Highly multiplexed simultaneous detection of RNAs and proteins in single cells
Open accessAbstract
To enable the detection of expression signatures specific to individual cells, we developed PLAYR (proximity ligation assay for RNA), a method for highly multiplexed transcript quantification by flow and mass cytometry that is compatible with standard antibody staining. When used with mass cytometry, PLAYR allowed for the simultaneous quantification of more than 40 different mRNAs and proteins. In primary cells, we quantified multiple transcripts, with the identity and functional state of each analyzed cell defined on the basis of the expression of a separate set of transcripts or proteins. By expanding high-throughput deep phenotyping of cells beyond protein epitopes to include RNA expression, PLAYR opens a new avenue for the characterization of cellular metabolism.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
PLAYR simultaneously quantifies more than 40 targeted mRNAs and proteins from 10,000 single cells in several cell types.
“For example, in 2016, the proximity ligation assay for RNA (PLAYR) was developed to simultaneously quantify more than 40 targeted mRNAs and proteins from 10,000 single cells in several cell types67.”
From The technological landscape and applications of single-cell multi-omics (2023) · cites this paper as [67]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Primer3—new capabilities and interfaces
Untergasser, A., Cutcutache, I., Kõressaar, T., Ye, J., Faircloth, B., Remm, M., & Rozen, S. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks596 · Cited by 9,165 · see citing works
Full-length RNA-seq from single cells using Smart-seq2
Picelli, S., Faridani, O. R., Björklund, Å. K., Winberg, G., Sagasser, S., & Sandberg, R. (2014) · Nature Protocols · doi:10.1038/nprot.2014.006 · Cited by 4,137 · see citing works
Repbase Update, a database of eukaryotic repetitive elements
Jurka, J., Kapitonov, V. V., Pavlı́ček, A., Klonowski, P., Kohany, O., & Walichiewicz, J. (2005) · Cytogenetic and Genome Research · doi:10.1159/000084979 · Cited by 3,331 · see citing works
Direct observation of individual endogenous protein complexes in situ by proximity ligation
Söderberg, O., Gullberg, M., Jarvius, M., Ridderstråle, K., Leuchowius, K.-J., Jarvius, J., Wester, K., Hydbring, P., Bahram, F., Larsson, L.-G., et al. (2006) · Nature Methods · doi:10.1038/nmeth947 · Cited by 2,419 · see citing works
Smart-seq2 for sensitive full-length transcriptome profiling in single cells
Picelli, S., Björklund, Å. K., Faridani, O. R., Sagasser, S., Winberg, G., & Sandberg, R. (2013) · Nature Methods · doi:10.1038/nmeth.2639 · Cited by 2,358 · see citing works
Bendall, S. C., Simonds, E. F., Qiu, P., Amir, E.-A. D., Krutzik, P. O., Finck, R., Bruggner, R. V., Melamed, R., Trejo, A., Ornatsky, O. I., et al. (2011) · Science · doi:10.1126/science.1198704 · Cited by 2,279 · see citing works
Self-citationMassively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types
Jaitin, D. A., Kenigsberg, E., Keren-Shaul, H., Elefant, N., Paul, F., Zaretsky, I., Mildner, A., Cohen, N., Jung, S., Tanay, A., et al. (2014) · Science · doi:10.1126/science.1247651 · Cited by 1,795 · see citing works
Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells
Ramsköld, D., Luo, S., Wang, Y.-C., Li, R., Deng, Q., Faridani, O. R., Daniels, G. A., Khrebtukova, I., Loring, J. F., Laurent, L. C., et al. (2012) · Nature Biotechnology · doi:10.1038/nbt.2282 · Cited by 1,609 · see citing works
Amir, E.-A. D., Davis, K. L., Tadmor, M. D., Simonds, E. F., Levine, J. H., Bendall, S. C., Shenfeld, D. K., Krishnaswamy, S., Nolan, G. P., & Pe'er, D. (2013) · Nature Biotechnology · doi:10.1038/nbt.2594 · Cited by 1,550 · see citing works
Self-citationProtein detection using proximity-dependent DNA ligation assays
Fredriksson, S., Gullberg, M. T., Jarvius, J., Olsson, C., Pietras, K., Gustafsdottir, S., Östman, A., & Landegren, U. D. (2002) · Nature Biotechnology · doi:10.1038/nbt0502-473 · Cited by 1,511 · see citing works
Mutation detection and single-molecule counting using isothermal rolling-circle amplification
Lizardi, P. M., Huang, X. C., Zhu, Z., Bray‐Ward, P., Thomas, D. C., & Ward, D. C. (1998) · Nature Genetics · doi:10.1038/898 · Cited by 1,443 · see citing works
Single-Cell RNA-Seq Reveals Dynamic, Random Monoallelic Gene Expression in Mammalian Cells
Deng, Q., Ramsköld, D., Reinius, B., & Sandberg, R. (2014) · Science · doi:10.1126/science.1245316 · Cited by 1,345 · see citing works
CEL-seq: single-cell RNA-seq by multiplexed linear amplification
Hashimshony, T., Wagner, F., Sher, N., & Yanai, I. (2012) · Cell Reports · doi:10.1016/j.celrep.2012.08.003 · Cited by 1,231 · see citing works
Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells
Shalek, A. K., Satija, R., Adiconis, X., Gertner, R. S., Gaublomme, J. T., Raychowdhury, R., Schwartz, S., Yosef, N., Malboeuf, C., Lu, D., et al. (2013) · Nature · doi:10.1038/nature12172 · Cited by 1,190 · see citing works
Quantitative single-cell RNA-seq with unique molecular identifiers
Islam, S., Zeisel, A., Joost, S., La Manno, G., Zajac, P., Kasper, M., Lönnerberg, P., & Linnarsson, S. (2014) · Nature Methods · doi:10.1038/nmeth.2772 · Cited by 1,183 · see citing works
Stochastic protein expression in individual cells at the single molecule level
Cai, L., Friedman, N., & Xie, X. S. (2006) · Nature · doi:10.1038/nature04599 · Cited by 1,145 · see citing works
Multiplexed ion beam imaging of human breast tumors
Angelo, M., Bendall, S. C., Finck, R., Hale, M. B., Hitzman, C., Borowsky, A. D., Levenson, R. M., Lowe, J. B., Liu, S. D., Zhao, S., et al. (2014) · Nature Medicine · doi:10.1038/nm.3488 · Cited by 1,108 · see citing works
Self-citationTranscriptional Pulsing of a Developmental Gene
Chubb, J. R., Trcek, T., Shenoy, S. M., & Singer, R. H. (2006) · Current Biology · doi:10.1016/j.cub.2006.03.092 · Cited by 714 · see citing works
Quantitative assessment of single-cell RNA-sequencing methods
Wu, A. R., Neff, N. F., Kalisky, T., Dalerba, P., Treutlein, B., Rothenberg, M. E., Mburu, F. M., Mantalas, G. L., Sim, S., Clarke, M. F., et al. (2014) · Nature Methods · doi:10.1038/nmeth.2694 · Cited by 696 · see citing works
Single Cell Profiling of Potentiated Phospho-Protein Networks in Cancer Cells
Irish, J. M., Hovland, R., Krutzik, P. O., Perez, O. D., Bruserud, Ø., Gjertsen, B. T., & Nolan, G. P. (2004) · Cell · doi:10.1016/j.cell.2004.06.028 · Cited by 684 · see citing works
Self-citationZunder, E. R., Finck, R., Behbehani, G. K., Amir, E.-A. D., Krishnaswamy, S., Gonzalez, V. D., Lorang, C. G., Bjornson, Z., Spitzer, M. H., Bodenmiller, B., et al. (2015) · Nature Protocols · doi:10.1038/nprot.2015.020 · Cited by 596 · see citing works
Self-citationKrutzik, P. O., & Nolan, G. P. (2003) · Cytometry Part A · doi:10.1002/cyto.a.10072 · Cited by 564 · see citing works
Self-citationNewell, E. W., Sigal, N., Bendall, S. C., Nolan, G. P., & Davis, M. M. (2012) · Immunity · doi:10.1016/j.immuni.2012.01.002 · Cited by 555 · see citing works
Self-citationDesign and Analysis of Single-Cell Sequencing Experiments
Grün, D., & van Oudenaarden, A. (2015) · Cell · doi:10.1016/j.cell.2015.10.039 · Cited by 536 · see citing works
Wilson, N. K., Kent, D. G., Buettner, F., Shehata, M., Macaulay, I. C., Calero-Nieto, F. J., Sánchez Castillo, M., Oedekoven, C. A., Diamanti, E., Schulte, R., et al. (2015) · Cell Stem Cell · doi:10.1016/j.stem.2015.04.004 · Cited by 466 · see citing works
Sasagawa, Y., Nikaido, I., Hayashi, T., Danno, H., Uno, K. D., Imai, T., & Ueda, H. R. (2013) · Genome Biology · doi:10.1186/gb-2013-14-4-r31 · Cited by 455 · see citing works
Combinatorial labeling of single cells for gene expression cytometry
Fan, H. C., Fu, G. K., & Fodor, S. P. A. (2015) · Science · doi:10.1126/science.1258367 · Cited by 455 · see citing works
A drug-inducible transgenic system for direct reprogramming of multiple somatic cell types
Wernig, M., Lengner, C. J., Hanna, J. H., Lodato, M. A., Steine, E. J., Foreman, R. K., Staerk, J., Markoulaki, S., & Jaenisch, R. (2008) · Nature Biotechnology · doi:10.1038/nbt1483 · Cited by 437 · see citing works
In situ detection and genotyping of individual mRNA molecules
Larsson, C., Grundberg, I., Söderberg, O., & Nilsson, M. F. (2010) · Nature Methods · doi:10.1038/nmeth.1448 · Cited by 415 · see citing works
Development and applications of single-cell transcriptome analysis
Tang, F., Lao, K., & Surani, M. A. (2011) · Nature Methods · doi:10.1038/nmeth.1557 · Cited by 337 · see citing works
Clinical recovery from surgery correlates with single-cell immune signatures
Gaudilliere, B. L., Fragiadakis, G. K., Bruggner, R. V., Nicolau, M. M., Finck, R., Tingle, M. S., Silva, J., Ganio, E. A., Yeh, C. G., Maloney, W. J., et al. (2014) · Science Translational Medicine · doi:10.1126/scitranslmed.3009701 · Cited by 333 · see citing works
Self-citationHighly multiplexed and strand-specific single-cell RNA 5′ end sequencing
Islam, S., Kjällquist, U., Moliner, A., Zajac, P., Fan, J.-B., Lönnerberg, P., & Linnarsson, S. (2012) · Nature Protocols · doi:10.1038/nprot.2012.022 · Cited by 272 · see citing works
Patterson, B. K., Till, M., Otto, P. A., Goolsby, C. L., Furtado, M. R., McBride, L. J., & Wolinsky, S. M. (1993) · Science · doi:10.1126/science.8493534 · Cited by 264 · see citing works
