Single-cell RNA-seq: advances and future challenges
Open accessAbstract
Phenotypically identical cells can dramatically vary with respect to behavior during their lifespan and this variation is reflected in their molecular composition such as the transcriptomic landscape. Single-cell transcriptomics using next-generation transcript sequencing (RNA-seq) is now emerging as a powerful tool to profile cell-to-cell variability on a genomic scale. Its application has already greatly impacted our conceptual understanding of diverse biological processes with broad implications for both basic and clinical research. Different single-cell RNA-seq protocols have been introduced and are reviewed here-each one with its own strengths and current limitations. We further provide an overview of the biological questions single-cell RNA-seq has been used to address, the major findings obtained from such studies, and current challenges and expected future developments in this booming field.
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?
Hi-C and single-cell sequencing had not been fully integrated at scale with brain genomics data.
“new methodologies, such as Hi-C and single-cell sequencing, have yet to be fully integrated at scale with brain genomics data (13–16).”
From Comprehensive functional genomic resource and integrative model for the human brain (2018) · cites this paper as [15]
The regulatory network contains 43,181 proximal and 42,681 distal linkages involving 11,573 protein-encoding target genes.
“This includes 43,181 proximal and 42,681 distal linkages involving 11,573 protein-encoding target genes (TF–to–target gene via promoter for proximal versus via enhancer–target gene connection for distal) (Fig. 5A) (15, 21).”
From Comprehensive functional genomic resource and integrative model for the human brain (2018) · cites this paper as [15]
The authors determined which modules were prioritized and the sets of genes associated with latent nodes at each hidden layer.
“Using it, we determined which modules were prioritized, as well as the sets of genes associated with latent nodes that were found at each hidden layer (Fig. 8A and table S10) (15, 21).”
From Comprehensive functional genomic resource and integrative model for the human brain (2018) · cites this paper as [15]
Current single-cell techniques suffer from low sensitivity and dropouts, making it challenging to reliably quantify low-abundance transcripts.
“In addition, current single-cell techniques suffer from low sensitivity and dropouts; thus, it remains challenging to reliably quantify low-abundance transcripts (15, 53).”
From Comprehensive functional genomic resource and integrative model for the human brain (2018) · cites this paper as [15]
This is particularly the case for specific brain cell substructures, such as axons and dendrites.
“This is particularly the case for specific brain cell substructures, such as axons and dendrites (15).”
From Comprehensive functional genomic resource and integrative model for the human brain (2018) · cites this paper as [15]
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
RNA-Seq: a revolutionary tool for transcriptomics
Wang, Z., Gerstein, M., & Snyder, M. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2484 · Cited by 13,174 · see citing works
Trapnell, C., Cacchiarelli, D., Grimsby, J., Pokharel, P., Li, S., Morse, M., Lennon, N. J., Livak, K. J., Mikkelsen, T. S., & Rinn, J. L. (2014) · Nature Biotechnology · doi:10.1038/nbt.2859 · Cited by 7,314 · see citing works
Sequencing technologies – the next generation
Metzker, M. L. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2626 · Cited by 7,066 · see citing works
Landscape of transcription in human cells
Djebali, S., Davis, C. A., Merkel, A., Dobin, A., Lassmann, T., Mortazavi, A., Tanzer, A., Lagarde, J., Lin, W., Schlesinger, F., et al. (2012) · Nature · doi:10.1038/nature11233 · Cited by 5,187 · see citing works
Derrien, T., Johnson, R., Bussotti, G., Andrea Tanzer, A., Djebali, S., Tilgner, H., Guernec, G., Martin, D., Merkel, A., Knowles, D. G., et al. (2012) · Genome Research · doi:10.1101/gr.132159.111 · Cited by 5,017 · see citing works
miRBase: annotating high confidence microRNAs using deep sequencing data
Kozomara, A., & Griffiths-Jones, S. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1181 · Cited by 4,629 · see citing works
Manipulating the mouse embryo: A laboratory manual
Hogan, B., Costantini, F. D., & Lacy, E. (1986) · Cited by 4,467 · 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
Tissue microarrays for high-throughput molecular profiling of tumor specimens
Kononen, J., Bubendorf, L., Kallionimeni, A., Barlund, M. T., Schraml, P., Leighton, S. B., Torhorst, J. K. H., Mihatsch, M. J., Sauter, G., & Kallionimeni, O.-P. (1998) · Nature Medicine · doi:10.1038/nm0798-844 · Cited by 4,101 · see citing works
mRNA-Seq whole-transcriptome analysis of a single cell
Tang, F., Barbacioru, C., Wang, Y., Nordman, E., Lee, C., Xu, N., Wang, X., Bodeau, J., Tuch, B. B., Siddiqui, A., et al. (2009) · Nature Methods · doi:10.1038/nmeth.1315 · Cited by 3,969 · see citing works
Genome-Wide Analysis in Vivo of Translation with Nucleotide Resolution Using Ribosome Profiling
Ingolia, N. T., Ghaemmaghami, S., Newman, J. R. S., & Weissman, J. S. (2009) · Science · doi:10.1126/science.1168978 · Cited by 3,853 · see citing works
Post-embryonic cell lineages of the nematode, Caenorhabditis elegans
Sulston, J. E., & Horvitz, H. R. (1977) · Developmental Biology · doi:10.1016/0012-1606(77)90158-0 · Cited by 3,479 · see citing works
The present and future role of microfluidics in biomedical research
Sackmann, E. K., Fulton, A. L., & Beebe, D. J. (2014) · Nature · doi:10.1038/nature13118 · Cited by 2,995 · see citing works
A Chromatin-Mediated Reversible Drug-Tolerant State in Cancer Cell Subpopulations
Sharma, S. V., Lee, D. Y., Li, B., Quinlan, M. P., Takahashi, F., Maheswaran, S., McDermott, U., Azizian, N., Zou, L., Fischbach, M. A., et al. (2010) · Cell · doi:10.1016/j.cell.2010.02.027 · Cited by 2,770 · see citing works
The potential and challenges of nanopore sequencing
Branton, D., Deamer, D. W., Marziali, A., Bayley, H., Benner, S. A., Butler, T. J., Ventra, M. D., Garaj, S., Hibbs, A. H., Huang, X. C., et al. (2008) · Nature Biotechnology · doi:10.1038/nbt.1495 · Cited by 2,534 · see citing works
RNA Maps Reveal New RNA Classes and a Possible Function for Pervasive Transcription
Kapranov, P., Cheng, J., Dike, S., Nix, D. A., Duttagupta, R., Willingham, A. T., Stadler, P. F., Jana Hertel, A., Jörg Hackermüller, A., Hofacker, I. L., et al. (2007) · Science · doi:10.1126/science.1138341 · Cited by 2,519 · see citing works
The Transcriptional Landscape of the Yeast Genome Defined by RNA Sequencing
Nagalakshmi, U., Wang, Z., Waern, K., Shou, C., Raha, D., Gerstein, M., & Snyder, M. (2008) · Science · doi:10.1126/science.1158441 · Cited by 2,479 · see citing works
Circulating Breast Tumor Cells Exhibit Dynamic Changes in Epithelial and Mesenchymal Composition
Yu, M., Bardia, A., Wittner, B. S., Stott, S. L., Smas, M. E., Ting, D. T., Isakoff, S. J., Ciciliano, J. C., Wells, M. N., Shah, A. M., et al. (2013) · Science · doi:10.1126/science.1228522 · Cited by 2,476 · see citing works
Insights into the phylogeny and coding potential of microbial dark matter
Rinke, C., Schwientek, P., Sczyrba, A., Ivanova, N. N., Anderson, I. J., Cheng, J.-F., Darling, A., Malfatti, S., Swan, B. K., Gies, E. A., et al. (2013) · Nature · doi:10.1038/nature12352 · Cited by 2,394 · 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
Insights into RNA Biology from an Atlas of Mammalian mRNA-Binding Proteins
Castello, A., Fischer, B., Eichelbaum, K., Horos, R., Beckmann, B. M., Strein, C., Davey, N. E., Humphreys, D. T., Preiss, T., Steinmetz, L. M., et al. (2012) · Cell · doi:10.1016/j.cell.2012.04.031 · Cited by 2,132 · see citing works
Taniguchi, Y., Choi, P. J., Li, G.-W., Chen, H., Babu, M., Hearn, J., Emili, A., & Xie, X. S. (2010) · Science · doi:10.1126/science.1188308 · Cited by 1,982 · cited 1× · see citing works
“As for bacteria, the average copy number of an mRNA in Escherichia coli is 0.4 per cell (40).”
