Single-cell epigenomics: powerful new methods for understanding gene regulation and cell identity
Open accessAbstract
Emerging single-cell epigenomic methods are being developed with the exciting potential to transform our knowledge of gene regulation. Here we review available techniques and future possibilities, arguing that the full potential of single-cell epigenetic studies will be realized through parallel profiling of genomic, transcriptional, and epigenetic information.
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?
Recent developments in single-cell technologies are circumventing the issue of cell-type specificity and allowing epigenetic modifications to be assessed at a single-cell level.
“Recent developments in single-cell technologies are circumventing this issue and allowing epigenetic modifications to be assessed on a single-cell level.”
From Epigenetics and depression (2019) · cites this paper as [34]
Fluorescence-activated cell sorting techniques and single-cell epigenomics can facilitate the examination of DNA methylation in various cell types.
“Fluorescence-activated cell sorting techniques and single-cell epigenomics can facilitate the examination of DNA methylation various cell types.106,411”
From Epigenetic regulation in major depression and other stress-related disorders: molecular mechanisms, clinical relevance and therapeutic potential (2023) · cites this paper as [106]
Data at this scale present difficulties in basic processing (e.g., calculating a covariation matrix; clustering) and in assessing the statistical significance and robustness of results.
“Data at this scale present difficulties in basic processing192 (e.g., calculating a covariation matrix; clustering) and in assessing the statistical significance and robustness of results.”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [192]
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
Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets.
Macosko, E. Z., Basu, A., Satija, R., Nemesh, J., Shekhar, K., Goldman, M., Tirosh, I., Bialas, A. R., Kamitaki, N., Martersteck, E. M., et al. (2015) · Cell · doi:10.1016/j.cell.2015.05.002 · Cited by 7,110 · see citing works
Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y., & Greenleaf, W. J. (2013) · Nature Methods · doi:10.1038/nmeth.2688 · Cited by 6,422 · see citing works
Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma
Patel, A. P., Tirosh, I., Trombetta, J. J., Shalek, A. K., Gillespie, S. M., Wakimoto, H., Cahill, D. P., Nahed, B. V., Curry, W. T., Martuza, R. L., et al. (2014) · Science · doi:10.1126/science.1254257 · Cited by 5,063 · see citing works
Real-Time DNA Sequencing from Single Polymerase Molecules
Eid, J., Fehr, A., Gray, J., Luong, K., Lyle, J., Otto, G., Peluso, P., Rank, D., Baybayan, P., Bettman, B., et al. (2009) · Science · doi:10.1126/science.1162986 · Cited by 3,732 · see citing works
Self-citationDroplet barcoding for single-cell transcriptomics applied to embryonic stem cells
Klein, A. M., Mazutis, L., Akartuna, I., Tallapragada, N., Veres, A., Li, V., Peshkin, L., Weitz, D. A., & Kirschner, M. W. (2015) · Cell · doi:10.1016/j.cell.2015.04.044 · Cited by 3,356 · see citing works
Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq
Zeisel, A., Muñoz-Manchado, A. B., Codeluppi, S., Lönnerberg, P., La Manno, G., Juréus, A., Marques, S., Munguba, H., He, L., Betsholtz, C., et al. (2015) · Science · doi:10.1126/science.aaa1934 · Cited by 3,124 · see citing works
DNA methylation: roles in mammalian development
