Step and Rapid Patterning of PDMS Microfluidic Device Wettability for PDMS Shell Production.Frontiers in bioengineering and biotechnology · 2022Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Analyzing every cell in a diverse sample provides insight into population-level heterogeneity, but abundant cell types dominate the analysis and rarer populations are scarcely represented in the data. To focus on specific cell types, the current paradigm is to physically isolate subsets of interest prior to analysis; however, it remains difficult to isolate and then single-cell sequence such populations because of compounding losses. Here, we describe an alternative approach that selectively merges cells with reagents to achieve enzymatic reactions without having to physically isolate cells. We apply this technique to perform single-cell transcriptome and genome sequencing of specific cell subsets. Our method for analyzing heterogeneous populations obviates the need for pre- or post-enrichment and simplifies single-cell workflows, making it useful for other applications in single-cell biology, combinatorial chemical synthesis, and drug screening.
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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.