Kinetics of TNF, IL-6, and IL-8 gene expression in LPS-stimulated human whole blood
DeForge, L. E., & Remick, D. G. (1991) · Biochemical and Biophysical Research Communications · doi:10.1016/0006-291x(91)90478-p · Cited by 217 · see citing works
Single-copy Gene Detection Using Branched DNA (bDNA) In Situ Hybridization
Player, A. N., Shen, L., Kenny, D. A., Antao, V., & Kolberg, J. A. (2001) · Journal of Histochemistry & Cytochemistry · doi:10.1177/002215540104900507 · Cited by 196 · see citing works
Agarwal, S., Piesco, N. P., Johns, L. P., & Riccelli, A. E. (1995) · Journal of Dental Research · doi:10.1177/00220345950740040501 · Cited by 173 · see citing works
Porichis, F., Hart, M. G., Griesbeck, M., Everett, H. L., Hassan, M., Baxter, A. E., Lindqvist, M., Miller, S. M., Soghoian, D. Z., Kavanagh, D. G., et al. (2014) · Nature Communications · doi:10.1038/ncomms6641 · Cited by 150 · see citing works
Flow Cytometric Analysis of Acute Leukemias
Kaleem, Z., Crawford, E., Pathan, M. H., Jasper, L., Covinsky, M. A., Johnson, L. R., & White, G. (2003) · Archives of Pathology & Laboratory Medicine · doi:10.5858/2003-127-42-fcaoa · Cited by 134 · see citing works
Combinatorial gene regulation by modulation of relative pulse timing
Lin, Y., Sohn, C. H., Dalal, C. K., Cai, L., & Elowitz, M. B. (2015) · Nature · doi:10.1038/nature15710 · Cited by 110 · see citing works
Translational Applications of Flow Cytometry in Clinical Practice
Jaye, D. L., Bray, R. A., Gebel, H. M., Harris, W. A. C., & Waller, E. K. (2012) · The Journal of Immunology · doi:10.4049/jimmunol.1290017 · Cited by 109 · see citing works
Weibrecht, I., Lundin, E., Kiflemariam, S., Mignardi, M., Grundberg, I., Larsson, C., Koos, B., Nilsson, M. F., & Söderberg, O. (2013) · Nature Protocols · doi:10.1038/nprot.2013.006 · Cited by 108 · see citing works
Flow cytometric analysis of acute leukemias
Duque, R. E., Everett, E. T., & Iturraspe, J. A. (1990) · Clinical Immunology Newsletter · doi:10.1016/0197-1859(90)90022-z · Cited by 98 · see citing works
Sample processing obscures cancer-specific alterations in leukemic transcriptomes
Dvinge, H., Ries, R. E., Ilagan, J. O., Stirewalt, D. L., Meshinchi, S., & Bradley, R. K. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1413374111 · Cited by 81 · see citing works
O’Gorman, W. E., Hsieh, E. W. Y., Savig, E. S., Gherardini, P. F., Hernandez, J. D., Hansmann, L., Balboni, I., Utz, P. J., Bendall, S. C., Fantl, W. J., et al. (2015) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2015.04.008 · Cited by 72 · see citing works
Self-citationParallel Visualization of Multiple Protein Complexes in Individual Cells in Tumor Tissue
Leuchowius, K., Clausson, C.-M., Grannas, K., Erbilgin, Y., Botling, J., Zieba, A., Landegren, U. D., & Söderberg, O. (2013) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o112.023374 · Cited by 61 · see citing works
Index sorting resolves heterogeneous murine hematopoietic stem cell populations
Schulte, R., Wilson, N. K., Prick, J. C. M., Cossetti, C., Maj, M. K., Göttgens, B., & Kent, D. G. (2015) · Experimental Hematology · doi:10.1016/j.exphem.2015.05.006 · Cited by 54 · see citing works
Fluorescent in‐situ hybridization to detect cellular RNA by flow cytometry and confocal microscopy†
Bauman, J. G. J., Bayer, J. A., & Dekken, H. V. (1990) · Journal of Microscopy · doi:10.1111/j.1365-2818.1990.tb02948.x · Cited by 50 · see citing works
Flow cytometric detection of EBV (EBER snRNA) using peptide nucleic acid probes
Just, T., Burgwald, H., & Broe, M. K. (1998) · Journal of Virological Methods · doi:10.1016/s0166-0934(98)00058-5 · Cited by 29 · see citing works
In situ hybridization in suspension and flow cytometry as a tool for the study of gene expression
Lalli, E., Gibellini, D., Santi, S., & Facchini, A. (1992) · Analytical Biochemistry · doi:10.1016/0003-2697(92)90015-y · Cited by 28 · see citing works
A fluorescent in situ hybridization method in flow cytometry to detect HIV-1 specific RNA
Borzı̀, R. M., Piacentini, A., Monaco, M. C., Lisignoli, G., Degrassi, A., Cattini, L., Santi, S., & Facchini, A. (1996) · Journal of Immunological Methods · doi:10.1016/0022-1759(96)00070-1 · Cited by 22 · see citing works
Chapter 5 Detection of mRNA Species by Flow Cytometry
Belloc, F., & Durrieu, F. (1994) · Methods in cell biology · doi:10.1016/s0091-679x(08)61068-7 · Cited by 5 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Simultaneous epitope and transcriptome measurement in single cells
Stoeckius, M., Hafemeister, C., Stephenson, W., Houck-Loomis, B., Chattopadhyay, P. K., Swerdlow, H., Satija, R., & Smibert, P. (2017) · Nature Methods · doi:10.1038/nmeth.4380 · Cited by 3,098 · see citing works
