Single-Cell Transcriptomics Meets Lineage Tracing
Open accessAbstract
Reconstructing lineage relationships between cells within a tissue or organism is a long-standing aim in biology. Traditionally, lineage tracing has been achieved through the (genetic) labeling of a cell followed by the tracking of its offspring. Currently, lineage trajectories can also be predicted using single-cell transcriptomics. Although single-cell transcriptomics provides detailed phenotypic information, the predicted lineage trajectories do not necessarily reflect genetic relationships. Recently, techniques have been developed that unite these strategies. In this Review, we discuss transcriptome-based lineage trajectory prediction algorithms, single-cell genetic lineage tracing, and the promising combination of these techniques for stem cell and cancer research.
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Single-cell RNA sequencing (scRNA-seq) is a powerful approach for reconstructing cellular differentiation trajectories.
“Single-cell RNA sequencing (scRNA-seq) is a powerful approach for reconstructing cellular differentiation trajectories.”
From Single-cell transcriptional diversity is a hallmark of developmental potential (2020) · cites this paper as [5]
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BackgroundLineage tracing meets single-cell omics: opportunities and challenges
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“However, clonal tracing techniques that are being developed to progressively record clonal histories of individual cells (56) would be ideally suited for validation of a complex differentiation process such as the one that takes place in neural crest.”
BackgroundLineage Tracing in Humans Enabled by Mitochondrial Mutations and Single-Cell Genomics
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A lineage-resolved molecular atlas of C. elegans embryogenesis at single-cell resolution
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“Because of these challenges, we anticipate that constructing end-to-end trajectories of vertebrate organogenesis will require the integration of sc-RNA-seq with experimental lineage-tracing methods (47).”
Integrating genetic and non-genetic determinants of cancer evolution by single-cell multi-omics
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Single-cell RNA sequencing in cardiovascular development, disease and medicine
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High-throughput and single-cell T cell receptor sequencing technologies
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Smooth Muscle Cell Phenotypic Diversity
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Establishing neuronal diversity in the spinal cord: a time and a place
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Live-seq enables temporal transcriptomic recording of single cells
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“For a detailed discussion of lineage tracing approaches, we refer the reader to Kester and van Oudenaarden (2018), and to McKenna and Gagnon (2019) in this issue.”
MethodIdentification, discrimination and heterogeneity of fibroblasts
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BackgroundComputational methods for single-cell omics across modalities
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Generation of a p16 Reporter Mouse and Its Use to Characterize and Target p16high Cells In Vivo
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Unravelling cellular relationships during development and regeneration using genetic lineage tracing
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The road ahead in genetics and genomics
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Recording development with single cell dynamic lineage tracing
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Adult hippocampal neurogenesis in Alzheimer’s disease: a roadmap to clinical relevance
Salta, E., Lazarov, O., Fitzsimons, C., Tanzi, R., Lucassen, P., & Choi, S.-H. (2023) · Cell Stem Cell · doi:10.1016/j.stem.2023.01.002 · Cited by 147 · see citing works
“195 Along these lines, analyzing anatomical substructures of the DG targeted by microdissection may be necessary to enrich for cellular populations of interest and thereby ensure that any significant alterations between groups of individuals can be detected.”
BackgroundNext-generation computational tools for interrogating cancer immunity
Finotello, F., Rieder, D., Hackl, H., & Trajanoski, Z. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0166-7 · Cited by 158 · see citing works
Cell lineage and communication network inference via optimization for single-cell transcriptomics
Wang, S., Karikomi, M. K., MacLean, A. L., & Nie, Q. H. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz204 · Cited by 153 · see citing works
“For the whole family of methods for pseudotime inference (the mathematical foundations of which vary considerably, see (28) for review), experimental validation of the temporal ordering of cells is difficult (15).”
BackgroundMethodZhang, X., Powell, K. A., & Li, L. (2020) · Cancers · doi:10.3390/cancers12123765 · Cited by 154 · see citing works
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“Furthermore, the relatively high cost of these experiments hinders the large-scale application of such methods [9].”