InfluentialA human memory T cell subset with stem cell–like properties
Gattinoni, L., Lugli, E., Ji, Y., Pos, Z., Paulos, C. M., Quigley, M. F., Almeida, J. R., Gostick, E., Yu, Z., Carpenito, C., et al. (2011) · Nature Medicine · doi:10.1038/nm.2446 · Cited by 1,974 · see citing works
Massively 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
Single-cell RNA-Seq profiling of human preimplantation embryos and embryonic stem cells
Yan, L., Yang, M., Guo, H., Yang, L., Wu, J., Li, R., Liu, P., Lian, Y., Zheng, X., Yan, J., et al. (2013) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.2660 · Cited by 1,740 · 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
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
Reconstructing lineage hierarchies of the distal lung epithelium using single-cell RNA-seq
Treutlein, B., Brownfield, D. G., Wu, A. R., Neff, N. F., Mantalas, G. L., Espinoza, F. H., Desai, T. J., Krasnow, M. A., & Quake, S. R. (2014) · Nature · doi:10.1038/nature13173 · Cited by 1,342 · see citing works
Functions and Regulation of RNA Editing by ADAR Deaminases
Nishikura, K. (2010) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-060208-105251 · Cited by 1,303 · 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
Single-cell sequencing-based technologies will revolutionize whole-organism science
Shapiro, E., Biezuner, T., & Linnarsson, S. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3542 · Cited by 1,177 · see citing works
The primary transcriptome of the major human pathogen Helicobacter pylori
Sharma, C. M., Hoffmann, S., Darfeuille, F., Reignier, J., Findeiß, S., Sittka, A., Chabas, S., Reiche, K., Jörg Hackermüller, A., Reinhardt, R., et al. (2010) · Nature · doi:10.1038/nature08756 · Cited by 1,133 · see citing works
Self-citationEmre Özkumur, A., Shah, A. M., Ciciliano, J. C., Emmink, B. L., Miyamoto, D. T., Brachtel, E. F., Yu, M., Chen, P.-I., Morgan, B., Trautwein, J., et al. (2013) · Science Translational Medicine · doi:10.1126/scitranslmed.3005616 · Cited by 1,087 · see citing works
Transcriptome-wide noise controls lineage choice in mammalian progenitor cells
Chang, H. H., Hemberg, M., Barahona, M., Ingber, D. E., & Huang, S. (2008) · Nature · doi:10.1038/nature06965 · Cited by 1,067 · see citing works
Baccelli, I., Schneeweiß, A., Riethdorf, S., Stenzinger, A., Schillert, A., Vogel, V., Klein, C., Saini, M., Bäuerle, T., Wallwiener, M., et al. (2013) · Nature Biotechnology · doi:10.1038/nbt.2576 · Cited by 1,050 · see citing works
mRNA localization: Gene expression in the spatial dimension
Martin, K. C., & Ephrussi, A. (2009) · Cell · doi:10.1016/j.cell.2009.01.044 · Cited by 1,048 · see citing works
Counting absolute numbers of molecules using unique molecular identifiers
Kivioja, T., Vähärautio, A., Karlsson, K., Bonke, M., Enge, M., Linnarsson, S., & Taipale, J. (2012) · Nature Methods · doi:10.1038/nmeth.1778 · Cited by 1,010 · see citing works
RNA-Methylation-Dependent RNA Processing Controls the Speed of the Circadian Clock
Fustin, J., Doi, M., Yamaguchi, Y., Hayashi, H., Nishimura, S., Yoshida, M., Isagawa, T., Morioka, M. S., Kakeya, H., Manabe, I., et al. (2013) · Cell · doi:10.1016/j.cell.2013.10.026 · Cited by 980 · see citing works
Highly Multiplexed Subcellular RNA Sequencing in Situ
Lee, J. H., Daugharthy, E. R., Scheiman, J., Kalhor, R., Yang, J. L., Ferrante, T. C., Terry, R., Jeanty, S. S. F., Li, C., Amamoto, R., et al. (2014) · Science · doi:10.1126/science.1250212 · Cited by 973 · see citing works
Genetic programs in human and mouse early embryos revealed by single-cell RNA sequencing
Xue, Z., Huang, K., Cai, C., Cai, L., Jiang, C.-Y., Feng, Y., Liu, Z., Zeng, Q., Cheng, L., Sun, Y. E., et al. (2013) · Nature · doi:10.1038/nature12364 · Cited by 963 · see citing works
Analysis of gene expression in single live neurons.
Eberwine, J. H., Yeh, H., Miyashiro, K., Cao, Y., Nair, S., Finnell, R. H., Zettel, M. F., & Coleman, P. D. (1992) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.89.7.3010 · Cited by 953 · see citing works
Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq
Islam, S., Kjällquist, U., Moliner, A., Zajac, P., Fan, J.-B., Lönnerberg, P., & Linnarsson, S. (2011) · Genome Research · doi:10.1101/gr.110882.110 · Cited by 949 · see citing works
In situ sequencing for RNA analysis in preserved tissue and cells
Ke, R., Mignardi, M., Pacureanu, A., Svedlund, J., Botling, J., Wählby, C., & Nilsson, M. (2013) · Nature Methods · doi:10.1038/nmeth.2563 · Cited by 934 · see citing works
Nicolas, P., Mäder, U., Dervyn, E., Rochat, T., Leduc, A., Pigeonneau, N., Bidnenko, E., Marchadier, E., Hoebeke, M., Aymerich, S., et al. (2012) · Science · doi:10.1126/science.1206848 · Cited by 910 · see citing works
Genome-wide probing of RNA structure reveals active unfolding of mRNA structures in vivo
Rouskin, S., Zubradt, M. M., Stefan Washietl, A., Kellis, M., & Weissman, J. S. (2013) · Nature · doi:10.1038/nature12894 · Cited by 860 · see citing works
Mapping complex disease traits with global gene expression
Cookson, W., Liang, L., Abecasis, G., Moffatt, M., & Lathrop, M. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2537 · Cited by 849 · see citing works
Espina, V. A., Wulfkuhle, J. D., Calvert, V. S., VanMeter, A., Zhou, W., Coukos, G., Geho, D. H., Petricoin, E. F., & Liotta, L. A. (2006) · Nature Protocols · doi:10.1038/nprot.2006.85 · Cited by 847 · see citing works
Buganim, Y., Faddah, D. A., Cheng, A. W., Itskovich, E., Markoulaki, S., Ganz, K., Klemm, S. L., van Oudenaarden, A., & Jaenisch, R. (2012) · Cell · doi:10.1016/j.cell.2012.08.023 · Cited by 800 · see citing works
Hydrodynamic stretching of single cells for large population mechanical phenotyping
Gossett, D. R., Tse, H. T. K., Lee, S. A., Ying, Y., Lindgren, A., Yang, O. O., Rao, J., Clark, A. T., & Carlo, D. D. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1200107109 · Cited by 780 · see citing works
Zhu, Y., Machleder, E. M., Chenchik, A. A., Li, R., & Siebert, P. D. (2001) · BioTechniques · doi:10.2144/01304pf02 · Cited by 773 · see citing works
Microfluidic, marker-free isolation of circulating tumor cells from blood samples
Karabacak, M., Spuhler, P. S., Fachin, F., Lim, E. J., Pai, V., Emre Özkumur, A., Martel, J. M., Kojić, N., Smith, K., Chen, P.-I., et al. (2014) · Nature Protocols · doi:10.1038/nprot.2014.044 · Cited by 760 · see citing works
Dual RNA-seq of pathogen and host
Westermann, A. J., Gorski, S. A., & Vogel, J. (2012) · Nature Reviews Microbiology · doi:10.1038/nrmicro2852 · Cited by 754 · see citing works
Self-citationComprehensive comparative analysis of strand-specific RNA sequencing methods
Levin, J. Z., Yassour, M., Adiconis, X., Nusbaum, C., Thompson, D. A., Friedman, N., Gnirke, A., & Regev, A. (2010) · Nature Methods · doi:10.1038/nmeth.1491 · Cited by 753 · see citing works
Internalization of Salmonella by Macrophages Induces Formation of Nonreplicating Persisters
Hélaine, S., Cheverton, A. M., Watson, K. G., Faure, L. M., Matthews, S. A., & Holden, D. W. (2014) · Science · doi:10.1126/science.1244705 · Cited by 744 · see citing works
Hangauer, M. J., Vaughn, I. W., & McManus, M. T. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003569 · Cited by 738 · see citing works
Validation of noise models for single-cell transcriptomics
Grün, D., Kester, L., & van Oudenaarden, A. (2014) · Nature Methods · doi:10.1038/nmeth.2930 · Cited by 721 · see citing works
Genome-wide transcription and the implications for genomic organization
Kapranov, P., Willingham, A. T., & Gingeras, T. (2007) · Nature Reviews Genetics · doi:10.1038/nrg2083 · Cited by 720 · see citing works
A single-molecule long-read survey of the human transcriptome
Sharon, D., Tilgner, H., Grubert, F., & Snyder, M. (2013) · Nature Biotechnology · doi:10.1038/nbt.2705 · Cited by 701 · see citing works
Single-cell dissection of transcriptional heterogeneity in human colon tumors
Dalerba, P. D., Tomer Kalisky, C., Sahoo, D., Rajendran, P. S., Rothenberg, M. E., Leyrat, A. A., Sim, S., Okamoto, J., Johnston, D. M., Qian, D., et al. (2011) · Nature Biotechnology · doi:10.1038/nbt.2038 · Cited by 693 · see citing works