Regev, A., Teichmann, S. A., Lander, E. S., Amit, I., Benoist, C., Birney, E., Bodenmiller, B., Campbell, P., Carninci, P., Clatworthy, M., et al. (2017) · eLife · doi:10.7554/elife.27041 · Cited by 2,232 · see citing works
Self-citationDixit, A., Parnas, O., Li, B., Chen, J., Fulco, C. P., Jerby-Arnon, L., Marjanovic, N. D., Dionne, D., Burks, T., Raychowdhury, R., et al. (2016) · Cell · doi:10.1016/j.cell.2016.11.038 · Cited by 1,863 · see citing works
Three-dimensional intact-tissue sequencing of single-cell transcriptional states
Wang, X., Allen, W. E., Wright, M. A., Sylwestrak, E. L., Samusik, N., Vesuna, S., Evans, K., Liu, C., Ramakrishnan, C., Liu, J., et al. (2018) · Science · doi:10.1126/science.aat5691 · Cited by 1,620 · see citing works
Self-citationRegev, A., Teichmann, S. A., Lander, E. S., Amit, I., Benoist, C. O., Birney, E., Bodenmiller, B., & al, E. (2017) · Zurich Open Repository and Archive (University of Zurich) · doi:10.5167/uzh-162597 · Cited by 1,457 · see citing works
Mass Cytometry: Single Cells, Many Features
Spitzer, M. H., & Nolan, G. P. (2016) · Cell · doi:10.1016/j.cell.2016.04.019 · Cited by 1,199 · see citing works
Self-citationThe technological landscape and applications of single-cell multi-omics
Baysoy, A., Bai, Z., Satija, R., & Fan, R. (2023) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-023-00615-w · Cited by 1,037 · see citing works
Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition)
Cossarizza, A., Chang, H., Radbruch, A., Acs, A., Adam, D., Adam‐Klages, S., Agace, W. W., Aghaeepour, N., Akdiş, M., Allez, M., et al. (2019) · European Journal of Immunology · doi:10.1002/eji.201970107 · Cited by 982 · see citing works
Higher-Order Inter-chromosomal Hubs Shape 3D Genome Organization in the Nucleus
Quinodoz, S. A., Ollikainen, N., Tabak, B., Palla, A., Schmidt, J. M., Detmar, E., Lai, M. M., Shishkin, A. A., Bhat, P., Takei, Y., et al. (2018) · Cell · doi:10.1016/j.cell.2018.05.024 · Cited by 892 · see citing works
Scaling single-cell genomics from phenomenology to mechanism
Tanay, A., & Regev, A. (2017) · Nature · doi:10.1038/nature21350 · Cited by 792 · see citing works
Brodin, P., & Davis, M. M. (2017) · Nature reviews. Immunology · doi:10.1038/nri.2016.125 · Cited by 730 · see citing works
Zitnik, M., Nguyen, F., Wang, B., Leskovec, J., Goldenberg, A., & Hoffman, M. M. (2019) · Information Fusion · doi:10.1016/j.inffus.2018.09.012 · Cited by 675 · see citing works
CODEX multiplexed tissue imaging with DNA-conjugated antibodies
Black, S. A., Phillips, D. J., Hickey, J. W., Kennedy‐Darling, J., Venkataraaman, V. G., Samusik, N., Goltsev, Y., Schürch, C. M., & Nolan, G. P. (2021) · Nature Protocols · doi:10.1038/s41596-021-00556-8 · Cited by 668 · see citing works
Self-citationRevealing the vectors of cellular identity with single-cell genomics
Wagner, A., Regev, A., & Yosef, N. (2016) · Nature Biotechnology · doi:10.1038/nbt.3711 · Cited by 632 · see citing works
Single-cell transcriptomics to explore the immune system in health and disease
Stubbington, M. J. T., Rozenblatt–Rosen, O., Regev, A., & Teichmann, S. A. (2017) · Science · doi:10.1126/science.aan6828 · Cited by 560 · see citing works
Guidelines for the use of flow cytometry and cell sorting in immunological studies *
Cossarizza, A., Chang, H., Radbruch, A., Akdiş, M., Andrä, I., Annunziato, F., Bächer, P., Barnaba, V., Battistini, L., Bauer, W. M., et al. (2017) · European Journal of Immunology · doi:10.1002/eji.201646632 · Cited by 572 · see citing works
Applications of multi‐omics analysis in human diseases
Chen, C., Wang, J., Pan, D., Wang, X., Xu, Y., Yan, J., Wang, L., Yang, X., Yang, M., & Liu, G. (2023) · MedComm · doi:10.1002/mco2.315 · Cited by 545 · see citing works
Single-cell multiomics: technologies and data analysis methods
Lee, J., Hyeon, D. Y., & Hwang, D. (2020) · Experimental & Molecular Medicine · doi:10.1038/s12276-020-0420-2 · Cited by 524 · see citing works
Multiplexed protein maps link subcellular organization to cellular states
Gut, G., Herrmann, M. D., & Pelkmans, L. (2018) · Science · doi:10.1126/science.aar7042 · Cited by 510 · see citing works
Single-cell multiomics: multiple measurements from single cells
Macaulay, I. C., Ponting, C. P., & Voet, T. (2017) · Trends in Genetics · doi:10.1016/j.tig.2016.12.003 · Cited by 451 · see citing works
MIBI-TOF: A multiplexed imaging platform relates cellular phenotypes and tissue structure
Keren, L., Bosse, M. M., Thompson, S., Risom, T., Vijayaragavan, K., McCaffrey, E., Marquez, D. M., Angoshtari, R., Greenwald, N. F., Fienberg, H. G., et al. (2019) · Science Advances · doi:10.1126/sciadv.aax5851 · Cited by 441 · see citing works