BackgroundCell Plasticity in Liver Regeneration
Li, W., Li, L., & Hui, L. (2020) · Trends in Cell Biology · doi:10.1016/j.tcb.2020.01.007 · Cited by 167 · see citing works
Next-Generation Lineage Tracing and Fate Mapping to Interrogate Development
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The Impact of Heterogeneity on Single-Cell Sequencing
Goldman, S. L., MacKay, M. J., Afshinnekoo, E., Melnick, A. M., Wu, S., & Mason, C. E. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00008 · Cited by 139 · see citing works
Inference of single-cell phylogenies from lineage tracing data using Cassiopeia
Jones, M. G., Khodaverdian, A., Quinn, J. J., Chan, M. M., Hussmann, J. A., Wang, R., Xu, C. A., Weissman, J. S., & Yosef, N. (2020) · Genome biology · doi:10.1186/s13059-020-02000-8 · Cited by 135 · see citing works
Acquired resistance in cancer: towards targeted therapeutic strategies
Soragni, A., Knudsen, E. S., O’Connor, T. N., Tognon, C. E., Tyner, J. W., Gini, B., Kim, D., Bivona, T. G., Zang, X., Witkiewicz, A. K., et al. (2025) · Nature reviews. Cancer · doi:10.1038/s41568-025-00824-9 · Cited by 145 · see citing works
“…lineage tracing measurements represents an efficient tool to study the acquisition of resistance over time using in vitro and in vivo tumour models by capturing state transitions and transcriptional rewiring of lineage populations during the responsive and resistant states of treatment 259,260 .”
Dissecting Cellular Heterogeneity Using Single-Cell RNA Sequencing.
Choi, Y. H., & Kim, J. K. (2019) · Europe PMC (PubMed Central) · doi:10.14348/molcells.2019.2446 · Cited by 120 · see citing works
Applications of Single-Cell DNA Sequencing
Evrony, G. D., Hinch, A. G., & Luo, C. (2021) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-111320-090436 · Cited by 120 · see citing works
“These methods, which have been reviewed elsewhere (7, 74, 115, 160), have enabled high-throughput phenotypic lineage tracing for the first time and have removed the requirement for scDNA seq in prospective lineage tracing of animal models.”
BackgroundMethodCoSpar identifies early cell fate biases from single-cell transcriptomic and lineage information
Wang, S., Herriges, M. J., Hurley, K., Kotton, D. N., & Klein, A. M. (2022) · Nature Biotechnology · doi:10.1038/s41587-022-01209-1 · Cited by 112 · see citing works
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“We next inferred a cell lineage tree from these 8 cell clusters using a minimal spanning tree approach 24 as described in the reprogramming study (Fig.5e, Methods).”
Fibroblastic reticular cells at the nexus of innate and adaptive immune responses
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Computational strategies for single-cell multi-omics integration
Adossa, N. A., Khan, S., Rytkönen, K. T., & Elo, L. L. (2021) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2021.04.060 · Cited by 106 · see citing works
Liu, J., Ottaviani, D., Sefta, M., Desbrousses, C., Chapeaublanc, E., Aschero, R., Sirab, N., Lubieniecki, F. J., Lamas, G., Tonon, L., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-25792-0 · Cited by 103 · see citing works
Clonal lineage tracing reveals shared origin of conventional and plasmacytoid dendritic cells
Feng, J., Pucella, J. N., Jang, G., Alcántara‐Hernández, M., Upadhaya, S., Adams, N. M., Khodadadi‐Jamayran, A., Lau, C. M., Stoeckius, M., Hao, S. P., et al. (2022) · Immunity · doi:10.1016/j.immuni.2022.01.016 · Cited by 106 · see citing works
Isakova, A., Neff, N. F., & Quake, S. R. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2113568118 · Cited by 97 · see citing works
Phylodynamics for cell biologists
Stadler, T., Pybus, O. G., & Stumpf, M. P. H. (2021) · Science · doi:10.1126/science.aah6266 · Cited by 97 · see citing works
“4B) (16, 75–77), with the potential to reveal robust insights into the underlying cell state transition diagram (40).”
