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Volumn 20, Issue 5, 2019, Pages 273-282

Publisher Correction: Challenges in unsupervised clustering of single-cell RNA-seq data (Nature Reviews Genetics, (2019), 20, 5, (273-282), 10.1038/s41576-018-0088-9);Challenges in unsupervised clustering of single-cell RNA-seq data

Author keywords

[No Author keywords available]

Indexed keywords

RNA; SINGLE CELL RNA; TRANSCRIPTOME; UNCLASSIFIED DRUG;

EID: 85059701495     PISSN: 14710056     EISSN: 14710064     Source Type: Journal    
DOI: 10.1038/s41576-019-0095-5     Document Type: Erratum
Times cited : (737)

References (115)
  • 1
    • 67349146589 scopus 로고    scopus 로고
    • mRNA-Seq whole-transcriptome analysis of a single cell
    • COI: 1:CAS:528:DC%2BD1MXktVKgu78%3D, PID: 19349980
    • Tang, F. et al. mRNA-Seq whole-transcriptome analysis of a single cell. Nat. Methods 6, 377–382 (2009).
    • (2009) Nat. Methods , vol.6 , pp. 377-382
    • Tang, F.1
  • 3
    • 84929684999 scopus 로고    scopus 로고
    • Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets
    • COI: 1:CAS:528:DC%2BC2MXpt1Sgt7o%3D, PID: 26000488
    • Macosko, E. Z. et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161, 1202–1214 (2015).
    • (2015) Cell , vol.161 , pp. 1202-1214
    • Macosko, E.Z.1
  • 4
    • 85041394976 scopus 로고    scopus 로고
    • SCANPY: large-scale single-cell gene expression data analysis
    • PID: 29409532
    • Wolf, F. A., Angerer, P. & Theis, F. J. SCANPY: large-scale single-cell gene expression data analysis. Genome Biol. 19, 15 (2018).
    • (2018) Genome Biol. , vol.19
    • Wolf, F.A.1    Angerer, P.2    Theis, F.J.3
  • 5
    • 84949293695 scopus 로고    scopus 로고
    • SINCERA: a pipeline for single-cell RNA-Seq profiling analysis
    • PID: 26600239
    • Guo, M., Wang, H., Potter, S. S., Whitsett, J. A. & Xu, Y. SINCERA: a pipeline for single-cell RNA-Seq profiling analysis. PLOS Comput. Biol. 11, e1004575 (2015).
    • (2015) PLOS Comput. Biol. , vol.11
    • Guo, M.1    Wang, H.2    Potter, S.S.3    Whitsett, J.A.4    Xu, Y.5
  • 6
    • 84923647450 scopus 로고    scopus 로고
    • Computational and analytical challenges in single-cell transcriptomics
    • COI: 1:CAS:528:DC%2BC2MXhs1Shur4%3D, PID: 25628217
    • Stegle, O., Teichmann, S. A. & Marioni, J. C. Computational and analytical challenges in single-cell transcriptomics. Nat. Rev. Genet. 16, 133–145 (2015).
    • (2015) Nat. Rev. Genet. , vol.16 , pp. 133-145
    • Stegle, O.1    Teichmann, S.A.2    Marioni, J.C.3
  • 7
    • 85010931059 scopus 로고    scopus 로고
    • A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor. [version 2; referees: 3 approved, 2 approved with reservations]
    • PID: 27909575
    • Lun, A. T. L., McCarthy, D. J. & Marioni, J. C. A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor. [version 2; referees: 3 approved, 2 approved with reservations]. F1000Res 5, 2122 (2016).
    • (2016) F1000Res , vol.5 , pp. 2122
    • Lun, A.T.L.1    McCarthy, D.J.2    Marioni, J.C.3
  • 8
    • 85027696020 scopus 로고    scopus 로고
    • A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications
    • PID: 28821273
    • Haque, A., Engel, J., Teichmann, S. A. & Lönnberg, T. A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications. Genome Med. 9, 75 (2017).
    • (2017) Genome Med. , vol.9
    • Haque, A.1    Engel, J.2    Teichmann, S.A.3    Lönnberg, T.4
  • 9
    • 85064576822 scopus 로고    scopus 로고
    • satijalab.org, References 4 and 9 are unsupervised clustering methods based on the Louvain method that have been shown to perform very well for large scRNA-seq data sets