Self-citationCompensation of Signal Spillover in Suspension and Imaging Mass Cytometry
Chevrier, S., Crowell, H. L., Zanotelli, V. R., Engler, S., Robinson, M. D., & Bodenmiller, B. (2018) · Cell Systems · doi:10.1016/j.cels.2018.02.010 · Cited by 407 · see citing works
Single-cell proteomics enabled by next-generation sequencing or mass spectrometry
Bennett, H. M., Stephenson, W., Rose, C. M., & Darmanis, S. (2023) · Nature Methods · doi:10.1038/s41592-023-01791-5 · Cited by 351 · see citing works
Highly Sensitive and Multiplexed Protein Measurements
Cohen, L., & Walt, D. R. (2018) · Chemical Reviews · doi:10.1021/acs.chemrev.8b00257 · Cited by 294 · see citing works
Schulz, D., Zanotelli, V. R., Fischer, J. R., Schapiro, D., Engler, S., Lun, X., Jackson, H. W., & Bodenmiller, B. (2017) · Cell Systems · doi:10.1016/j.cels.2017.12.001 · Cited by 279 · see citing works
Single‐Cell Mass Spectrometry Approaches to Explore Cellular Heterogeneity
Zhang, L., & Vértes, Á. (2017) · Angewandte Chemie International Edition · doi:10.1002/anie.201709719 · Cited by 277 · see citing works
Integrative Methods and Practical Challenges for Single-Cell Multi-omics
Ma, A., McDermaid, A., Xu, J., Chang, Y., & Ma, Q. (2020) · Trends in biotechnology · doi:10.1016/j.tibtech.2020.02.013 · Cited by 272 · see citing works
Challenges in measuring and understanding biological noise
Eling, N., Morgan, M. D., & Marioni, J. C. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0130-6 · Cited by 247 · see citing works
Single-cell analysis targeting the proteome
Labib, M., & Kelley, S. O. (2020) · Nature Reviews Chemistry · doi:10.1038/s41570-020-0162-7 · Cited by 233 · see citing works
Yellow Fever Virus: Knowledge Gaps Impeding the Fight Against an Old Foe
Douam, F., & Ploß, A. (2018) · Trends in Microbiology · doi:10.1016/j.tim.2018.05.012 · Cited by 217 · see citing works
Single-Cell (Multi)omics Technologies
Chappell, L., Russell, A. J. C., & Voet, T. (2018) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-091416-035324 · Cited by 206 · see citing works
Cyclic Immunofluorescence (CycIF), A Highly Multiplexed Method for Single‐cell Imaging
Lin, J., Fallahi‐Sichani, M., Chen, J., & Sorger, P. K. (2016) · Current Protocols in Chemical Biology · doi:10.1002/cpch.14 · Cited by 208 · see citing works
Immune monitoring using mass cytometry and related high-dimensional imaging approaches
Hartmann, F. J., & Bendall, S. C. (2019) · Nature Reviews Rheumatology · doi:10.1038/s41584-019-0338-z · Cited by 203 · see citing works
Advanced liquid biopsy technologies for circulating biomarker detection
Soda, N., Rehm, B. H. A., Sonar, P. M., Nguyen, N., & Shiddiky, M. J. A. (2019) · Journal of Materials Chemistry B · doi:10.1039/c9tb01490j · Cited by 198 · see citing works
Single Cell Multi-Omics Technology: Methodology and Application
Hu, Y., An, Q., Sheu, K. M., Trejo, B. M., Fan, S., & Guo, Y. Q. (2018) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2018.00028 · Cited by 192 · see citing works
The tumor microenvironment’s role in the response to immune checkpoint blockade
Aliazis, K., Christofides, A., Shah, R., Yeo, Y. Y., Jiang, S., Charest, A., & Boussiotis, V. A. (2025) · Nature Cancer · doi:10.1038/s43018-025-00986-3 · Cited by 203 · see citing works
Digital Quantification of Proteins and mRNA in Single Mammalian Cells
Albayrak, C., Jordi, C. A., Zechner, C., Lin, J., Bichsel, C. A., Khammash, M., & Tay, S. (2016) · Molecular Cell · doi:10.1016/j.molcel.2016.02.030 · Cited by 176 · see citing works
Multiplexed, targeted profiling of single-cell proteomes and transcriptomes in a single reaction
Genshaft, A. S., Li, S., Gallant, C. J., Darmanis, S., Prakadan, S. M., Ziegler, C. G. K., Lundberg, M., Fredriksson, S., Hong, J., Regev, A., et al. (2016) · Genome Biology · doi:10.1186/s13059-016-1045-6 · Cited by 175 · see citing works
Spatial imaging of glycoRNA in single cells with ARPLA
Ma, Y., Guo, W., Mou, Q., Shao, X., Lyu, M., Garcia, V., Kong, L., Lewis, W. C., Ward, C. R., Yang, Z., et al. (2023) · Nature Biotechnology · doi:10.1038/s41587-023-01801-z · Cited by 167 · see citing works
Flow Cytometry: Principles, Applications and Recent Advances
Manohar, S. M., Shah, P., & Nair, A. (2021) · Bioanalysis · doi:10.4155/bio-2020-0267 · Cited by 158 · see citing works
Cho, S., Yang, H. C., & Rhee, W. J. (2019) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2019.111749 · Cited by 149 · see citing works
Nanopore DNA sequencing technologies and their applications towards single-molecule proteomics
Dorey, A., & Howorka, S. (2024) · Nature Chemistry · doi:10.1038/s41557-023-01322-x · Cited by 149 · see citing works
Nanoarchitecture Frameworks for Electrochemical miRNA Detection