Gene expression profiles of laser-captured adjacent neuronal subtypes
Luo, L., Salunga, R. C., Guo, H., Bittner, A., Joy, K. C., Galindo, J. E., Xiao, H., Rogers, K. E., Wan, J. S., Jackson, M. R., et al. (1999) · Nature Medicine · doi:10.1038/4806 · Cited by 691 · 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
Marcy, Y., Ouverney, C., Bik, E. M., Lösekann, T., Ivanova, N., Martín, H. G., Szeto, E., Platt, D., Hugenholtz, P., Relman, D. A., et al. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0704662104 · Cited by 632 · see citing works
Gene regulation by antisense transcription
Pelechano, V., & Steinmetz, L. M. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3594 · Cited by 628 · see citing works
Schwartz, S., Agarwala, S. D., Mumbach, M. R., Jovanović, M., Mertins, P., Shishkin, A., Tabach, Y., Mikkelsen, T. S., Satija, R., Ruvkun, G., et al. (2013) · Cell · doi:10.1016/j.cell.2013.10.047 · Cited by 627 · see citing works
Deterministic hydrodynamics: Taking blood apart
Davis, J. A., Inglis, D. W., Morton, K. J., Lawrence, D. A., Huang, L. R., Chou, S. Y., Sturm, J. C., & Austin, R. H. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0605967103 · Cited by 623 · see citing works
Marguerat, S., Schmidt, A., Codlin, S., Chen, W., Aebersold, R., & Bähler, J. (2012) · Cell · doi:10.1016/j.cell.2012.09.019 · Cited by 571 · see citing works
Adey, A., Morrison, H. G., Asan, Xu, X., Kitzman, J. O., Turner, E. H., Stackhouse, B., MacKenzie, A. P., Caruccio, N. C., Zhang, X., et al. (2010) · Genome biology · doi:10.1186/gb-2010-11-12-r119 · Cited by 566 · see citing works
Single-Cell Gene Expression Profiling
Levsky, J. M., Shenoy, S. M., Pezo, R. C., & Singer, R. H. (2002) · Science · doi:10.1126/science.1072241 · Cited by 526 · see citing works
Tang, F., Bárbácioru, C., Bao, S., Lee, C. G. L., Nordman, E., Wang, X., Lao, K., & Surani, M. A. (2010) · Cell stem cell · doi:10.1016/j.stem.2010.03.015 · Cited by 499 · see citing works
RNA-Seq analysis to capture the transcriptome landscape of a single cell
Tang, F., Bárbácioru, C., Nordman, E., Li, B., Xu, N., Bashkirov, V. I., Lao, K., & Surani, M. A. (2010) · Nature Protocols · doi:10.1038/nprot.2009.236 · Cited by 487 · see citing works
RNA sequencing of pancreatic circulating tumour cells implicates WNT signalling in metastasis
Yu, M., Ting, D. T., Stott, S. L., Wittner, B. S., Ozsolak, F., Paul, S., Ciciliano, J. C., Smas, M. E., Winokur, D., Gilman, A. J., et al. (2012) · Nature · doi:10.1038/nature11217 · Cited by 484 · see citing works
Genetic Determinants and Cellular Constraints in Noisy Gene Expression
Sánchez, Á., & Golding, I. (2013) · Science · doi:10.1126/science.1242975 · Cited by 460 · 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
The Genomic and Transcriptomic Landscape of a HeLa Cell Line
Landry, J. J. M., Pyl, P. T., Rausch, T., Zichner, T., Tekkedil, M. M., Stütz, A. M., Jauch, A. S., Aiyar, R. S., Pau, G., Delhomme, N., et al. (2013) · G3 Genes Genomes Genetics · doi:10.1534/g3.113.005777 · Cited by 455 · see citing works
Extensive transcriptional heterogeneity revealed by isoform profiling
Pelechano, V., Wu, W., & Steinmetz, L. M. (2013) · Nature · doi:10.1038/nature12121 · Cited by 450 · see citing works
Vogel, J. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkg867 · Cited by 441 · see citing works
Self-citationHigh-throughput microfluidic single-cell RT-qPCR
White, A. K., VanInsberghe, M. A., Petriv, O. I., Hamidi, M., Sikorski, D., Marra, M. A., Piret, J. M., Aparicio, S. A. J. R., & Hansen, C. L. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1019446108 · Cited by 437 · see citing works
Genomewide characterization of non-polyadenylated RNAs
Yang, L. C., Duff, M. O., Graveley, B. R., Carmichael, G., & Chen, L. (2011) · Genome biology · doi:10.1186/gb-2011-12-2-r16 · Cited by 423 · see citing works
RNA-sequencing from single nuclei
Grindberg, R. V., Yee-Greenbaum, J. L., McConnell, M. J., Novotny, M., O’Shaughnessy, A. L., Lambert, G. M., Araúzo-Bravo, M. J., Lee, J., Fishman, M., Robbins, G. E., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1319700110 · Cited by 422 · see citing works
The complex eukaryotic transcriptome: unexpected pervasive transcription and novel small RNAs
Jacquier, A. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2683 · Cited by 421 · see citing works
Transcriptome complexity in a genome-reduced bacterium
Güell, M., van Noort, V., Yus, E., Chen, W.-H., Leigh-Bell, J., Michalodimitrakis, K., Yamada, T., Arumugam, M., Doerks, T., Kühner, S., et al. (2009) · Science · doi:10.1126/science.1176951 · Cited by 418 · see citing works
Kurimoto, K. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl050 · Cited by 403 · see citing works
Population context determines cell-to-cell variability in endocytosis and virus infection
Snijder, B., Sacher, R., Rämö, P., Damm, E.-M., Liberali, P., & Pelkmans, L. (2009) · Nature · doi:10.1038/nature08282 · Cited by 401 · see citing works
Mechanosensitive mechanisms in transcriptional regulation
Mammoto, A., Mammoto, T., & Ingber, D. E. (2012) · Journal of Cell Science · doi:10.1242/jcs.093005 · Cited by 393 · see citing works
cis-Antisense RNA, Another Level of Gene Regulation in Bacteria
Georg, J., & Hess, W. R. (2011) · Microbiology and Molecular Biology Reviews · doi:10.1128/mmbr.00032-10 · Cited by 392 · see citing works
High-throughput single-microparticle imaging flow analyzer
Goda, K., Ayazi, A., Gossett, D. R., Sadasivam, J., Lonappan, C. K., Sollier, E., Fard, A. M., Hur, S., Adam, J., Murray, C., et al. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1204718109 · Cited by 386 · see citing works
The transcriptional landscape and small RNAs of Salmonella enterica serovar Typhimurium
Kröger, C., Dillon, S. C., Cameron, A. D. S., Papenfort, K., Sivasankaran, S. K., Hokamp, K., Chao, Y., Sittka, A., Hébrard, M., Händler, K., et al. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1201061109 · Cited by 384 · see citing works
Self-citationQuantum dot semiconductor nanocrystals for immunophenotyping by polychromatic flow cytometry
Chattopadhyay, P. K., Price, D. A., Harper, T. F., Betts, M. R., Yu, J., Gostick, E., Perfetto, S. P., Goepfert, P., Koup, R. A., De Rosa, S. C., et al. (2006) · Nature Medicine · doi:10.1038/nm1371 · Cited by 372 · see citing works
Functional Roles of Pulsing in Genetic Circuits
Levine, J. H., Lin, Y., & Elowitz, M. B. (2013) · Science · doi:10.1126/science.1239999 · Cited by 369 · see citing works
Unfoldase-mediated protein translocation through an α-hemolysin nanopore
Nivala, J., Marks, D. B., & Akeson, M. A. (2013) · Nature Biotechnology · doi:10.1038/nbt.2503 · Cited by 362 · see citing works
A single-base resolution map of an archaeal transcriptomePreprint
Wurtzel, O., Sapra, R., Chen, F., Zhu, Y., Simmons, B. A., & Sorek, R. (2009) · Genome Research · doi:10.1101/gr.100396.109 · Cited by 356 · see citing works
Microfluidic sorting and multimodal typing of cancer cells in self-assembled magnetic arrays
Saliba, A., Saïas, L., Psychari, E., Minc, N., Simon, D., Bidard, F., Mathiot, C., Pierga, J., Fraisier, V., Salamero, J., et al. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1001515107 · Cited by 338 · see citing works
Self-citationSchneider, G. F., & Dekker, C. (2012) · Nature Biotechnology · doi:10.1038/nbt.2181 · Cited by 338 · see citing works
MicroRNA expression profiling of single whole embryonic stem cells
Tang, F. (2006) · Nucleic Acids Research · doi:10.1093/nar/gnj009 · Cited by 335 · see citing works
Ghosh, S., Spagnoli, G. C., Martin, I., Ploegert, S., Demougin, P., Heberer, M., & Reschner, A. (2005) · Journal of Cellular Physiology · doi:10.1002/jcp.20320 · Cited by 326 · see citing works
Eukaryotic transcriptional dynamics: from single molecules to cell populations
Coulon, A., Chow, C. C., Singer, R. H., & Larson, D. R. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3484 · Cited by 309 · see citing works
Blainey, P. C., Mosier, A. C., Potanina, A., Francis, C. A., & Quake, S. R. (2011) · PLoS ONE · doi:10.1371/journal.pone.0016626 · Cited by 305 · see citing works
Combined transcriptome and genome analysis of single micrometastatic cells