BackgroundMethodConnecting past and present: single-cell lineage tracing
Chen, C., Liao, Y., & Peng, G. (2022) · Protein & Cell · doi:10.1007/s13238-022-00913-7 · Cited by 93 · see citing works
“…various aspects of its basic concepts, sequence architectures, computational tools, and so on (Woodworth et al., 2017; Kebschull and Zador, 2018; Kester and van Oudenaarden, 2018; Baron and van Oudenaarden, 2019; McKenna and Gagnon, 2019; Wu et al., 2019; VanHorn and Morris, 2020; Wagner and…”
BackgroundMultimodal deep learning approaches for single-cell multi-omics data integration
Athaya, T., Ripan, R. C., Li, X., & Hu, H. (2023) · Briefings in Bioinformatics · doi:10.1093/bib/bbad313 · Cited by 94 · see citing works
“It has found extensive use in cancer research, where it helps track the growth of different cell clones and understand tumor development [19–21].”
BackgroundKong, W., Biddy, B. A., Kamimoto, K., Amrute, J., Butka, E. G., & Morris, S. A. (2020) · Nature Protocols · doi:10.1038/s41596-019-0247-2 · Cited by 93 · see citing works
“Fundamen-tally, lineage tracing is based on the unique labeling of individual cells, either via the exploitation of naturally occurring somatic mutations 32 – 34 or experimentally induced heritable marks 35 .”
BackgroundSingle-Cell RNA Sequencing for Plant Research: Insights and Possible Benefits
Bawa, G., Liu, Z., Yu, X., Qin, A., & Sun, X. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23094497 · Cited by 96 · see citing works
Mapping human cell phenotypes to genotypes with single-cell genomics
Camp, J. G., Platt, R. J., & Treutlein, B. (2019) · Science · doi:10.1126/science.aax6648 · Cited by 83 · see citing works
Jindal, K., Adil, M. T., Yamaguchi, N., Yang, X., Wang, H. C., Kamimoto, K., Rivera-Gonzalez, G. C., & Morris, S. A. (2024) · Nature Biotechnology · doi:10.1038/s41587-023-01931-4 · Cited by 82 · see citing works
“In particular, single-cell lineage-tracing (scLT) methods allow cell relationships to be tracked throughout biological processes, revealing cell fate decisions during differentiation and reprogramming 4,5 .”
Zhang, K., Chen, S., Sun, H., Wang, L., Li, H., Zhao, J., Zhang, C., Li, N., Guo, Z., Han, Z., et al. (2020) · Journal of Biological Chemistry · doi:10.1074/jbc.ra120.012732 · Cited by 85 · see citing works
Lange, C. M., Rost, F., Machate, A., Reinhardt, S., Lesche, M., Weber, A., Kuscha, V., Dahl, A., Rulands, S., & Brand, M. (2020) · Development · doi:10.1242/dev.185595 · Cited by 78 · see citing works
Evolution of metastasis: new tools and insights
Gui, P., & Bivona, T. G. (2021) · Trends in cancer · doi:10.1016/j.trecan.2021.11.002 · Cited by 83 · see citing works
Concerted localization-resets precede YAP-dependent transcription
Franklin, J. M., Ghosh, R. P., Shi, Q., Reddick, M. P., & Liphardt, J. (2020) · Nature Communications · doi:10.1038/s41467-020-18368-x · Cited by 82 · see citing works
Single-cell lineage tracing by integrating CRISPR-Cas9 mutations with transcriptomic data
Zafar, H., Lin, C. H., & Bar‐Joseph, Z. (2020) · Nature Communications · doi:10.1038/s41467-020-16821-5 · Cited by 81 · see citing works
“Elucidating the relationships among the diverse cell types can provide key insights into the fundamental processes underlying normal tissue development as well as valuable information on what goes wrong in developmental diseases 1 – 3 .”