Masud, M. K., Umer, M., Hossain, M. S. A., Yamauchi, Y., Nguyen, N., & Shiddiky, M. J. A. (2019) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2018.11.012 · Cited by 144 · see citing works
Iyer, A., Hamers, A. A. J., & Pillai, A. B. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.815828 · Cited by 140 · see citing works
Zuo, C., & Chen, L. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbaa287 · Cited by 126 · see citing works
Zhu, H., Zou, G., Wang, N., Zhuang, M., Xiong, W., & Huang, G. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1615557114 · Cited by 133 · see citing works
A combined approach for single-cell mRNA and intracellular protein expression analysis
Reimegård, J., Tarbier, M., Danielsson, M., Schuster, J., Baskaran, S., Panagiotou, S., Dahl, N., Friedländer, M. R., & Gallant, C. J. (2021) · Communications Biology · doi:10.1038/s42003-021-02142-w · Cited by 129 · see citing works
Bordt, E. A., Ceasrine, A. M., & Bilbo, S. D. (2020) · Glia · doi:10.1002/glia.23753 · Cited by 118 · see citing works
Yuan, B., Shen, C., Luna, A., Korkut, A., Marks, D. S., Ingraham, J., & Sander, C. (2020) · Cell Systems · doi:10.1016/j.cels.2020.11.013 · Cited by 128 · see citing works
Sévère, N., Karabacak, M., Gustafsson, K. U., Baryawno, N., Courties, G., Kfoury, Y. S., Kokkaliaris, K. D., Rhee, C., Lee, D., Scadden, E. W., et al. (2019) · Cell stem cell · doi:10.1016/j.stem.2019.06.003 · Cited by 118 · see citing works
Islam, M. N., Masud, M. K., Haque, M. H., Hossain, M. S. A., Yamauchi, Y., Nguyen, N., & Shiddiky, M. J. A. (2017) · Small Methods · doi:10.1002/smtd.201700131 · Cited by 115 · see citing works
Imaging approaches to optimize molecular therapies
Weissleder, R., Schwaiger, M. C., Gambhir, S. S., & Hricak, H. (2016) · Science Translational Medicine · doi:10.1126/scitranslmed.aaf3936 · Cited by 112 · see citing works
Computational strategies for single-cell multi-omics integration
Adossa, N. A., Khan, S., Rytkönen, K. T., & Elo, L. L. (2021) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2021.04.060 · Cited by 106 · see citing works
Automated cell-type classification in intact tissues by single-cell molecular profiling
Nagendran, M., Riordan, D. P., Harbury, P. B., & Desai, T. (2018) · eLife · doi:10.7554/elife.30510 · Cited by 105 · see citing works
Basic principles of hydrogel-based tissue transformation technologies and their applications
Choi, S. W., Guan, W., & Chung, K. (2021) · Cell · doi:10.1016/j.cell.2021.07.009 · Cited by 105 · see citing works
Gerlach, J. P., van Buggenum, J. A. G., Tanis, S. E. J., Hogeweg, M., Heuts, B. M. H., Muraro, M. J., Elze, L., Rivello, F., Rakszewska, A., van Oudenaarden, A., et al. (2019) · Scientific Reports · doi:10.1038/s41598-018-37977-7 · Cited by 104 · see citing works
Advanced model systems and tools for basic and translational human immunology
Wagar, L. E., DiFazio, R. M., & Davis, M. M. (2018) · Genome Medicine · doi:10.1186/s13073-018-0584-8 · Cited by 102 · see citing works
Quantification of tumor heterogeneity: from data acquisition to metric generation
Kashyap, A., Rapsomaniki, M., Barros, V., Khartchenko, A. F., Martinelli, A. L., Foncubierta–Rodríguez, A., Gabrani, M., Rosen‐Zvi, M., & Kaigala, G. V. (2021) · Trends in biotechnology · doi:10.1016/j.tibtech.2021.11.006 · Cited by 104 · see citing works
Remnestål, J., Just, D., Mitsios, N., Fredolini, C., Mulder, J., Schwenk, J. M., Uhlén, M., Kultima, K., Ingelsson, M., Kilander, L., et al. (2016) · PROTEOMICS - CLINICAL APPLICATIONS · doi:10.1002/prca.201500150 · Cited by 97 · see citing works
Jiang, S., Chan, C. N., Rovira‐Clavé, X., Chen, H. M., Bai, Y., Zhu, B., McCaffrey, E., Greenwald, N. F., Liu, C. C., Barlow, G. L., et al. (2021) · Immunity · doi:10.1016/j.immuni.2022.03.020 · Cited by 94 · see citing works
Self-citationBiosensors for early diagnosis of pancreatic cancer: a review
Qian, L., Li, Q., Baryeh, K., Qiu, W., Li, K., Zhang, J., Yu, Q., Xu, D., Liu, W., Brand, R. E., et al. (2019) · Translational research · doi:10.1016/j.trsl.2019.08.002 · Cited by 92 · see citing works
Single cell protein analysis for systems biology
Levy, E., & Slavov, N. (2018) · Essays in Biochemistry · doi:10.1042/ebc20180014 · Cited by 73 · see citing works
Recent advances in single extracellular vesicle detection methods
Wang, S., Khan, A., Huang, R., Ye, S., Di, K., Xiong, T., & Li, Z. (2020) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2020.112056 · Cited by 87 · see citing works
Allam, M., Cai, S., & Coskun, A. F. (2020) · npj Precision Oncology · doi:10.1038/s41698-020-0114-1 · Cited by 93 · see citing works
Fan, B.-L., Chen, L.-H., Chen, L., & Guo, H. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26041466 · Cited by 98 · see citing works