Smith, Z. D., & Meissner, A. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3354 · Cited by 3,045 · see citing works
A decade of exploring the cancer epigenome—biological and translational implications
Baylin, S. B., & Jones, P. A. (2011) · Nature Reviews Cancer · doi:10.1038/nrc3130 · Cited by 2,871 · see citing works
Single-cell chromatin accessibility reveals principles of regulatory variation
Buenrostro, J. D., Wu, B., Litzenburger, U. M., Ruff, D., Gonzales, M. L., Snyder, M. P., Chang, H. Y., & Greenleaf, W. J. (2015) · Nature · doi:10.1038/nature14590 · Cited by 2,308 · see citing works
Shotgun bisulphite sequencing of the Arabidopsis genome reveals DNA methylation patterning
Cokus, S. J., Feng, S.-H., Zhang, X.-Y., Chen, Z., Merriman, B., Haudenschild, C., Pradhan, S., Nelson, S., Pellegrini, M., & Jacobsen, S. (2008) · Nature · doi:10.1038/nature06745 · Cited by 2,278 · see citing works
Bernstein, B. E., Meissner, A., & Lander, E. S. (2007) · Cell · doi:10.1016/j.cell.2007.01.033 · Cited by 2,086 · see citing works
Function and information content of DNA methylation
Schübeler, D. (2015) · Nature · doi:10.1038/nature14192 · Cited by 2,060 · 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 Hi-C reveals cell-to-cell variability in chromosome structure
Nagano, T., Lubling, Y., Stevens, T. J., Schoenfelder, S., Yaffe, E., Dean, W., Laue, E. D., Tanay, A., & Fraser, P. (2013) · Nature · doi:10.1038/nature12593 · Cited by 1,589 · see citing works
The Technology and Biology of Single-Cell RNA Sequencing
Kolodziejczyk, A. A., Kim, J. K., Svensson, V., Marioni, J. C., & Teichmann, S. A. (2015) · Molecular Cell · doi:10.1016/j.molcel.2015.04.005 · Cited by 1,487 · see citing works
Direct detection of DNA methylation during single-molecule, real-time sequencing
Flusberg, B. A., Webster, D. R., Lee, J. H., Travers, K. J., Olivares, E. C., Clark, T. A., Korlach, J., & Turner, S. W. (2010) · Nature Methods · doi:10.1038/nmeth.1459 · Cited by 1,460 · see citing works
Dynamic Regulation of Nucleosome Positioning in the Human Genome
Schones, D. E., Cui, K., Cuddapah, S., Roh, T., Barski, A., Wang, Z., Wei, G., & Zhao, K. (2008) · Cell · doi:10.1016/j.cell.2008.02.022 · Cited by 1,396 · 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
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
Computational and analytical challenges in single-cell transcriptomics
Stegle, O., Teichmann, S. A., & Marioni, J. C. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3833 · Cited by 1,170 · see citing works
Charting histone modifications and the functional organization of mammalian genomes
Zhou, V. W., Goren, A., & Bernstein, B. E. (2011) · Nature Reviews Genetics · doi:10.1038/nrg2905 · Cited by 1,147 · see citing works
Single-cell genome-wide bisulfite sequencing for assessing epigenetic heterogeneity
Smallwood, S. A., Lee, H. J., Angermueller, C., Krueger, F., Saadeh, H., Peat, J., Andrews, S. R., Stegle, O., Reik, W., & Kelsey, G. (2014) · Nature Methods · doi:10.1038/nmeth.3035 · Cited by 1,125 · see citing works
Self-citationDynamic regulation of 5-hydroxymethylcytosine in mouse ES cells and during differentiation
Ficz, G., Branco, M. R., Seisenberger, S., Santos, F., Krueger, F., Hore, T. A., Marques, C. J., Andrews, S., & Reik, W. (2011) · Nature · doi:10.1038/nature10008 · Cited by 1,123 · see citing works
Self-citationBase-Resolution Analysis of 5-Hydroxymethylcytosine in the Mammalian Genome
Yu, M., Hon, G. C., Szulwach, K. E., Song, C., Zhang, L., Kim, A., Li, X., Dai, Q., Shen, Y., Park, B., et al. (2012) · Cell · doi:10.1016/j.cell.2012.04.027 · Cited by 1,022 · 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