Klein, C. A., Seidl, S., Petat‐Dutter, K., Offner, S., Geigl, J. B., Schmidt‐Kittler, O., Wendler, N., Passlick, B., Huber, R. M., Schlimok, G., et al. (2002) · Nature Biotechnology · doi:10.1038/nbt0402-387 · Cited by 303 · see citing works
Ohnishi, Y., Huber, W., Tsumura, A., Kang, M., Xenopoulos, P., Kurimoto, K., Oleś, A. K., Araúzo-Bravo, M. J., Saitou, M., Hadjantonakis, A.-K., et al. (2014) · Nature Cell Biology · doi:10.1038/ncb2881 · Cited by 300 · see citing works
The future is now: single-cell genomics of bacteria and archaea
Blainey, P. C. (2013) · FEMS Microbiology Reviews · doi:10.1111/1574-6976.12015 · Cited by 299 · see citing works
Transcriptome in vivo analysis (TIVA) of spatially defined single cells in live tissue
Lovatt, D., Ruble, B. K., Lee, J., Dueck, H., Kim, T. K., Fisher, S., Francis, C., Spaethling, J. M., Wolf, J. A., Grady, M. S., et al. (2014) · Nature Methods · doi:10.1038/nmeth.2804 · Cited by 287 · see citing works
PCR-based cDNA library construction: general cDNA libraries at the level of a few cells
Belyavsky, A. V., Vinogradova, T., & Rajewsky, K. (1989) · Nucleic Acids Research · doi:10.1093/nar/17.8.2919 · Cited by 283 · see citing works
Comparative transcriptomics of pathogenic and non‐pathogenic Listeria species
Wurtzel, O., Sesto, N., Mellin, J. R., Karunker, I., Edelheit, S., Bécavin, C., Archambaud, C., Cossart, P., & Sorek, R. (2012) · Molecular Systems Biology · doi:10.1038/msb.2012.11 · Cited by 278 · see citing works
Metatranscriptomics reveals unique microbial small RNAs in the ocean’s water column
Shi, Y., Tyson, G. W., & DeLong, E. F. (2009) · Nature · doi:10.1038/nature08055 · Cited by 277 · see citing works
Dugar, G., Herbig, A., Förstner, K. U., Heidrich, N., Reinhardt, R., Nieselt, K., & Sharma, C. M. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003495 · Cited by 275 · see citing works
Microfluidic single-cell whole-transcriptome sequencing
Streets, A., Zhang, X., Cao, C., Pang, Y., Wu, X., Xiong, L., Yang, L., Fu, Y., Zhao, L., Tang, F., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1402030111 · Cited by 274 · see citing works
Highly 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
Global Analysis of mRNA Isoform Half-Lives Reveals Stabilizing and Destabilizing Elements in Yeast
Geisberg, J. V., Moqtaderi, Z., Fan, X., Ozsolak, F., & Struhl, K. (2014) · Cell · doi:10.1016/j.cell.2013.12.026 · Cited by 270 · see citing works
Quantitative Diagnosis of Malignant Pleural Effusions by Single-Cell Mechanophenotyping
Tse, H. T. K., Gossett, D. R., Moon, Y. S., Masaeli, M., Sohsman, M. Y., Ying, Y., Mislick, K., Adams, R. P., Rao, J., & Carlo, D. D. (2013) · Science Translational Medicine · doi:10.1126/scitranslmed.3006559 · Cited by 267 · see citing works
Isolation of a hyperthermophilic archaeum predicted by in situ RNA analysis
Huber, R., Burggraf, S., Mayer, T., Barns, S. M., Rossnagel, P., & STETTER, K. O. (1995) · Nature · doi:10.1038/376057a0 · Cited by 266 · see citing works
Clonally dominant cardiomyocytes direct heart morphogenesis
Gupta, V., & Poss, K. D. (2012) · Nature · doi:10.1038/nature11045 · Cited by 255 · see citing works
Genome-wide antisense transcription drives mRNA processing in bacteria
Lasa, Í., Toledo‐Arana, A., Dobin, A., Villanueva, M., Mozos, I. R. D. L., Vergara-Irigaray, M., Segura, V., Fagegaltier, D., Penadés, J. R., Valle, J., et al. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1113521108 · Cited by 249 · see citing works
Single-cell gene expression analysis reveals genetic associations masked in whole-tissue experiments
Wills, Q. F., Livak, K. J., Tipping, A. J., Enver, T., Goldson, A. J., Sexton, D. W., & Holmes, C. C. (2013) · Nature Biotechnology · doi:10.1038/nbt.2642 · Cited by 244 · see citing works
Comparison of Reverse Transcriptases in Gene Expression Analysis
Ståhlberg, A., Kubista, M., & Pfaffl, M. (2004) · Clinical Chemistry · doi:10.1373/clinchem.2004.035469 · Cited by 240 · see citing works
From single cells to deep phenotypes in cancer
Bendall, S. C., & Nolan, G. P. (2012) · Nature Biotechnology · doi:10.1038/nbt.2283 · Cited by 222 · see citing works
A global view of protein expression in human cells, tissues, and organs
Pontén, F., Gry, M., Fagerberg, L., Lundberg, E., Asplund, A., Berglund, L., Oksvold, P., Björling, E., Hober, S., Kampf, C., et al. (2009) · Molecular Systems Biology · doi:10.1038/msb.2009.93 · Cited by 222 · see citing works
Validation of two ribosomal RNA removal methods for microbial metatranscriptomics
He, S., Wurtzel, O., Singh, K., Froula, J. L., Yilmaz, S., Tringe, S. G., Wang, Z., Chen, F., Lindquist, E. A., Sorek, R., et al. (2010) · Nature Methods · doi:10.1038/nmeth.1507 · Cited by 219 · see citing works
Microfluidics separation reveals the stem-cell–like deformability of tumor-initiating cells
Zhang, W., Kai, K., Choi, D. S., Iwamoto, T., Nguyen, Y., Wong, H. H., Landis, M. D., Ueno, N. T., Chang, J. C., & Qin, L. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1209893109 · Cited by 210 · see citing works
Genomic Analysis at the Single-Cell Level
Tomer Kalisky, C., Blainey, P. C., & Quake, S. R. (2011) · Annual Review of Genetics · doi:10.1146/annurev-genet-102209-163607 · Cited by 203 · see citing works
Identification of regulatory RNAs in Bacillus subtilis
Irnov, I., Sharma, C. M., Vogel, J., & Winkler, W. C. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq454 · Cited by 199 · see citing works
Self-citationOxford Nanopore announcement sets sequencing sector abuzz
Eisenstein, M. S. (2012) · Nature Biotechnology · doi:10.1038/nbt0412-295 · Cited by 195 · see citing works
Kurimoto, K., Yabuta, Y., Ohinata, Y., & Saitou, M. (2007) · Nature Protocols · doi:10.1038/nprot.2007.79 · Cited by 186 · see citing works
Digital transcriptome profiling using selective hexamer priming for cDNA synthesis
Armour, C. D., Castle, J. C., Chen, R., Babak, T., Loerch, P., Jackson, S., Shah, J. K., Dey, J., Rohl, C. A., Johnson, J. M., et al. (2009) · Nature Methods · doi:10.1038/nmeth.1360 · Cited by 174 · see citing works
Comprehensive qPCR profiling of gene expression in single neuronal cells
Citri, A., Pang, Z. P., Südhof, T. C., Wernig, M., & Malenka, R. C. (2011) · Nature Protocols · doi:10.1038/nprot.2011.430 · Cited by 169 · see citing works
The intracellular sRNA transcriptome of Listeria monocytogenes during growth in macrophages
Mraheil, M. A., Billion, A., Mohamed, W. A., Mukherjee, K., Kuenne, C. T., Pischimarov, J., Krawitz, C., Retey, J., Hartsch, T., Chakraborty, T., et al. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr033 · Cited by 168 · see citing works
RNA editing in the human ENCODE RNA-seq dataPreprint
Park, E., Williams, B. A., Wold, B. J., & Mortazavi, A. (2012) · Genome Research · doi:10.1101/gr.134957.111 · Cited by 161 · see citing works
Huang, R., Barber, T. A., Schmidt, M. A., Tompkins, R. G., Toner, M., Bianchi, D. W., Kapur, R., & Flejter, W. L. (2008) · Prenatal Diagnosis · doi:10.1002/pd.2079 · Cited by 158 · see citing works
Methods for qPCR gene expression profiling applied to 1440 lymphoblastoid single cells
Livak, K. J., Wills, Q. F., Tipping, A. J., Datta, K., Mittal, R., Goldson, A. J., Sexton, D. W., & Holmes, C. C. (2012) · Methods · doi:10.1016/j.ymeth.2012.10.004 · Cited by 151 · see citing works
Deterministic and Stochastic Allele Specific Gene Expression in Single Mouse Blastomeres
Tang, F., Bárbácioru, C., Nordman, E., Bao, S., Lee, C. G. L., Wang, X., Tuch, B. B., Heard, É., Lao, K., & Surani, M. A. (2011) · PLoS ONE · doi:10.1371/journal.pone.0021208 · Cited by 150 · see citing works
Nygaard, V. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkj499 · Cited by 136 · see citing works
Cytometry: Today’s technology and tomorrow’s horizons
Chattopadhyay, P. K., & Roederer, M. (2012) · Methods · doi:10.1016/j.ymeth.2012.02.009 · Cited by 134 · see citing works
Identifying single-cell molecular programs by stochastic profiling
Janes, K. A., Wang, C., Holmberg, K. J., Cabral, K., & Brugge, J. S. (2010) · Nature Methods · doi:10.1038/nmeth.1442 · Cited by 130 · see citing works
Bacterial transcriptomics: what is beyond the RNA horiz-ome?