Klebes, A., Ates, H. C., Verboket, R. D., Urban, G. A., von Stetten, F., Dincer, C., & Früh, S. M. (2023) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2023.115800 · Cited by 90 · see citing works
Su, Y., Shi, Q., & Wei, W. (2017) · PROTEOMICS · doi:10.1002/pmic.201600267 · Cited by 86 · see citing works
Machine learning: its challenges and opportunities in plant system biology
Hesami, M., Alizadeh, M., Jones, A. M. P., & Torkamaneh, D. (2022) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-022-11963-6 · Cited by 87 · see citing works
Bayesian inference of gene expression states from single-cell RNA-seq data
Breda, J., Zavolan, M., & van Nimwegen, E. (2021) · Nature Biotechnology · doi:10.1038/s41587-021-00875-x · Cited by 87 · see citing works
Into the multiverse: advances in single-cell multiomic profiling
Ogbeide, S., Giannese, F., Mincarelli, L., & Macaulay, I. C. (2022) · Trends in Genetics · doi:10.1016/j.tig.2022.03.015 · Cited by 82 · see citing works
Enhancing clinical potential of liquid biopsy through a multi-omic approach: A systematic review
Sario, G. D., Rossella, V., Famulari, E. S., Maurizio, A., Lazarević, D., Giannese, F., & Felici, C. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2023.1152470 · Cited by 87 · see citing works
Immunology in the Era of Single-Cell Technologies
Efremova, M., Vento‐Tormo, R., Park, J.-E., Teichmann, S. A., & James, K. R. (2020) · Annual Review of Immunology · doi:10.1146/annurev-immunol-090419-020340 · Cited by 77 · see citing works
Single-cell omics: experimental workflow, data analyses and applications
Sun, F., Li, H., Sun, D., Fu, S., Gu, L., Shao, X., Wang, Q., Dong, X., Duan, B., Xing, F., et al. (2024) · Science China Life Sciences · doi:10.1007/s11427-023-2561-0 · Cited by 81 · see citing works
Soares, R. R. G., Madaboosi, N., & Nilsson, M. F. (2021) · Accounts of Chemical Research · doi:10.1021/acs.accounts.1c00438 · Cited by 78 · see citing works
Paper-Based Strips for the Electrochemical Detection of Single and Double Stranded DNA
Cinti, S., Proietti, E., Casotto, F., Moscone, D., & Arduini, F. (2018) · Analytical Chemistry · doi:10.1021/acs.analchem.8b04052 · Cited by 74 · see citing works
The Human Cell AtlasPreprint
Regev, A., Teichmann, S. A., Lander, E. S., Amit, I., Benoist, C. O., Birney, E., Bodenmiller, B., Campbell, P. J., Carninci, P., Clatworthy, M. R., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/121202 · Cited by 76 · see citing works
Self-citationDeep Profiling of Cellular Heterogeneity by Emerging Single‐Cell Proteomic Technologies
Yang, L., George, J., & Wang, J. (2019) · PROTEOMICS · doi:10.1002/pmic.201900226 · Cited by 70 · see citing works
ICP-MS and trace element analysis as tools for better understanding medical conditions
Amais, R. S., Donati, G. L., & Arruda, M. A. Z. (2020) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2020.116094 · Cited by 70 · see citing works
Statistical single cell multi-omics integration
Colomé‐Tatché, M., & Theis, F. J. (2018) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2018.01.003 · Cited by 70 · see citing works
Cell size assays for mass cytometry
Stern, A. D., Rahman, A. H., & Birtwistle, M. R. (2016) · Cytometry Part A · doi:10.1002/cyto.a.23000 · Cited by 65 · see citing works
The Spatial and Genomic Hierarchy of Tumor Ecosystems Revealed by Single-Cell Technologies
Smith, E. A., & Hodges, H. C. (2019) · Trends in cancer · doi:10.1016/j.trecan.2019.05.009 · Cited by 64 · see citing works
Rolling circle amplification for single cell analysis and in situ sequencing
Gao, H., Zhang, K., Teng, X., & Li, J. (2019) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2019.115700 · Cited by 63 · see citing works
Progress and applications of mass cytometry in sketching immune landscapes
Zhang, T., Warden, A. R., Li, Y., & Ding, X. (2020) · Clinical and Translational Medicine · doi:10.1002/ctm2.206 · Cited by 62 · see citing works
Microchip-based single-cell functional proteomics for biomedical applications
Lu, Y., Liu, Y., Wei, W., & Shi, Q. (2017) · Lab on a Chip · doi:10.1039/c7lc00037e · Cited by 60 · see citing works
Vries, N. L. D., Mahfouz, A. E., Koning, F., & de Miranda, N. F. C. C. (2020) · Frontiers in Oncology · doi:10.3389/fonc.2020.01254 · Cited by 58 · see citing works
Fibroblasts: Diverse Cells Critical to Biomaterials Integration
Hannan, R. T., Peirce, S. M., & Barker, T. H. (2018) · ACS Biomaterials Science & Engineering · doi:10.1021/acsbiomaterials.7b00244 · Cited by 59 · see citing works
How Clinical Flow Cytometry Rebooted Sepsis Immunology
Monneret, G., Gossez, M., Aghaeepour, N., Gaudilliere, B. L., & Venet, F. (2019) · Cytometry Part A · doi:10.1002/cyto.a.23749 · Cited by 59 · see citing works