Quantitative Sequencing of 5-Methylcytosine and 5-Hydroxymethylcytosine at Single-Base Resolution
Booth, M. J., Branco, M. R., Ficz, G., Oxley, D., Krueger, F., Reik, W., & Balasubramanian, S. (2012) · Science · doi:10.1126/science.1220671 · Cited by 923 · see citing works
Self-citationUnravelling cancer stem cell potential
Beck, B., & Blanpain, C. (2013) · Nature reviews. Cancer · doi:10.1038/nrc3597 · Cited by 895 · see citing works
Single-cell analysis reveals a stem-cell program in human metastatic breast cancer cells
Lawson, D. A., Bhakta, N. R., Kessenbrock, K., Prummel, K. D., Yu, Y., Takai, K., Zhou, A. Y., Eyob, H., Balakrishnan, S., Wang, C., et al. (2015) · Nature · doi:10.1038/nature15260 · Cited by 894 · see citing works
Single-cell ChIP-seq reveals cell subpopulations defined by chromatin state
Rotem, A., Ram, O., Shoresh, N., Sperling, R. A., Goren, A., Weitz, D. A., & Bernstein, B. E. (2015) · Nature Biotechnology · doi:10.1038/nbt.3383 · Cited by 854 · 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
Single-Cell RNA-Seq with Waterfall Reveals Molecular Cascades underlying Adult Neurogenesis
Shin, J., Berg, D. A., Zhu, Y., Shin, J. Y., Song, J., Bonaguidi, M. A., Enikolopov, G., Nauen, D. W., Christian, K. M., Ming, G.-L., et al. (2015) · Cell Stem Cell · doi:10.1016/j.stem.2015.07.013 · Cited by 784 · see citing works
Uncovering the role of 5-hydroxymethylcytosine in the epigenome
Branco, M. R., Ficz, G., & Reik, W. (2012) · Nature Reviews Genetics · doi:10.1038/nrg3080 · Cited by 766 · cited 1× · see citing works
“logical functions of these modifications [43–46].”
Self-citationG&T-seq: parallel sequencing of single-cell genomes and transcriptomes
Macaulay, I. C., Haerty, W., Kumar, P., Li, Y. I., Hu, T. X., Teng, M. J., Goolam, M., Saurat, N., Coupland, P., Shirley, L. M., et al. (2015) · Nature Methods · doi:10.1038/nmeth.3370 · Cited by 750 · see citing works
Toward understanding and exploiting tumor heterogeneity
Alizadeh, A. A., Aranda, V., Bardelli, A., Blanpain, C., Bock, C., Borowski, C., Caldas, C., Califano, A., Doherty, M., Elsner, M., et al. (2015) · Nature Medicine · doi:10.1038/nm.3915 · Cited by 742 · see citing works
Chromatin structure and the inheritance of epigenetic information
Margueron, R., & Reinberg, D. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2752 · Cited by 733 · see citing works
Parallel single-cell sequencing links transcriptional and epigenetic heterogeneity
Angermueller, C., Clark, S. J., Lee, H. J., Macaulay, I. C., Teng, M. J., Hu, T. X., Krueger, F., Smallwood, S. A., Ponting, C. P., Voet, T., et al. (2016) · Nature Methods · doi:10.1038/nmeth.3728 · Cited by 717 · see citing works
Self-citationSingle-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
A Bayesian deconvolution strategy for immunoprecipitation-based DNA methylome analysis
Down, T. A., Rakyan, V. K., Turner, D., Flicek, P., Li, H., Kulesha, E., Gräf, S., Johnson, N., Herrero, J., Tomazou, E. M., et al. (2008) · Nature Biotechnology · doi:10.1038/nbt1414 · Cited by 651 · 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
Genome-wide Profiling of 5-Formylcytosine Reveals Its Roles in Epigenetic Priming
Song, C., Szulwach, K. E., Dai, Q., Fu, Y., Mao, S.-Q., Lin, L., Street, C., Li, Y., Poidevin, M., Wu, H., et al. (2013) · Cell · doi:10.1016/j.cell.2013.04.001 · Cited by 545 · see citing works
Guo, H., Zhu, P., Wu, X., Li, X., Wen, L., & Tang, F. (2013) · Genome Research · doi:10.1101/gr.161679.113 · Cited by 518 · see citing works
Integrated genome and transcriptome sequencing of the same cell