Güell, M., Yus, E., Lluch‐Senar, M., & Serrano, L. G. (2011) · Nature Reviews Microbiology · doi:10.1038/nrmicro2620 · Cited by 126 · see citing works
Nanopore-Based Identification of Individual Nucleotides for Direct RNA Sequencing
Ayub, M., Hardwick, S. W., Luisi, B. F., & Bayley, H. (2013) · Nano Letters · doi:10.1021/nl403469r · Cited by 126 · see citing works
Intuitive, Image-Based Cell Sorting Using Optofluidic Cell Sorting
Kovač, J., & Joel Voldman, B. (2007) · Analytical Chemistry · doi:10.1021/ac071366y · Cited by 125 · see citing works
Digital MDA for enumeration of total nucleic acid contamination
Blainey, P. C., & Quake, S. R. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq1074 · Cited by 123 · see citing works
Transcript amplification from single bacterium for transcriptome analysisPreprint
Kang, Y., Norris, M. H., Zarzycki‐Siek, J., Nierman, W. C., Donachie, S. P., & Hoang, T. T. (2011) · Genome Research · doi:10.1101/gr.116103.110 · Cited by 121 · see citing works
Going with the Flow: From Circulating Tumor Cells to DNA
Bidard, F., Weigelt, B., & Reis-Filho, J. S. (2013) · Science Translational Medicine · doi:10.1126/scitranslmed.3006305 · Cited by 118 · see citing works
New techniques for isolation of single prokaryotic cells
Fröhlich, J., & König, H. (2000) · FEMS Microbiology Reviews · doi:10.1111/j.1574-6976.2000.tb00558.x · Cited by 113 · see citing works
220-plex microRNA expression profile of a single cell
Tang, F., Hájková, P., Barton, S. C., O’Carroll, D., Lee, C. G. L., Lao, K., & Surani, M. A. (2006) · Nature Protocols · doi:10.1038/nprot.2006.161 · Cited by 110 · see citing works
Two methods for full-length RNA sequencing for low quantities of cells and single cells
Pan, X., Durrett, R., Zhu, H., Tanaka, Y., Li, Y., Zi, X., Marjani, S. L., Euskirchen, G. M., Ma, C., LaMotte, R. H., et al. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1217322109 · Cited by 110 · see citing works
High-Throughput Microfluidic Single-Cell Digital Polymerase Chain Reaction
White, A. K., Heyries, K. A., Doolin, C., VanInsberghe, M. A., & Hansen, C. L. (2013) · Analytical Chemistry · doi:10.1021/ac400896j · Cited by 107 · see citing works
An RNA degradosome assembly in Caulobacter crescentus
Hardwick, S. W., Chan, V. S. Y., Broadhurst, R. W., & Luisi, B. F. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq928 · Cited by 98 · see citing works
Arezi, B., & Hogrefe, H. H. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn952 · Cited by 96 · see citing works
The transcriptional landscape of Chlamydia pneumoniae
Albrecht, M., Sharma, C. M., Dittrich, M. T., Müller, T., Reinhardt, R., Vogel, J., & Rudel, T. (2011) · Genome biology · doi:10.1186/gb-2011-12-10-r98 · Cited by 81 · see citing works
Self-citationAn automated system for high-throughput single cell-based breeding
Yoshimoto, N., 木田, 晶., Xu, J., Kurokawa, M., Iijima, M., Niimi, T., Maturana, A. D., Nikaido, I., Ueda, H. R., Tatematsu, K., et al. (2013) · Scientific Reports · doi:10.1038/srep01191 · Cited by 79 · see citing works
Filby, A. J., Perucha, E., Summers, H. D., Rees, P. C. T., Chana, P. S., Heck, S., Lord, G. M., & Davies, D. C. (2011) · Cytometry Part A · doi:10.1002/cyto.a.21091 · Cited by 77 · see citing works
Individual RNA Base Recognition in Immobilized Oligonucleotides Using a Protein Nanopore
Ayub, M., & Bayley, H. (2012) · Nano Letters · doi:10.1021/nl3027873 · Cited by 76 · see citing works
New techniques for isolation of single prokaryotic cells
Fröhlich, J. ⁄. R. (2000) · FEMS Microbiology Reviews · doi:10.1016/s0168-6445(00)00045-0 · Cited by 74 · see citing works
Transcriptome Analysis of Single Cells
Morris, J. F., Singh, J. M., & Eberwine, J. H. (2011) · Journal of Visualized Experiments · doi:10.3791/2634 · Cited by 68 · see citing works
Gene expression profiling of single cells on large-scale oligonucleotide arrays
Hartmann, C. H., & Klein, C. A. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl740 · Cited by 66 · see citing works
Optofluidic Cell Selection from Complex Microbial Communities for Single-Genome Analysis
Landry, Z., Giovannoni, S. J., Quake, S. R., & Blainey, P. C. (2013) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/b978-0-12-407863-5.00004-6 · Cited by 65 · see citing works
Accurate Identification and Analysis of Human mRNA Isoforms Using Deep Long Read Sequencing
Tilgner, H., Raha, D., Habegger, L., Mohiuddin, M., Gerstein, M., & Snyder, M. P. (2013) · G3 Genes Genomes Genetics · doi:10.1534/g3.112.004812 · Cited by 65 · see citing works
A Stimuli-Responsive Nanopore Based on a Photoresponsive Host-Guest System
Ying, Y., Zhang, J., Meng, F.-N., Cao, C., Yao, X., Willner, I., Tian, H., & Long, Y. (2013) · Scientific Reports · doi:10.1038/srep01662 · Cited by 62 · see citing works
Lazinski, D. W., & Camilli, A. (2013) · BioTechniques · doi:10.2144/000113981 · Cited by 60 · see citing works
Translocating Kilobase RNA through the Staphylococcal α-Hemolysin Nanopore
Cracknell, J. A., Japrung, D., & Bayley, H. (2013) · Nano Letters · doi:10.1021/nl400560r · Cited by 55 · see citing works
Khaladkar, M., Buckley, P. T., Lee, M. T., Francis, C., Eghbal, M. M., Chuong, T., Suresh, S., Kühn, B., Eberwine, J. H., & Kim, J. (2013) · PLoS ONE · doi:10.1371/journal.pone.0076194 · Cited by 41 · see citing works
CD147-Dependent Heterogeneity in Malignant and Chemoresistant Properties of Cancer Cells
Dai, L., Guinea, M., Slomiany, M. G., Bratoeva, M., Grass, G. D., Tolliver, L. B., Maria, B. L., & Toole, B. P. (2012) · American Journal Of Pathology · doi:10.1016/j.ajpath.2012.10.011 · Cited by 41 · see citing works
Transcriptional profiling of cells sorted by RNA abundance
Klemm, S. L., Semrau, S., Wiebrands, K., Mooijman, D., Faddah, D. A., Jaenisch, R., & van Oudenaarden, A. (2014) · Nature Methods · doi:10.1038/nmeth.2910 · Cited by 36 · see citing works
Wang, L., & Janes, K. A. (2013) · Nature Protocols · doi:10.1038/nprot.2012.158 · Cited by 32 · see citing works
Gerard, G. F., D'Alessio, J. M., Kotewicz, M. L., & Noon, M. C. (1986) · DNA · doi:10.1089/dna.1986.5.271 · Cited by 28 · see citing works
Quantitative biology of single neurons
Eberwine, J. H., Lovatt, D., Buckley, P. T., Dueck, H., Francis, C., Kim, T. K., Lee, J., Lee, M. T., Miyashiro, K., Morris, J. F., et al. (2012) · Journal of The Royal Society Interface · doi:10.1098/rsif.2012.0417 · Cited by 18 · see citing works
Microfluidic genome-wide profiling of intrinsic electrical properties in Saccharomyces cerevisiae
Vahey, M. D., Pesudo, L. Q., Svensson, J. P., Samson, L. D., & Joel Voldman, B. (2013) · Lab on a Chip · doi:10.1039/c3lc50162k · Cited by 17 · see citing works
Single cell expression quantitative trait loci and complex traits
Petretto, E. G. (2013) · Genome Medicine · doi:10.1186/gm476 · Cited by 7 · see citing works
Construction of cDNA Libraries Stage 2: Second-strand SynthesisPreprint
Sambrook, J., & Russell, D. W. (2006) · Cold Spring Harbor Protocols · doi:10.1101/pdb.prot3560 · Cited by 2 · see citing works
Flagged first, then by citations
Research works printed but not linked: 4
- [116]Picelli S. Bjorklund A.K. Faridani O.R. Sagasser S. Winberg G. Sandberg R. Smart-seq2 for sensitive full-length transcriptome profiling in single cells Nat. Methods 2013 10 1096 1098 24056875