Highly efficient and robust π-FISH rainbow for multiplexed in situ detection of diverse biomolecules
Tao, Y., Zhou, X., Sun, L., Lin, D., Cai, H., Chen, X., Zhou, W., Yang, B., Hu, Z., Yu, J., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-36137-4 · Cited by 58 · see citing works
Gao, Y., Huang, K., Wang, F., Hou, Y., Xu, J. J., & Li, G. (2022) · The Analyst · doi:10.1039/d2an00556e · Cited by 57 · see citing works
Re-Evaluating the Conventional Wisdom about Binding Assays
Wilson, B. D., & Soh, H. T. (2020) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2020.04.005 · Cited by 56 · see citing works
Single cell transcriptomics: moving towards multi-omics
Song, Y., Xu, X., Wang, W., Tian, T., Zhu, Z., & Yang, C. J. (2019) · The Analyst · doi:10.1039/c8an01852a · Cited by 56 · see citing works
Yu, J., Peng, J., & Chi, H. (2019) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2019.03.003 · Cited by 60 · see citing works
High-Fidelity Nanopore Sequencing of Ultra-Short DNA Targets
Wilson, B. D., Eisenstein, M. S., & Soh, H. T. (2019) · Analytical Chemistry · doi:10.1021/acs.analchem.9b00856 · Cited by 56 · see citing works
Inflammatory Bowel Disease Through the Lens of Single-cell RNA-seq Technologies
Corridoni, D., Chapman, T., Antanaviciute, A., Satsangi, J. J., & Simmons, A. (2020) · Inflammatory Bowel Diseases · doi:10.1093/ibd/izaa089 · Cited by 54 · see citing works
The Intriguing Landscape of Single‐Cell Protein Analysis
Xie, H., & Ding, X. (2022) · Advanced Science · doi:10.1002/advs.202105932 · Cited by 52 · see citing works
Robust single-cell matching and multimodal analysis using shared and distinct features
Zhu, B., Chen, S., Bai, Y., Chen, H. M., Liao, G., Mukherjee, N., Vazquez, G., McIlwain, D. R., Tzankov, A., Lee, I. T., et al. (2023) · Nature Methods · doi:10.1038/s41592-022-01709-7 · Cited by 49 · see citing works
Self-citationFulcher, J. M., Markillie, L. M., Mitchell, H. D., Williams, S., Engbrecht, K. M., Degnan, D. J., Bramer, L., Moore, R., Chrisler, W., Cantlon-Bruce, J., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-54099-z · Cited by 72 · see citing works
Handly, L. N., Yao, J. J., & Wollman, R. (2016) · Journal of Molecular Biology · doi:10.1016/j.jmb.2016.07.009 · Cited by 51 · see citing works
Applications of Single-Cell Omics in Tumor Immunology
Liu, J., Qu, S., Zhang, T., Gao, Y., Shi, H., Song, K., Chen, W., & Yin, W. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.697412 · Cited by 52 · see citing works
Single cell analysis of normal and leukemic hematopoiesis
Povinelli, B. J., Rodríguez-Meira, A., & Mead, A. J. (2017) · Molecular Aspects of Medicine · doi:10.1016/j.mam.2017.08.006 · Cited by 47 · see citing works
- Authors
- Frei, A. P., Bava, F.-A., Zunder, E. R., Hsieh, E. W. Y., Chen, S.-Y., Nolan, G. P., & Gherardini, P. F.
- Affiliations
- Stanford University (US)
- University of Virginia (US)
- University of Colorado Denver (US)
- Corresponding author
- Nolan, Garry P
- Gherardini, Pier Federico
- ORCID
- Venue
- Nature Methods
- Published
- 2016-01-25
- Volume
- 13
- Issue
- 3
- Pages
- 269-275
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- PMC
- PMC4767631
- OpenAlex
- W2253972942
- Cited by
- 330
- References
- 51
- Citations by year
- 2026: 8 · 2025: 20 · 2024: 24 · 2023: 32 · 2022: 29 · 2021: 31 · 2020: 35 · 2019: 45 · 2018: 43 · 2017: 42 · 2016: 20
- FWCI
- 25.98
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature Methods (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (5r01ca196657-02, n01hv28183-13-0-0, 5r01hl120724-05)
- National Heart, Lung, and Blood Institute (N01 HV028183, HHSN268201000034C, R01 - HL120724)
- National Cancer Institute (R33CA183654, R21CA183660, R33CA183692, R01CA184968, 1R01CA19665701)
- National Institute of General Medical Sciences (R01GM109836, 1R01GM10983601)
- National Institute of Allergy and Infectious Diseases (U19AI100627, P01AI036535, U19AI057229, T32AI007328)
- National Institute of Neurological Disorders and Stroke (1R01NS08953301, R01NS089533)
- National Institute of Arthritis and Musculoskeletal and Skin Diseases (UH2AR067676)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (K12HD000850)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Biotin and Related Studies
- Keywords
- single-cell transcriptomics, single-cell proteomics, mass cytometry, flow cytometry, cellular metabolism, deep phenotyping, primary cells
- MeSH terms
- Flow Cytometry, Humans, Proteins, RNA, Jurkat Cells, Protein Array Analysis, High-Throughput Screening Assays, High-Throughput Nucleotide Sequencing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review