Dey, S. S., Kester, L., Spanjaard, B., Bienko, M., & van Oudenaarden, A. (2015) · Nature Biotechnology · doi:10.1038/nbt.3129 · Cited by 502 · see citing works
Genome-wide Analysis Reveals TET- and TDG-Dependent 5-Methylcytosine Oxidation Dynamics
Shen, L., Wu, H., Diep, D., Yamaguchi, S., D’Alessio, A. C., Fung, H.-L., Zhang, K., & Zhang, Y. (2013) · Cell · doi:10.1016/j.cell.2013.04.002 · Cited by 497 · see citing works
Epigenetic dynamics of stem cells and cell lineage commitment: digging Waddington's canal
Hemberger, M., Dean, W., & Reik, W. (2009) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2727 · Cited by 474 · see citing works
Self-citationHabibi, E., Brinkman, A. B., Arand, J., Kroeze, L. I., Kerstens, H. H. D., Matarese, F., Lepikhov, K., Gut, M., Heath, I. B., Hubner, N. C., et al. (2013) · Cell stem cell · doi:10.1016/j.stem.2013.06.002 · Cited by 470 · see citing works
Genome-wide Maps of Nuclear Lamina Interactions in Single Human Cells
Kind, J., Pagie, L., de Vries, S., Nahidiazar, L., Dey, S. S., Bienko, M., Zhan, Y., Lajoie, B. R., de Graaf, C. A., Amendola, M., et al. (2015) · Cell · doi:10.1016/j.cell.2015.08.040 · Cited by 467 · see citing works
Genome-wide mapping of nucleosome positioning and DNA methylation within individual DNA molecules
Kelly, T. K., Liu, Y., Lay, F. D., Liang, G., Berman, B. P., & Jones, P. A. (2012) · Genome Research · doi:10.1101/gr.143008.112 · Cited by 455 · see citing works
Single-cell DNA methylome sequencing and bioinformatic inference of epigenomic cell-state dynamics
Farlik, M., Sheffield, N. C., Nuzzo, A., Datlinger, P., Schönegger, A., Klughammer, J., & Bock, C. (2015) · Cell Reports · doi:10.1016/j.celrep.2015.02.001 · Cited by 422 · see citing works
Amplification-free whole-genome bisulfite sequencing by post-bisulfite adaptor tagging
Miura, F., Enomoto, Y., Dairiki, R., & Ito, T. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks454 · Cited by 419 · see citing works
High-throughput spatial mapping of single-cell RNA-seq data to tissue of origin
Achim, K., Pettit, J.-B., Saraiva, L. R., Gavriouchkina, D., Larsson, T., Arendt, D., & Marioni, J. C. (2015) · Nature Biotechnology · doi:10.1038/nbt.3209 · Cited by 395 · see citing works
Chromatin dynamics during cellular reprogramming
Apostolou, E., & Hochedlinger, K. (2013) · Nature · doi:10.1038/nature12749 · Cited by 394 · see citing works
Ficz, G., Hore, T. A., Santos, F., Lee, H. J., Dean, W., Arand, J., Krueger, F., Oxley, D., Paul, Y., Walter, J., et al. (2013) · Cell stem cell · doi:10.1016/j.stem.2013.06.004 · Cited by 387 · see citing works
Self-citationSingle Cell Genomics: Advances and Future Perspectives
Macaulay, I. C., & Voet, T. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004126 · Cited by 384 · see citing works
Reprogramming the Methylome: Erasing Memory and Creating Diversity
Lee, H. J., Hore, T. A., & Reik, W. (2014) · Cell stem cell · doi:10.1016/j.stem.2014.05.008 · Cited by 382 · see citing works
Self-citationThe first five years of single-cell cancer genomics and beyondPreprint
Navin, N. E. (2015) · Genome Research · doi:10.1101/gr.191098.115 · Cited by 368 · see citing works
Genome-wide detection of DNase I hypersensitive sites in single cells and FFPE tissue samples
Jin, W., Tang, Q., Wan, M., Cui, K., Zhang, Y., Ren, G., Ni, B., Sklar, J., Przytycka, T. M., Childs, R., et al. (2015) · Nature · doi:10.1038/nature15740 · Cited by 332 · see citing works
<i>EGFR</i> Variant Heterogeneity in Glioblastoma Resolved through Single-Nucleus Sequencing