- [136]Trapnell C. Cacchiarelli D. Grimsby J. Pokharel P. Li S. Morse M. Lennon N.J. Livak K.J. Mikkelsen T.S. Rinn J.L. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells Nat. Biotechnol 2014 32 PMC4122333 24658644
- [142]Tang F. Barbacioru C. Nordman E. Bao S. Lee C. Wang X. Tuch B.B. Heard E. Lao K. Surani M.A. Deterministic and stochastic allele specific gene expression in single mouse blastomeres PLoS One 2011 6 e21208 21731673 PMC3121735
- [159]Rinke C. Schwientek P. Sczyrba A. Ivanova N.N. Anderson I.J. Cheng J.F. Darling A. Malfatti S. Swan B.K. Gies E.A. Insights into the phylogeny and coding potential of microbial dark matter Nature 2013 499 431 437 23851394
Cited by
Sorted by citations
Single-cell RNA sequencing to explore immune cell heterogeneity
Papalexi, E., & Satija, R. (2018) · Nature Reviews Immunology · doi:10.1038/nri.2017.76 · Cited by 1,806 · see citing works
Comparative Analysis of Single-Cell RNA Sequencing Methods
Ziegenhain, C., Vieth, B., Parekh, S., Reinius, B., Guillaumet-Adkins, A., Smets, M., Leonhardt, H., Heyn, H., Hellmann, I., & Enard, W. (2017) · Molecular Cell · doi:10.1016/j.molcel.2017.01.023 · Cited by 1,494 · see citing works
Multiplex single-cell profiling of chromatin accessibility by combinatorial cellular indexing
Cusanovich, D. A., Daza, R., Adey, A., Pliner, H. A., Christiansen, L., Gunderson, K. L., Steemers, F. J., Trapnell, C., & Shendure, J. (2015) · Science · doi:10.1126/science.aab1601 · Cited by 1,248 · see citing works
Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data
Racle, J., de Jonge, K., Baumgaertner, P., Speiser, D. E., & Gfeller, D. (2017) · eLife · doi:10.7554/elife.26476 · Cited by 1,373 · see citing works
Comprehensive functional genomic resource and integrative model for the human brain
Wang, D., Liu, S., Warrell, J., Won, H., Shi, X., Navarro, F. C. P., Clarke, D., Gu, M., Emani, P., Yang, Y. T., et al. (2018) · Science · doi:10.1126/science.aat8464 · Cited by 965 · see citing works
BBKNN: fast batch alignment of single cell transcriptomes
Polański, K., Young, M. D., Miao, Z., Meyer, K. B., Teichmann, S. A., & Park, J.-E. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btz625 · Cited by 932 · see citing works
Cochain, C., Vafadarnejad, E., Arampatzi, P., Pelisek, J., Winkels, H., Ley, K., Wolf, D., Saliba, A.-E., & Zernecke, A. (2018) · Circulation Research · doi:10.1161/circresaha.117.312509 · Cited by 894 · see citing works
Self-citationDefining cell types and states with single-cell genomics
Trapnell, C. (2015) · Genome Research · doi:10.1101/gr.190595.115 · Cited by 813 · see citing works
Revealing 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
An accurate and robust imputation method scImpute for single-cell RNA-seq data
Li, W. V., & Li, J. J. (2018) · Nature Communications · doi:10.1038/s41467-018-03405-7 · Cited by 682 · see citing works
RNA ‐Seq methods for transcriptome analysis
Hrdličková, R., Toloue, M., & Tian, B. (2016) · Wiley Interdisciplinary Reviews - RNA · doi:10.1002/wrna.1364 · Cited by 686 · see citing works
TSCAN: Pseudo-time reconstruction and evaluation in single-cell RNA-seq analysis
Ji, Z., & Ji, H. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw430 · Cited by 624 · see citing works
Statistics or biology: the zero-inflation controversy about scRNA-seq data
Jiang, R., Sun, T., Song, D., & Li, J. J. (2022) · Genome Biology · doi:10.1186/s13059-022-02601-5 · Cited by 614 · see citing works
Identification of cell types from single-cell transcriptomes using a novel clustering method
Xu, C., & Su, Z. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv088 · Cited by 559 · see citing works
Advances and Applications of Single-Cell Sequencing Technologies
Wang, Y., & Navin, N. E. (2015) · Molecular Cell · doi:10.1016/j.molcel.2015.05.005 · Cited by 610 · see citing works
Missing data and technical variability in single-cell RNA-sequencing experiments
Hicks, S. C., Townes, F. W., Teng, M., & Irizarry, R. A. (2018) · Biostatistics · doi:10.1093/biostatistics/kxx053 · Cited by 635 · see citing works
Design 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
Ribosome profiling reveals the what, when, where and how of protein synthesis
Brar, G. A., & Weissman, J. S. (2015) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm4069 · Cited by 535 · see citing works
Deep Sequencing in Microdissected Renal Tubules Identifies Nephron Segment–Specific Transcriptomes
Lee, J. W., Chou, C., & Knepper, M. A. (2015) · Journal of the American Society of Nephrology · doi:10.1681/asn.2014111067 · Cited by 531 · see citing works
Normalizing single-cell RNA sequencing data: challenges and opportunities
Vallejos, C. A., Risso, D., Scialdone, A., Dudoit, S., & Marioni, J. C. (2017) · Nature Methods · doi:10.1038/nmeth.4292 · Cited by 436 · see citing works
Raj, B., & Blencowe, B. J. (2015) · Neuron · doi:10.1016/j.neuron.2015.05.004 · Cited by 475 · see citing works
Design and computational analysis of single-cell RNA-sequencing experiments
Bacher, R. L., & Kendziorski, C. M. (2016) · Genome biology · doi:10.1186/s13059-016-0927-y · Cited by 437 · see citing works
Optochemical Control of Biological Processes in Cells and Animals
Ankenbruck, N., Courtney, T. M., Naro, Y., & Deiters, A. (2017) · Angewandte Chemie International Edition · doi:10.1002/anie.201700171 · Cited by 415 · see citing works
Batch effects and the effective design of single-cell gene expression studies
Tung, P.-Y., Blischak, J. D., Hsiao, C. J., Knowles, D. A., Burnett, J. E., Pritchard, J. K., & Gilad, Y. (2017) · Scientific Reports · doi:10.1038/srep39921 · Cited by 356 · see citing works
A practical solution to pseudoreplication bias in single-cell studies
Zimmerman, K. D., Espeland, M. A., & Langefeld, C. D. (2021) · Nature Communications · doi:10.1038/s41467-021-21038-1 · Cited by 362 · see citing works
Comparative transcriptomics in human and mouse
Breschi, A., Gingeras, T., & Guigó, R. (2017) · Nature Reviews Genetics · doi:10.1038/nrg.2017.19 · Cited by 368 · see citing works
SINCERA: A Pipeline for Single-Cell RNA-Seq Profiling Analysis
Guo, M., Wang, H., Potter, S. S., Whitsett, J. A., & Xu, Y. J. (2015) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004575 · Cited by 347 · see citing works
Beyond bulk: a review of single cell transcriptomics methodologies and applications
Kulkarni, A., Anderson, A. G., Merullo, D. P., & Konopka, G. (2019) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2019.03.001 · Cited by 344 · see citing works
Technological Developments in lncRNA Biology
Jathar, S., Kumar, V., Srivastava, J. P., & Tripathi, V. (2017) · Advances in experimental medicine and biology · doi:10.1007/978-981-10-5203-3_10 · Cited by 348 · see citing works
Wang, T., Li, B., Nelson, C. E., & Nabavi, S. (2019) · BMC Bioinformatics · doi:10.1186/s12859-019-2599-6 · Cited by 286 · see citing works
“Consequently, analyzing gene expression values on the single-cell scale provides deep insight into the interplay between intrinsic cellular processes and stochastic gene expression in biological and biomedical research [6 – 9].”