    • Satija, R. SEURAT - R toolkit for single cell genomics: single cell integration in Seurat v3.0. satijalab.org https://satijalab.org/seurat/ (2015). References 4 and 9 are unsupervised clustering methods based on the Louvain method that have been shown to perform very well for large scRNA-seq data sets.
    • (2015) SEURAT - R Toolkit for Single Cell Genomics: Single Cell Integration in Seurat V3.0
    • Satija, R.1
  • 11
    • 77950369345 scopus 로고    scopus 로고
    • Data clustering: 50 years beyond K-means
    • Jain, A. K. Data clustering: 50 years beyond K-means. Pattern Recognit. Lett. 31, 651–666 (2010).
    • (2010) Pattern Recognit. Lett. , vol.31 , pp. 651-666
    • Jain, A.K.1
  • 13
    • 85050565701 scopus 로고    scopus 로고
    • Molecular architecture of the mouse nervous system
    • Preprint at
    • Zeisel, A. et al. Molecular architecture of the mouse nervous system. Preprint at bioRxiv 10.1101/294918 (2018).
    • (2018) bioRxiv
    • Zeisel, A.1
  • 14
    • 85042366842 scopus 로고    scopus 로고
    • Mapping the mouse cell atlas by Microwell-Seq
    • COI: 1:CAS:528:DC%2BC1cXjt12ltr4%3D, PID: 29474909, References 12–14 are large collections of scRNA-seq data from mouse, and they give an indication of what a full atlas could look like
    • Han, X. et al. Mapping the mouse cell atlas by Microwell-Seq. Cell 172, 1091–1107 (2018). References 12–14 are large collections of scRNA-seq data from mouse, and they give an indication of what a full atlas could look like.
    • (2018) Cell , vol.172 , pp. 1091-1107
    • Han, X.1
  • 15
    • 85045640021 scopus 로고    scopus 로고
    • Single-cell RNA-seq reveals hidden transcriptional variation in malaria parasites
    • PID: 29580379
    • Reid, A. J. et al. Single-cell RNA-seq reveals hidden transcriptional variation in malaria parasites. eLife 7, e33105 (2018).
    • (2018) eLife , vol.7
    • Reid, A.J.1
  • 16
    • 85048501088 scopus 로고    scopus 로고
    • A single-cell transcriptome atlas of the aging Drosophila brain
    • COI: 1:CAS:528:DC%2BC1cXhtFCqtL3O, PID: 29909982
    • Davie, K. et al. A single-cell transcriptome atlas of the aging Drosophila brain. Cell 174, 982–998 (2018).
    • (2018) Cell , vol.174 , pp. 982-998
    • Davie, K.1
  • 17
    • 85044334985 scopus 로고    scopus 로고
    • The cis-regulatory dynamics of embryonic development at single-cell resolution
    • COI: 1:CAS:528:DC%2BC1cXksFegu7g%3D, PID: 29539636
    • Cusanovich, D. A. et al. The cis-regulatory dynamics of embryonic development at single-cell resolution. Nature 555, 538–542 (2018).
    • (2018) Nature , vol.555 , pp. 538-542
    • Cusanovich, D.A.1
  • 18
    • 85032448109 scopus 로고    scopus 로고
    • The Human Cell Atlas: from vision to reality
    • COI: 1:CAS:528:DC%2BC2sXhslajtr7M, PID: 29072289
    • Rozenblatt-Rosen, O., Stubbington, M. J. T., Regev, A. & Teichmann, S. A. The Human Cell Atlas: from vision to reality. Nature 550, 451–453 (2017).
    • (2017) Nature , vol.550 , pp. 451-453
    • Rozenblatt-Rosen, O.1    Stubbington, M.J.T.2    Regev, A.3    Teichmann, S.A.4
  • 20
    • 84887109584 scopus 로고    scopus 로고
    • Accounting for technical noise in single-cell RNA-seq experiments
    • COI: 1:CAS:528:DC%2BC3sXhsVyqtb3L, PID: 24056876
    • Brennecke, P. et al. Accounting for technical noise in single-cell RNA-seq experiments. Nat. Methods 10, 1093–1095 (2013).
    • (2013) Nat. Methods , vol.10 , pp. 1093-1095
    • Brennecke, P.1
  • 21
    • 0020102027 scopus 로고
    • Least squares quantization in PCM
    • Lloyd, S. Least squares quantization in PCM. IEEE Trans. Inform. Theory 28, 129–137 (1982).
    • (1982) IEEE Trans. Inform. Theory , vol.28 , pp. 129-137
    • Lloyd, S.1
  • 22
    • 85016121177 scopus 로고    scopus 로고
    • SC3: consensus clustering of single-cell RNA-seq data