BackgroundMethodInfluentialThe transcriptome dynamics of single cells during the cell cycle
Schwabe, D., Formichetti, S., Junker, J. P., Falcke, M., & Rajewsky, N. (2020) · Molecular Systems Biology · doi:10.15252/msb.20209946 · Cited by 76 · see citing works
Immunology in the Era of Single-Cell Technologies
Efremova, M., Vento‐Tormo, R., Park, J.-E., Teichmann, S. A., & James, K. R. (2020) · Annual Review of Immunology · doi:10.1146/annurev-immunol-090419-020340 · Cited by 77 · see citing works
Recharacterizing Tumor-Infiltrating Lymphocytes by Single-Cell RNA Sequencing
Zhang, L., & Zhang, Z. (2019) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-18-0658 · Cited by 77 · see citing works
PhyloVelo enhances transcriptomic velocity field mapping using monotonically expressed genes
Wang, K., Hou, L., Wang, X., Zhai, X., Lu, Z., Zi, Z., Zhai, W., He, X., Curtis, C., Zhou, D., et al. (2024) · Nature Biotechnology · doi:10.1038/s41587-023-01887-5 · Cited by 66 · see citing works
“…of CRISPR lineage tracing coupled with single-cell transcriptomics has been widely acknowledged in developmental biology and somatic evolution 13,29,33 , computationally integrating dual information for reconstructing cellular trajectories is challenging, partially due to the distinct data…”
Single-cell RNA-seq clustering: datasets, models, and algorithms
Peng, L., Tian, X., Tian, G., Xu, J., Huang, X., Weng, Y., Yang, J., & Zhou, L. (2020) · RNA Biology · doi:10.1080/15476286.2020.1728961 · Cited by 74 · see citing works
Critical downstream analysis steps for single-cell RNA sequencing data
Zhang, Z., Cui, F., Lin, C., Zhao, L., Wang, C., & Zou, Q. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab105 · Cited by 70 · see citing works
Exploring single cells in space and time during tissue development, homeostasis and regeneration
Mayr, U., Serra, D., & Liberali, P. (2019) · Development · doi:10.1242/dev.176727 · Cited by 63 · see citing works
Using single-cell RNA sequencing to unravel cell lineage relationships in the respiratory tract
Zaragosi, L., Deprez, M., & Barbry, P. (2020) · Biochemical Society Transactions · doi:10.1042/bst20191010 · Cited by 67 · see citing works
Single-Cell RNA Sequencing: Technological Progress and Biomedical Application in Cancer Research
Xu, C., Zheng, Y., & Xu, K. (2023) · Molecular Biotechnology · doi:10.1007/s12033-023-00777-0 · Cited by 74 · see citing works
“Owing to genome-scale single-cell analysis, our understanding has shifted over the past few years from an animation of discontinuous changes to a dynamic state driven by data [63].”
BackgroundInfluentialCell Taxonomy: a curated repository of cell types with multifaceted characterization
Jiang, S., Qian, Q., Zhu, T., Zong, W., Shang, Y., Jin, T., Zhang, Y., Chen, M., Wu, Z., Chu, Y., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac816 · Cited by 66 · see citing works
“8% (2,601) are annotated with available cell markers, giving rise to a total of 226,222 entries collected from 4,299 publications.”
BackgroundGiudice, Q. L., Leleu, M., Manno, G. L., & Fabre, P. J. (2019) · Development · doi:10.1242/dev.178103 · Cited by 65 · see citing works
Osorio, D., Zhong, Y., Li, G., Huang, J. Z., & Cai, J. J. (2020) · Patterns · doi:10.1016/j.patter.2020.100139 · Cited by 65 · see citing works
Gong, W., Granados, A. A., Hu, J., Jones, M. G., Raz, O., Salvador-Martínez, I., Zhang, H., Chow, K.-H. K., Kwak, I.-Y., Retkute, R., et al. (2021) · Cell Systems · doi:10.1016/j.cels.2021.05.008 · Cited by 62 · see citing works
Tumor Dormancy and Slow-Cycling Cancer Cells
DAVIS, J. E., Kirk, J. S., Ji, Y., & Tang, D. G. (2019) · Advances in experimental medicine and biology · doi:10.1007/978-3-030-22254-3_15 · Cited by 62 · see citing works
Spatio-temporal mRNA tracking in the early zebrafish embryo
Holler, K., Neuschulz, A., Drewe-Boß, P., Mintcheva, J., Spanjaard, B., Arsiè, R., Ohler, U., Landthaler, M., & Junker, J. P. (2021) · Nature Communications · doi:10.1038/s41467-021-23834-1 · Cited by 55 · see citing works
Investigating Tumor Heterogeneity in Mouse Models
Tammela, T., & Sage, J. (2019) · Annual Review of Cancer Biology · doi:10.1146/annurev-cancerbio-030419-033413 · Cited by 58 · see citing works
Single-Cell Applications of Next-Generation SequencingPreprint
Anaparthy, N., Ho, Y.-J., Martelotto, L. G., Hammell, M., & Hicks, J. B. (2019) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a026898 · Cited by 55 · see citing works
“…RNA molecules for NGS, and now highthroughput RNA transcriptomics to both classify all the neuroanatomical cell types and trace the lineages back to stem cells (Dulken et al. 2017; also see Kester and van Oudenaarden 2018 for a detailed review on the general topic of transcriptomics and lineage).”