BackgroundGenetic mapping of cell type specificity for complex traits
Watanabe, K., Mirkov, M. U., de Leeuw, C., van den Heuvel, M. P., & Posthuma, D. (2019) · Nature Communications · doi:10.1038/s41467-019-11181-1 · Cited by 323 · see citing works
Barcoded nanoparticles for high throughput in vivo discovery of targeted therapeutics
Dahlman, J. E., Kauffman, K. J., Xing, Y., Shaw, T. E., Mir, F. F., Dlott, C. C., Langer, R., Anderson, D. G., & Wang, E. T. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1620874114 · Cited by 335 · see citing works
BASiCS: Bayesian Analysis of Single-Cell Sequencing Data
Vallejos, C. A., Marioni, J. C., & Richardson, S. (2015) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1004333 · Cited by 302 · see citing works
3D steerable, acoustically powered microswimmers for single-particle manipulation
Ren, L., Nama, N., McNeill, J. M., Soto, F., Yan, Z. W., Liu, W., Wang, W., Wang, J., & Mallouk, T. E. (2019) · Science Advances · doi:10.1126/sciadv.aax3084 · Cited by 304 · see citing works
pcaReduce: hierarchical clustering of single cell transcriptional profiles
Žurauskienė, J., & Yau, C. (2016) · BMC Bioinformatics · doi:10.1186/s12859-016-0984-y · Cited by 298 · see citing works
Advanced Applications of RNA Sequencing and Challenges
Han, Y., Gao, S., Muegge, K., Zhang, W., & Zhou, B. (2015) · Bioinformatics and Biology Insights · doi:10.4137/bbi.s28991 · Cited by 277 · see citing works
Classifying Drosophila Olfactory Projection Neuron Subtypes by Single-Cell RNA Sequencing
Li, H., Horns, F., Wu, B., Xie, Q., Li, J., Li, T., Luginbuhl, D. J., Quake, S. R., & Luo, L. (2017) · Cell · doi:10.1016/j.cell.2017.10.019 · Cited by 256 · see citing works
Protein-Based Biological Materials: Molecular Design and Artificial Production
Miserez, A., Yu, J., & Mohammadi, P. (2023) · Chemical Reviews · doi:10.1021/acs.chemrev.2c00621 · Cited by 284 · see citing works
The impact of amplification on differential expression analyses by RNA-seq
Parekh, S., Ziegenhain, C., Vieth, B., Enard, W., & Hellmann, I. (2016) · Scientific Reports · doi:10.1038/srep25533 · Cited by 252 · see citing works
SCDC: bulk gene expression deconvolution by multiple single-cell RNA sequencing references
Dong, M., Thennavan, A., Urrutia, E., Li, Y., Perou, C. M., Zou, F., & Jiang, Y. (2019) · Briefings in Bioinformatics · doi:10.1093/bib/bbz166 · Cited by 250 · see citing works
Single-cell RNA-sequencing: The future of genome biology is now
Picelli, S. (2016) · RNA Biology · doi:10.1080/15476286.2016.1201618 · Cited by 237 · see citing works
Benchmarking Computational Doublet-Detection Methods for Single-Cell RNA Sequencing Data
Xi, N. M., & Li, J. J. (2021) · Cell Systems · doi:10.1016/j.cels.2020.11.008 · Cited by 208 · see citing works
Single-cell transcriptome sequencing: recent advances and remaining challenges
Liu, S., & Trapnell, C. (2016) · F1000Research · doi:10.12688/f1000research.7223.1 · Cited by 230 · see citing works
Single cells make big data: New challenges and opportunities in transcriptomics
Angerer, P., Simon, L. M., Tritschler, S., Wolf, F., Fischer, D. S., & Theis, F. J. (2017) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2017.07.004 · Cited by 213 · see citing works
Systems biology primer: the basic methods and approaches
Tavassoly, I., Goldfarb, J., & Iyengar, R. (2018) · Essays in Biochemistry · doi:10.1042/ebc20180003 · Cited by 221 · see citing works
Cell fixation and preservation for droplet-based single-cell transcriptomics
Alles, J., Karaiskos, N., Praktiknjo, S. D., Grosswendt, S., Wahle, P., Ruffault, P.-L., Ayoub, S., Schreyer, L., Boltengagen, A., Birchmeier, C., et al. (2017) · BMC Biology · doi:10.1186/s12915-017-0383-5 · Cited by 218 · see citing works
“handling of cellular input material [9].”
Single-cell RNA-seq reveals hidden transcriptional variation in malaria parasites
Reid, A. J., Talman, A. M., Bennett, H. M., Gomes, A. R., Sanders, M. J., Illingworth, C. J. R., Billker, O., Berriman, M., & Lawniczak, M. (2018) · eLife · doi:10.7554/elife.33105 · Cited by 209 · see citing works
Single-cell RNA-seq ties macrophage polarization to growth rate of intracellular Salmonella
Saliba, A., Li, L., Westermann, A. J., Appenzeller, S., Stapels, D. A. C., Schulte, L. N., Hélaine, S., & Vogel, J. (2016) · Nature Microbiology · doi:10.1038/nmicrobiol.2016.206 · Cited by 203 · see citing works
Self-citationTanaka, N., Kanatani, S., Tomer, R., Sahlgren, C., Kronqvist, P., Kaczyńska, D., Louhivuori, L. M., Kis, L. L., Lindh, C., Mitura, P., et al. (2017) · Nature Biomedical Engineering · doi:10.1038/s41551-017-0139-0 · Cited by 200 · see citing works
McLeod, C., & Mauck, R. L. (2017) · European Cells and Materials · doi:10.22203/ecm.v034a14 · Cited by 199 · see citing works
Tumour Heterogeneity: The Key Advantages of Single-Cell Analysis
Tellez-Gabriel, M., Ory, B., Lamoureux, F., Heymann, M., & Heymann, D. (2016) · International Journal of Molecular Sciences · doi:10.3390/ijms17122142 · Cited by 193 · see citing works
Introduction to Single‐Cell RNA Sequencing
Olsen, T. K., & Baryawno, N. (2018) · Current Protocols in Molecular Biology · doi:10.1002/cpmb.57 · Cited by 192 · see citing works
Bacterial RNA Biology on a Genome Scale
Hör, J., Gorski, S. A., & Vogel, J. (2018) · Molecular Cell · doi:10.1016/j.molcel.2017.12.023 · Cited by 186 · see citing works
Self-citationYao, W., Chen, Y., Li, Z., Ji, J., You, A., Jin, S., Ma, Y., Zhao, Y., Wang, J., Qu, L., et al. (2022) · Advanced Science · doi:10.1002/advs.202103675 · Cited by 192 · see citing works
Smad3 Promotes Cancer‐Associated Fibroblasts Generation via Macrophage–Myofibroblast Transition
Tang, P. C., Chung, J. Y., Xue, V. W., Xiao, J., Meng, X., Huang, X., Zhou, S., Chan, A. S. W., Tsang, C. M., Cheng, A. S., et al. (2021) · Advanced Science · doi:10.1002/advs.202101235 · Cited by 190 · see citing works
Machine learning meets omics: applications and perspectives
Li, R., Li, L., Xu, Y., & Yang, J. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab460 · Cited by 180 · see citing works
A comprehensive survey of regulatory network inference methods using single cell RNA sequencing data
Nguyen, H., Tran, D., Tran, B., Pehlivan, B. A., & Nguyen, T. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbaa190 · Cited by 181 · see citing works
Lee, M.-C. W., López-Díaz, F. J., Khan, S. Y., Tariq, M., Dayn, Y., Vaske, C. J., Radenbaugh, A., Kim, H. J., Emerson, B. M., & Pourmand, N. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1404656111 · Cited by 172 · 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
Comi, T. J., Do, T. D., Rubakhin, S. S., & Sweedler, J. V. (2017) · Journal of the American Chemical Society · doi:10.1021/jacs.6b12822 · Cited by 174 · see citing works
Yang, L. C., Wang, W., Qiu, W., Guo, Z., Bi, E., & Xu, C. (2017) · Hepatology · doi:10.1002/hep.29353 · Cited by 162 · see citing works
Zhang, F. S., Guo, X. Q., Xia, Y., & Mao, L. (2021) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-021-04079-z · Cited by 170 · see citing works
Qiu, W., Zhang, Y.-W., Ye, F., Li, L., Yang, L., & Xu, C. (2017) · Cell Metabolism · doi:10.1016/j.cmet.2017.04.003 · Cited by 160 · see citing works
The barcode, UMI, set format and BUStools
Melsted, P., Ntranos, V., & Pachter, L. S. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz279 · Cited by 151 · see citing works
Platforms for Single-Cell Collection and Analysis
Valihrach, L., Androvic, P., & Kubista, M. (2018) · International Journal of Molecular Sciences · doi:10.3390/ijms19030807 · Cited by 165 · see citing works
Single Cell T Cell Receptor Sequencing: Techniques and Future Challenges
Simone, M. C. D., Rossetti, G., & Pagani, M. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.01638 · Cited by 161 · see citing works
Bardy, C., van den Hurk, M., Kakaradov, B., Erwin, J. A., Jaeger, B. N., Hernandez, R. V., Eames, T., Paucar, A. A., Gorris, M. A. J., Marchand, C., et al. (2016) · Molecular Psychiatry · doi:10.1038/mp.2016.158 · Cited by 160 · see citing works
Deng, Y. C., Bao, F., Dai, Q., Wu, L. F., & Altschuler, S. J. (2019) · Nature Methods · doi:10.1038/s41592-019-0353-7 · Cited by 173 · see citing works
Arlehamn, C. S. L., McKinney, D. M., Carpenter, C., Paul, S., Rozot, V., Makgotlho, E., Gregg, Y., van Rooyen, M., Ernst, J., Hatherill, M., et al. (2016) · PLoS Pathogens · doi:10.1371/journal.ppat.1005760 · Cited by 158 · see citing works
