ArticleLab on a chip2020
μCB-seq: microfluidic cell barcoding and sequencing for high-resolution imaging and sequencing of single cells.
Article in Lab on a chip, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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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
13 citing papers in PubMed, 26 citations in OpenAlex.
- Clonal memory of cell division in humans diverges between healthy haematopoiesis and acute myeloid leukaemia.Nature communications · 2026Article
- A high-throughput modular microfluidic platform for versatile functional assays at single-cell level.Microsystems & nanoengineering · 2026Article
- Innovative treatment of age-related hearing loss using MSCs and EVs with Apelin.Cell biology and toxicology · 2025Article
- Advancements in single-cell RNA sequencing and spatial transcriptomics: transforming biomedical research.Acta biochimica Polonica · 2025Review
- The axis of tumor-associated macrophages, extracellular matrix proteins, and cancer-associated fibroblasts in oncogenesis.Cancer cell international · 2024Review
- Novel insights into the heterogeneity of FOXP3 + Treg cells in drug-induced allergic reactions through single-cell transcriptomics.Immunologic research · 2024Article
- Single-cell RNA sequencing in osteoarthritis.Cell proliferation · 2023Review
- nuPRISM: Microfluidic Genome-Wide Phenotypic Screening Platform for Cellular Nuclei.ACS central science · 2022Article
- Phototoxic effects of nonlinear optical microscopy on cell cycle, oxidative states, and gene expression.Scientific reports · 2022Article
- Review
- Anti-bias training for (sc)RNA-seq: experimental and computational approaches to improve precision.Briefings in bioinformatics · 2021Article
- Microfluidic sample preparation for respiratory virus detection: A review.Biomicrofluidics · 2021Review
- μDamID: A Microfluidic Approach for Joint Imaging and Sequencing of Protein-DNA Interactions in Single Cells.Cell systems · 2020Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Single-cell RNA sequencing (scRNA-seq) enables the investigation of complex biological processes in multicellular organisms with high resolution. However, many phenotypic features that are critical to understanding the functional role of cells in a heterogeneous tissue or organ are not directly encoded in the genome and therefore cannot be profiled with scRNA-seq. Quantitative optical microscopy has long been a powerful approach for characterizing diverse cellular phenotypes including cell morphology, protein localization, and chemical composition. Combining scRNA-seq with optical imaging has the potential to provide comprehensive single-cell analysis, allowing for functional integration of gene expression profiling and cell-state characterization. However, it is difficult to track single cells through both measurements; therefore, coupling current scRNA-seq protocols with optical measurements remains a challenge. Here, we report microfluidic cell barcoding and sequencing (μCB-seq), a microfluidic platform that combines high-resolution imaging and sequencing of single cells. μCB-seq is enabled by a novel fabrication method that preloads primers with known barcode sequences inside addressable reaction chambers of a microfluidic device. In addition to enabling multi-modal single-cell analysis, μCB-seq improves gene detection sensitivity, providing a scalable and accurate method for information-rich characterization of single cells.
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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.