BackgroundThe Source and Dynamics of Adult Hematopoiesis: Insights from Lineage Tracing
Pucella, J. N., Upadhaya, S., & Reizis, B. (2020) · Annual Review of Cell and Developmental Biology · doi:10.1146/annurev-cellbio-020520-114601 · Cited by 53 · see citing works
Midbrain Dopaminergic Neuron Development at the Single Cell Level: In vivo and in Stem Cells
Ásgrímsdóttir, E. S., & Arenas, E. (2020) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2020.00463 · Cited by 51 · see citing works
Deciphering Cell Fate Decision by Integrated Single-Cell Sequencing Analysis
Sagar, & Grün, D. (2020) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-111419-091750 · Cited by 48 · see citing works
“Current DNA-based barcoding approaches can be broadly divided into three different categories: viral transduction–based, recombinase-based, and CRISPR-based techniques (19, 95).”
BackgroundEmploying core regulatory circuits to define cell identity
Almeida, N., Chung, M. W. H., Drudi, E. M., Engquist, E. N., Hamrud, E., Isaacson, A., Tsang, V. S. K., Watt, F. M., & Spagnoli, F. M. (2021) · The EMBO Journal · doi:10.15252/embj.2020106785 · Cited by 49 · see citing works
“In developmental systems, the concept of cell state refers to cell fate transition along a particular developmental trajectory (Kester & van Oudenaarden, 2018).”
Lineage Tracing: Computational Reconstruction Goes Beyond the Limit of Imaging.
Wu, S.-H. S., Lee, J., & Koo, B. (2019) · Europe PMC (PubMed Central) · doi:10.14348/molcells.2019.0006 · Cited by 44 · see citing works
“Numerous trajectory inference algorithms have been developed in recent years (Kester and van Oudenaarden, 2018; Ye and Sarkar, 2018) 106 Mol.”
BackgroundMethodThe emergence and promise of single-cell temporal-omics approaches
Lederer, A. R., & Manno, G. L. (2020) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2019.12.005 · Cited by 41 · see citing works
Iqbal, F., Lupieri, A., Aikawa, M., & Aikawa, E. R. (2020) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.120.314776 · Cited by 44 · see citing works
Stem cell mutations, associated cancer risk, and consequences for regenerative medicine
Derks, L. L. M., & van Boxtel, R. (2023) · Cell stem cell · doi:10.1016/j.stem.2023.09.008 · Cited by 45 · see citing works
Cellular diversity and lineage trajectory: insights from mouse single cell transcriptomes
Tam, P., & Ho, J. W. K. (2020) · Development · doi:10.1242/dev.179788 · Cited by 43 · see citing works
Peng, G., Cui, G., Ke, J., & Jing, N. (2020) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-120219-083220 · Cited by 42 · see citing works
Exploiting Single-Cell Tools in Gene and Cell Therapy
Bode, D., Cull, A. H., Rubio-Lara, J. A., & Kent, D. G. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.702636 · Cited by 43 · see citing works
Single‐cell omics: Overview, analysis, and application in biomedical science
Stein, C. M., Weiskirchen, R., Damm, F., & Strzelecka, P. M. (2021) · Journal of Cellular Biochemistry · doi:10.1002/jcb.30134 · Cited by 42 · see citing works
“It can be used to trace the expansion of different clones and reconstruct cell lineages in the mosaic tissue of the tumour.(10,11) In addition, scDNA‐seq has the power to characterise rare cell types (e.”