Francis, J. M., Zhang, C.-Z., Maire, C. L., Jung, J., Manzo, V. E., Adalsteinsson, V. A., Homer, H., Haidar, S., Blumenstiel, B., Pedamallu, C. S., et al. (2014) · Cancer Discovery · doi:10.1158/2159-8290.cd-13-0879 · Cited by 287 · see citing works
Brunner, A. L., Johnson, D. S., Kim, S. W., Valouev, A., Reddy, T. E., Neff, N. F., Anton, E., Medina, C., Nguyen, L., Chiao, E. T., et al. (2009) · Genome Research · doi:10.1101/gr.088773.108 · Cited by 283 · see citing works
Tomer Kalisky, C., & Quake, S. R. (2011) · Nature Methods · doi:10.1038/nmeth0411-311 · Cited by 270 · see citing works
Raiber, E., Beraldi, D., Ficz, G., Burgess, H. E., Branco, M. R., Murat, P., Oxley, D., Booth, M. J., Reik, W., & Balasubramanian, S. (2012) · Genome biology · doi:10.1186/gb-2012-13-8-r69 · Cited by 230 · see citing works
Self-citationStirzaker, C., Zotenko, E., Song, J. Z., Qu, W., Nair, S. S., Locke, W. J., Stone, A. M., Armstong, N. J., Robinson, M. D., Dobrovic, A., et al. (2015) · Nature Communications · doi:10.1038/ncomms6899 · Cited by 188 · see citing works
Self-citationZunder, E. R., Lujan, E., Goltsev, Y., Wernig, M., & Nolan, G. P. (2015) · Cell stem cell · doi:10.1016/j.stem.2015.01.015 · Cited by 177 · see citing works
Reprogramming of cell fate: epigenetic memory and the erasure of memories past
Nashun, B., Hill, P. W. S., & Hájková, P. (2015) · The EMBO Journal · doi:10.15252/embj.201490649 · Cited by 176 · see citing works
Discrimination of Methylcytosine from Hydroxymethylcytosine in DNA Molecules
Wanunu, M., Cohen-Karni, D., Johnson, R. R., Fields, L. G., Benner, J. S., Peterman, N., Zheng, Y., Klein, M. L., & Drndić, M. (2010) · Journal of the American Chemical Society · doi:10.1021/ja107836t · Cited by 173 · see citing works
High-Resolution Enzymatic Mapping of Genomic 5-Hydroxymethylcytosine in Mouse Embryonic Stem Cells
Sun, Z., Terragni, J., Borgaro, J. G., Liu, Y., Yu, L., Guan, S., Wang, H., Sun, D., Cheng, X., Zhu, Z., et al. (2013) · Cell Reports · doi:10.1016/j.celrep.2013.01.001 · Cited by 170 · see citing works
Single-Cell Transcriptome Analysis Reveals Dynamic Changes in lncRNA Expression during Reprogramming
Kim, D. H., Marinov, G. K., Pepke, S., Singer, Z. S., He, P., Williams, B. A., Schroth, G. P., Elowitz, M. B., & Wold, B. J. (2015) · Cell stem cell · doi:10.1016/j.stem.2014.11.005 · Cited by 163 · see citing works
Nagano, T., Lubling, Y., Yaffe, E., Wingett, S., Dean, W., Tanay, A., & Fraser, P. (2015) · Nature Protocols · doi:10.1038/nprot.2015.127 · Cited by 159 · see citing works
Single-cell nucleosome mapping reveals the molecular basis of gene expression heterogeneity
Small, E. C., Xi, L., Wang, J.-P., Widom, J., & Licht, J. D. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1400517111 · Cited by 105 · see citing works
High-Throughput Single-Cell Labeling (Hi-SCL) for RNA-Seq Using Drop-Based Microfluidics
Rotem, A., Ram, O., Noam Shoresh, F., Sperling, R. A., Schnall-Levin, M., Zhang, H., Basu, A., Bernstein, B., & Weitz, D. A. (2015) · PLoS ONE · doi:10.1371/journal.pone.0116328 · Cited by 77 · see citing works
Counting absolute number of molecules using unique molecular identifiersPreprint
Kivioja, T., Vähärautio, A., Karlsson, K., Bonke, M., Linnarsson, S., & Taipale, J. (2011) · Nature Precedings · doi:10.1038/npre.2011.5903.1 · Cited by 58 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Current and future perspectives of liquid biopsies in genomics-driven oncology
Heitzer, E., Haque, I. S., Roberts, C. E. S., & Speicher, M. R. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-018-0071-5 · Cited by 1,557 · 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