    • COI: 1:CAS:528:DC%2BC2sXltVWgtLY%3D, PID: 28346451, SC3 is a user-friendly clustering method that works very well for smaller data sets
    • Kiselev, V. Y. et al. SC3: consensus clustering of single-cell RNA-seq data. Nat. Methods 14, 483–486 (2017). SC3 is a user-friendly clustering method that works very well for smaller data sets.
    • (2017) Nat. Methods , vol.14 , pp. 483-486
    • Kiselev, V.Y.1
  • 23
    • 84941201582 scopus 로고    scopus 로고
    • Single-cell messenger RNA sequencing reveals rare intestinal cell types
    • PID: 26287467
    • Grün, D. et al. Single-cell messenger RNA sequencing reveals rare intestinal cell types. Nature 525, 251–255 (2015).
    • (2015) Nature , vol.525 , pp. 251-255
    • Grün, D.1
  • 24
    • 85014528252 scopus 로고    scopus 로고
    • Visualization and analysis of single-cell RNA-seq data by kernel-based similarity learning
    • COI: 1:CAS:528:DC%2BC2sXltVWgt7c%3D, PID: 28263960
    • Wang, B., Zhu, J., Pierson, E., Ramazzotti, D. & Batzoglou, S. Visualization and analysis of single-cell RNA-seq data by kernel-based similarity learning. Nat. Methods 14, 414–416 (2017).
    • (2017) Nat. Methods , vol.14 , pp. 414-416
    • Wang, B.1    Zhu, J.2    Pierson, E.3    Ramazzotti, D.4    Batzoglou, S.5
  • 25
    • 85016502564 scopus 로고    scopus 로고
    • CIDR: Ultrafast and accurate clustering through imputation for single-cell RNA-seq data
    • PID: 28351406
    • Lin, P., Troup, M. & Ho, J. W. K. CIDR: Ultrafast and accurate clustering through imputation for single-cell RNA-seq data. Genome Biol. 18, 59 (2017).
    • (2017) Genome Biol. , vol.18
    • Lin, P.1    Troup, M.2    Ho, J.W.K.3
  • 26
    • 84924565530 scopus 로고    scopus 로고
    • Brain structure. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq
    • COI: 1:CAS:528:DC%2BC2MXjsF2hsro%3D, PID: 25700174
    • Zeisel, A. et al. Brain structure. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq. Science 347, 1138–1142 (2015).
    • (2015) Science , vol.347 , pp. 1138-1142
    • Zeisel, A.1
  • 27
    • 84977499231 scopus 로고    scopus 로고
    • pcaReduce: hierarchical clustering of single cell transcriptional profiles
    • PID: 27005807
    • Žurauskiene˙, J. & Yau, C. pcaReduce: hierarchical clustering of single cell transcriptional profiles. BMC Bioinformatics 17, 140 (2016).
    • (2016) BMC Bioinformatics , vol.17
    • Žurauskiene˙, J.1    Yau, C.2
  • 28
    • 84961327715 scopus 로고    scopus 로고
    • Adult mouse cortical cell taxonomy revealed by single cell transcriptomics
    • COI: 1:CAS:528:DC%2BC28XitFWqsw%3D%3D, PID: 26727548
    • Tasic, B. et al. Adult mouse cortical cell taxonomy revealed by single cell transcriptomics. Nat. Neurosci. 19, 335–346 (2016).
    • (2016) Nat. Neurosci. , vol.19 , pp. 335-346
    • Tasic, B.1
  • 30
    • 84863516584 scopus 로고    scopus 로고
    • Overlapping community detection in networks
    • Xie, J., Kelley, S. & Szymanski, B. K. Overlapping community detection in networks. ACM Comput. Surv. 45, 1–35 (2013).
    • (2013) ACM Comput. Surv. , vol.45 , pp. 1-35
    • Xie, J.1    Kelley, S.2    Szymanski, B.K.3
  • 32
    • 84934442835 scopus 로고    scopus 로고
    • Data-driven phenotypic dissection of AML reveals progenitor-like cells that correlate with prognosis
    • COI: 1:CAS:528:DC%2BC2MXhtV2it7jE, PID: 26095251
    • Levine, J. H. et al. Data-driven phenotypic dissection of AML reveals progenitor-like cells that correlate with prognosis. Cell 162, 184–197 (2015).
    • (2015) Cell , vol.162 , pp. 184-197
    • Levine, J.H.1
  • 33
    • 85064579299 scopus 로고    scopus 로고
    • matchSCore: matching single-cell phenotypes across tools and experiments
    • Preprint at
    • Mereu, E. et al. matchSCore: matching single-cell phenotypes across tools and experiments. Preprint at bioRxiv 10.1101/314831 (2018).