BackgroundVolumetric compression develops noise-driven single-cell heterogeneity
Zhao, X., Hu, J., Li, Y., & Guo, M. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2110550118 · Cited by 42 · see citing works
Machine learning enables prediction of metabolic system evolution in bacteria
Konno, N., & Iwasaki, W. (2023) · Science Advances · doi:10.1126/sciadv.adc9130 · Cited by 40 · see citing works
“From a broader perspective, singlecell transcriptomics will also be empowered if a cell lineage tree and a cell-gene matrix of expression levels (as a trait table) are given to Evodictor to decipher the universal rules behind cell differentiation by taking advantage of the rapidly progressing cell lineage tracing tech…”
BackgroundeHSCPr discriminating the cell identity involved in endothelial to hematopoietic transition
Wang, H., Liang, P., Zheng, L., Long, C., Li, H., & Zuo, Y. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab071 · Cited by 40 · see citing works
Li, G., Fang, N., Yuan, G.-H., Liu, C., Liu, X., Chen, L., Tian, B., & Yang, L. C. (2021) · Genome biology · doi:10.1186/s13059-021-02437-5 · Cited by 40 · see citing works
Toward a Consensus in the Repertoire of Hemocytes Identified in Drosophila
Cattenoz, P. B., Monticelli, S., Pavlidaki, A., & Giangrande, A. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.643712 · Cited by 39 · see citing works
“…differentiation of lamellocytes that encapsulate the wasp eggs or participate to the wound closure (Figure 1A) and the same cell type is found upon the activation of proinflammatory pathways (Lemaitre et al., 1995; Luo et al., 1995; Markus et al., 2005; Fleury et al., 2009; Kim-Jo et al., 2019).”
BackgroundXu, X., Hua, X., Han, M., Hu, S., & Song, J. (2023) · Basic Research in Cardiology · doi:10.1007/s00395-022-00972-1 · Cited by 37 · see citing works
“In addition, scRNA-seq can also be combined with lineage tracing techniques at cellular level, searching for the lineage origin and phenotypic alterations of specific cell populations in disease status [71, 175].”
Application of single-cell RNA sequencing on human skin: Technical evolution and challenges
Kim, D., Chung, K. B., & Kim, T. (2020) · Journal of Dermatological Science · doi:10.1016/j.jdermsci.2020.06.002 · Cited by 36 · see citing works
Computational Stem Cell Biology: Open Questions and Guiding Principles
Cahan, P., Cacchiarelli, D., Dunn, S.-J., Hemberg, M., Lopes, S. M. C. D. S., Morris, S. A., Rackham, O. J. L., del Sol, A., & Wells, C. A. (2021) · Cell stem cell · doi:10.1016/j.stem.2020.12.012 · Cited by 36 · see citing works
“These methods are based on uniquely labeling individual cells by leveraging naturally occurring somatic mutations (Leung et al., 2017; Lodato et al., 2015) or experimentally introducing heritable genetic makers (Kester and van Oudenaarden, 2018).”
MethodSingle-cell and spatial transcriptomics: Advances in heart development and disease applications
Long, X., Yuan, X., & Du, J. (2023) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2023.04.007 · Cited by 37 · see citing works
- Authors
- Kester, L., & van Oudenaarden, A.
- Affiliations
- Royal Netherlands Academy of Arts and Sciences (NL)
- ORCID
- Kester, Lennart
- Venue
- Cell Stem Cell
- Publisher
- Elsevier BV
- Published
- 2018-08
- Volume
- 23
- Issue
- 2
- Pages
- 166-179
- ISSN
- 1875-9777 (ISSN-L)
- 1934-5909
- OpenAlex
- W2801820889
- Cited by
- 375
- References
- 145
- Citations by year
- 2026: 30 · 2025: 33 · 2024: 32 · 2023: 37 · 2022: 45 · 2021: 61 · 2020: 71 · 2019: 55 · 2018: 10 · 2012: 1
- FWCI
- 4.83
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell stem cell (publishedVersion)
- PubMed (publishedVersion)
- KNAW research portal (Royal Academy of Art and Sciences (KNAW)) (publishedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
- KNAW Research Portal (The Royal Netherlands Academy of Arts and Sciences) (submittedVersion)
- Funders
- European Research Council Advanced grant (ERC-AdG 742225-IntScOmics)
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO) TOP award (NWO-CW 714.016.001)
- Dutch Cancer Society project grant (KWF project 10158, 2016-1)
- Oncode Institute
- Dutch Cancer Society
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Developmental Biology and Gene Regulation
- Keywords
- lineage tracing, single-cell transcriptomics, stem cells, cancer
- MeSH terms
- Animals, Humans, Cell Lineage, Cell Tracking, Single-Cell Analysis, Transcriptome
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