ArticleScientific reports2020
Integrating single-cell RNA-seq and imaging with SCOPE-seq2.
Article in Scientific reports, 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 trial behind it
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Who cites it
13 citing papers in PubMed.
- Mapping and engineering the human cell-cell interactome.Nature biotechnology · 2026Review
- Imaging-Guided Omics Technologies for Resolving Rare Cancer States and Advancing Nanomedicine.Nano letters · 2026Review
- Predictive Cellular Signatures from Live Human Motor Neurons Distinguish TDP-43 ALS and Enable ALS Subtype Stratification.bioRxiv : the preprint server for biology · 2026Article
- Single-cell sequencing and organoids: applications in organ development and disease.Molecular biomedicine · 2025Review
- Mapping T cell dynamics to molecular profiles through behavior-guided transcriptomics.Nature protocols · 2025Review
- Exploring New Dimensions of Tumor Heterogeneity: The Application of Single Cell Analysis to Organoid-Based 3D In Vitro Models.Advanced healthcare materials · 2023Review
- Initial refinement of data from video-based single-cell tracking.Cancer innovation · 2023Article
- Identifying a Lung Stem Cell Subpopulation by Combining Single-Cell Morphometrics, Organoid Culture, and Transcriptomics.Stem cells (Dayton, Ohio) · 2023Article
- Robotic data acquisition with deep learning enables cell image-based prediction of transcriptomic phenotypes.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Dynamics ofProceedings of the National Academy of Sciences of the United States of America · 2022Article
- Spatial components of molecular tissue biology.Nature biotechnology · 2022Review
- Anti-bias training for (sc)RNA-seq: experimental and computational approaches to improve precision.Briefings in bioinformatics · 2021Article
- Connecting Timescales in Biology: Can Early Dynamical Measurements Predict Long-Term Outcomes?Trends in cancer · 2021Review
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Live cell imaging allows direct observation and monitoring of phenotypes that are difficult to infer from transcriptomics. However, existing methods for linking microscopy and single-cell RNA-seq (scRNA-seq) have limited scalability. Here, we describe an upgraded version of Single Cell Optical Phenotyping and Expression (SCOPE-seq2) for combining single-cell imaging and expression profiling, with substantial improvements in throughput, molecular capture efficiency, linking accuracy, and compatibility with standard microscopy instrumentation. We introduce improved optically decodable mRNA capture beads and implement a more scalable and simplified optical decoding process. We demonstrate the utility of SCOPE-seq2 for fluorescence, morphological, and expression profiling of individual primary cells from a human glioblastoma (GBM) surgical sample, revealing relationships between simple imaging features and cellular identity, particularly among malignantly transformed tumor 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.