Marine Protists Are Not Just Big Bacteria
Keeling, P. J., & del Campo, J. (2017) · Current Biology · doi:10.1016/j.cub.2017.03.075 · Cited by 158 · see citing works
A microfluidic platform enabling single-cell RNA-seq of multigenerational lineages
Kimmerling, R. J., Szeto, G. L., Li, J. W., Genshaft, A. S., Kazer, S. W., Payer, K. R., Borrajo, J. D. R., Blainey, P. C., Irvine, D. J., Shalek, A. K., et al. (2016) · Nature Communications · doi:10.1038/ncomms10220 · Cited by 155 · see citing works
Circulating RNAs as new biomarkers for detecting pancreatic cancer
Kishikawa, T. (2015) · World Journal of Gastroenterology · doi:10.3748/wjg.v21.i28.8527 · Cited by 152 · see citing works
Schaefer, M., Kapoor, U., & Jantsch, M. F. (2017) · Open Biology · doi:10.1098/rsob.170077 · Cited by 152 · see citing works
Fast and precise single-cell data analysis using a hierarchical autoencoder
Tran, D., Nguyen, H., Tran, B., La Vecchia, C., Luu, H. N., & Nguyen, T. (2021) · Nature Communications · doi:10.1038/s41467-021-21312-2 · Cited by 145 · see citing works
Inferring relevant cell types for complex traits by using single-cell gene expression
Calderon, D., Bhaskar, A., Knowles, D. A., Golan, D., Raj, T., Fu, A. Q., & Pritchard, J. K. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.09.009 · Cited by 127 · see citing works
Velez, D. O., Tsui, B., Goshia, T., Chute, C. L., Han, A. M., Carter, H. K., & Fraley, S. I. (2017) · Nature Communications · doi:10.1038/s41467-017-01556-7 · Cited by 144 · see citing works
Carmona, S. J., Teichmann, S. A., Ferreira, L., Macaulay, I. C., Stubbington, M. J. T., Cvejic, A., & Gfeller, D. (2017) · Genome Research · doi:10.1101/gr.207704.116 · Cited by 136 · see citing works
Applications of Immunomodulatory Immune Synergies to Adjuvant Discovery and Vaccine Development
Tom, J. K., Albin, T. J., Manna, S., Moser, B., Steinhardt, R. C., & Esser-Kahn, A. P. (2018) · Trends in biotechnology · doi:10.1016/j.tibtech.2018.10.004 · Cited by 138 · see citing works
Cross-species RNA-seq for deciphering host–microbe interactions
Westermann, A. J., & Vogel, J. (2021) · Nature Reviews Genetics · doi:10.1038/s41576-021-00326-y · Cited by 136 · see citing works
Self-citationSingle-Cell Transcriptomics: Current Methods and Challenges in Data Acquisition and Analysis
Adil, A., Kumar, V., Jan, A. T., & Asger, M. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.591122 · Cited by 133 · see citing works
Tang, P. M., Zhou, S., Li, C., Liao, J., Xiao, J., Wang, Q., Lian, G., Li, J., Huang, X., To, K., et al. (2017) · Kidney International · doi:10.1016/j.kint.2017.07.026 · Cited by 130 · see citing works
Single-nuclei RNA-seq on human retinal tissue provides improved transcriptome profiling
Liang, Q., Dharmat, R., Owen, L. A., Shakoor, A., Li, Y., Kim, S., Vitale, A. T., Kim, I. K., Morgan, D. J., Liang, S., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-12917-9 · Cited by 120 · see citing works
Single-Cell Sequencing for Precise Cancer Research: Progress and Prospects
Zhang, X., Marjani, S. L., Hu, Z., Weissman, S. M., Pan, X., & Wu, S. (2016) · Cancer Research · doi:10.1158/0008-5472.can-15-1907 · Cited by 122 · see citing works
SC3-seq: a method for highly parallel and quantitative measurement of single-cell gene expression
Nakamura, T., Yabuta, Y., Okamoto, I., Aramaki, S., Yokobayashi, S., Kurimoto, K., Sekiguchi, K., Nakagawa, M., Yamamoto, T., & Saitou, M. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv134 · Cited by 120 · see citing works
He, B., Bai, X., Tan, Y., Xie, W., Feng, Y. F., & Yang, G. (2022) · Synthetic and Systems Biotechnology · doi:10.1016/j.synbio.2022.01.001 · Cited by 118 · see citing works
Desta, G. M., & Birhanu, A. G. (2025) · Acta Biochimica Polonica · doi:10.3389/abp.2025.13922 · Cited by 121 · see citing works
Nanogrid single-nucleus RNA sequencing reveals phenotypic diversity in breast cancer
Gao, R., Kim, C. R., Sei, E., Foukakis, T., Crosetto, N., Chan, L., Srinivasan, M., Zhang, H., Meric‐Bernstam, F., & Navin, N. E. (2017) · Nature Communications · doi:10.1038/s41467-017-00244-w · Cited by 116 · see citing works
Avital, G., Avraham, R., Fan, A. C., Hashimshony, T., Hung, D. T., & Yanai, I. (2017) · Genome biology · doi:10.1186/s13059-017-1340-x · Cited by 115 · see citing works
Whole transcriptome profiling reveals the RNA content of motor axons
Briese, M., Saal-Bauernschubert, L., Appenzeller, S., Moradi, M., Baluapuri, A., & Sendtner, M. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1027 · Cited by 113 · see citing works
New RNA-seq approaches for the study of bacterial pathogens
Saliba, A., Santos, S. C., & Vogel, J. (2017) · Current Opinion in Microbiology · doi:10.1016/j.mib.2017.01.001 · Cited by 113 · see citing works
Self-citationAccelerating Discovery and Functional Analysis of Small RNAs with New Technologies
Barquist, L., & Vogel, J. (2015) · Annual Review of Genetics · doi:10.1146/annurev-genet-112414-054804 · Cited by 108 · see citing works
Self-citationFast and accurate single-cell RNA-seq analysis by clustering of transcript-compatibility counts
Ntranos, V., Kamath, G. M., Zhang, J. M., Pachter, L. S., & Tse, D. N. C. (2016) · Genome biology · doi:10.1186/s13059-016-0970-8 · Cited by 107 · see citing works
Tsang, J. C. H., Yu, Y., Burke, S., Buettner, F., Wang, C., Kolodziejczyk, A., Teichmann, S., Lu, L.-M., & Liu, P. (2015) · Genome Biology · doi:10.1186/s13059-015-0739-5 · Cited by 98 · see citing works
Crocker, A., Guan, X.-J., Murphy, C. T., & Murthy, M. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.04.046 · Cited by 108 · see citing works
Imputing single-cell RNA-seq data by combining graph convolution and autoencoder neural networks
Rao, J., Zhou, X., Lu, Y., Zhao, H., & Yang, Y. (2021) · iScience · doi:10.1016/j.isci.2021.102393 · Cited by 105 · see citing works
Homogenizing bacterial cell factories: Analysis and engineering of phenotypic heterogeneity
Binder, D., Drepper, T., Jaeger, K., Delvigne, F., Wiechert, W., Kohlheyer, D., & Grünberger, A. (2017) · Metabolic Engineering · doi:10.1016/j.ymben.2017.06.009 · Cited by 105 · see citing works
HLA and proteasome expression body map
Boegel, S., Löwer, M., Bukur, T., Sorn, P., Castle, J. C., & Şahin, U. (2018) · BMC Medical Genomics · doi:10.1186/s12920-018-0354-x · Cited by 106 · see citing works
Analytics for Metabolic Engineering
Petzold, C. J., Chan, L. J. G., Nhan, M., & Adams, P. D. (2015) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2015.00135 · Cited by 106 · see citing works
Optochemische Steuerung biologischer Vorgänge in Zellen und Tieren
Ankenbruck, N., Courtney, T. M., Naro, Y., & Deiters, A. (2017) · Angewandte Chemie · doi:10.1002/ange.201700171 · Cited by 105 · see citing works
ST Pipeline: an automated pipeline for spatial mapping of unique transcripts
Navarro, J. F., Sjöstrand, J., Salmén, F., Lundeberg, J., & Ståhl, P. L. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx211 · Cited by 103 · see citing works
- Authors
- Saliba, A.-E., Westermann, A. J., Gorski, S. A., & Vogel, J.
- Affiliations
- University of Würzburg (DE)
- Corresponding author
- Vogel, Jörg
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-07-22
- Volume
- 42
- Issue
- 14
- Pages
- 8845-8860
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC4132710
- OpenAlex
- W2069295116
- Cited by
- 847
- References
- 167
- Citations by year
- 2026: 38 · 2025: 81 · 2024: 92 · 2023: 78 · 2022: 74 · 2021: 69 · 2020: 58 · 2019: 63 · 2018: 67 · 2017: 91 · 2016: 84 · 2015: 46 · 2014: 6
- FWCI
- 7.00
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nucleic Acids Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- MDC Repository (Max-Delbrueck-Center for Molecular Medicine) (acceptedVersion)
- Online Publication Service of Würzburg University (Würzburg University) (submittedVersion, cc-by)
- Funders
- Deutsche Forschungsgemeinschaft
- Bundesministerium für Bildung und Forschung
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Keywords
- single-cell RNA sequencing, single-cell transcriptomics, cell-to-cell variability, transcriptional landscape
- MeSH terms
- Cell Separation, Sequence Analysis, RNA, Gene Expression Profiling, Single-Cell Analysis, 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