Clark, S. J., Argelaguet, R., Kapourani, C.-A., Stubbs, T. M., Lee, H. J., Alda-Catalinas, C., Krueger, F., Sanguinetti, G., Kelsey, G., Marioni, J. C., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-03149-4 · Cited by 657 · see citing works
Self-citationSingle-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
Dynamics of the epigenetic landscape during the maternal-to-zygotic transition
Eckersley-Maslin, M. A., Alda-Catalinas, C., & Reik, W. (2018) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-018-0008-z · Cited by 431 · see citing works
Self-citationChallenges 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
Clark, S. J., Smallwood, S. A., Lee, H. J., Krueger, F., Reik, W., & Kelsey, G. (2017) · Nature Protocols · doi:10.1038/nprot.2016.187 · Cited by 270 · see citing works
Self-citationPenner-Goeke, S., & Binder, E. B. (2019) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2019.21.4/ebinder · Cited by 254 · see citing works
Yuan, M., Yang, B., Rothschild, G., Mann, J. J., Sanford, L. D., Tang, X., Huang, C., Wang, C., & Zhang, W. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01519-z · Cited by 246 · see citing works
“106,411 Likewise, although the patterns of histone modi fi cation usually differ between cell types, most studies conducted have examined these modi fi cations in cell populations that are heterogeneous.”
BackgroundMethodSingle-cell DNA methylation profiling: technologies and biological applications
Karemaker, I. D., & Vermeulen, M. (2018) · Trends in Biotechnology · doi:10.1016/j.tibtech.2018.04.002 · Cited by 170 · see citing works
Carter, B., Ku, W. L., Kang, J. Y., Hu, G., Perrie, J., Tang, Q., & Zhao, K. (2019) · Nature Communications · doi:10.1038/s41467-019-11559-1 · Cited by 148 · see citing works
Microglial NLRP3 inflammasome activation in multiple sclerosis
(2020) · Advances in Protein Chemistry and Structural Biology · doi:10.1016/bs.apcsb.2019.08.007 · Cited by 83 · see citing works
Lopez‐Atalaya, J. P., Askew, K. E., Sierra, A., & Gomez‐Nicola, D. (2018) · Developmental Neurobiology · doi:10.1002/dneu.22545 · Cited by 49 · see citing works
Analyzing Circulating Tumor Cells One at a Time
Ortiz, V., & Yu, M. (2018) · Trends in Cell Biology · doi:10.1016/j.tcb.2018.05.004 · Cited by 48 · see citing works
- Authors
- Clark, S. J., Lee, H. J., Smallwood, S. A., Kelsey, G., & Reik, W.
- Affiliations
- Babraham Institute (GB)
- Corresponding author
- Lee, Heather J.
- Venue
- Genome Biology
- Published
- 2016-04-18
- Volume
- 17
- Issue
- 1
- Pages
- 72-72
- ISSN
- 1465-6906 (ISSN-L)
- 1474-760X
- PMC
- PMC4834828
- OpenAlex
- W2340182364
- Cited by
- 310
- References
- 70
- Citations by year
- 2026: 12 · 2025: 23 · 2024: 21 · 2023: 19 · 2022: 24 · 2021: 28 · 2020: 32 · 2019: 42 · 2018: 53 · 2017: 46 · 2016: 9 · 2015: 1
- FWCI
- 4.51
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Genome biology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Apollo (University of Cambridge) (submittedVersion, cc-by)
- Apollo (cc-by)
- Funders
- Biotechnology and Biological Sciences Research Council
- Medical Research Council
- Wellcome Trust
- Seventh Framework Programme
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Keywords
- single-cell epigenomics, gene expression regulation, cell identity, chromatin accessibility, single-cell sequencing, multi-omics integration, gene expression profiling
- MeSH terms
- Animals, Gene Expression Regulation, Humans, DNA Methylation, Epigenomics, Single-Cell Analysis
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