    • (2018) bioRxiv
    • Mereu, E.1
  • 34
    • 85056462361 scopus 로고    scopus 로고
    • Cluster headache: comparing clustering tools for 10X single cell sequencing data
    • Preprint at
    • Freytag, S., Lonnstedt, I., Ng, M. & Bahlo, M. Cluster headache: comparing clustering tools for 10X single cell sequencing data. Preprint at bioRxiv 10.1101/203752 (2017).
    • (2017) bioRxiv
    • Freytag, S.1    Lonnstedt, I.2    Ng, M.3    Bahlo, M.4
  • 35
    • 85054667891 scopus 로고    scopus 로고
    • Clustering single cells: a review of approaches on high-and low-depth single-cell RNA-seq data
    • Menon, V. Clustering single cells: a review of approaches on high-and low-depth single-cell RNA-seq data. Brief. Funct. Genom. 17, 240–245 (2018).
    • (2018) Brief. Funct. Genom. , vol.17 , pp. 240-245
    • Menon, V.1
  • 36
    • 33846126275 scopus 로고    scopus 로고
    • Resolution limit in community detection
    • COI: 1:CAS:528:DC%2BD2sXjs1Wmug%3D%3D, PID: 17190818
    • Fortunato, S. & Barthélemy, M. Resolution limit in community detection. Proc. Natl Acad. Sci. USA 104, 36–41 (2007).
    • (2007) Proc. Natl Acad. Sci. USA , vol.104 , pp. 36-41
    • Fortunato, S.1    Barthélemy, M.2
  • 39
    • 85049105514 scopus 로고    scopus 로고
    • A comparison of single-cell trajectory inference methods: towards more accurate and robust tools
    • Preprint at
    • Saelens, W., Cannoodt, R., Todorov, H. & Saeys, Y. A comparison of single-cell trajectory inference methods: towards more accurate and robust tools. Preprint at bioRxiv 10.1101/276907 (2018).
    • (2018) bioRxiv
    • Saelens, W.1    Cannoodt, R.2    Todorov, H.3    Saeys, Y.4
  • 40
    • 84900873950 scopus 로고    scopus 로고
    • The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells
    • COI: 1:CAS:528:DC%2BC2cXks12ku7c%3D, PID: 24658644
    • Trapnell, C. et al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat. Biotechnol. 32, 381–386 (2014).
    • (2014) Nat. Biotechnol. , vol.32 , pp. 381-386
    • Trapnell, C.1
  • 41
    • 84982806105 scopus 로고    scopus 로고
    • TSCAN: pseudo-time reconstruction and evaluation in single-cell RNA-seq analysis
    • PID: 27179027
    • Ji, Z. & Ji, H. TSCAN: pseudo-time reconstruction and evaluation in single-cell RNA-seq analysis. Nucleic Acids Res. 44, e117 (2016).
    • (2016) Nucleic Acids Res. , vol.44
    • Ji, Z.1    Ji, H.2
  • 42
    • 84892179132 scopus 로고    scopus 로고
    • Single-cell RNA-seq reveals dynamic, random monoallelic gene expression in mammalian cells
    • COI: 1:CAS:528:DC%2BC2cXktVykug%3D%3D, PID: 24408435
    • Deng, Q., Ramsköld, D., Reinius, B. & Sandberg, R. Single-cell RNA-seq reveals dynamic, random monoallelic gene expression in mammalian cells. Science 343, 193–196 (2014).
    • (2014) Science , vol.343 , pp. 193-196
    • Deng, Q.1    Ramsköld, D.2    Reinius, B.3    Sandberg, R.4
  • 43
    • 84873284300 scopus 로고    scopus 로고
    • Soft clustering – fuzzy and rough approaches and their extensions and derivatives
    • Peters, G., Crespo, F., Lingras, P. & Weber, R. Soft clustering – fuzzy and rough approaches and their extensions and derivatives. Int. J. Approx. Reason. 54, 307–322 (2013).
    • (2013) Int. J. Approx. Reason. , vol.54 , pp. 307-322
    • Peters, G.1    Crespo, F.2    Lingras, P.3    Weber, R.4
  • 44
    • 85047447859 scopus 로고    scopus 로고
    • Graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells
    • Preprint at
    • Wolf, F. A. et al. Graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells. Preprint at bioRxiv 10.1101/208819 (2017).
    • (2017) bioRxiv
    • Wolf, F.A.1
  • 45
    • 84977080410 scopus 로고    scopus 로고
    • Mpath maps multi-branching single-cell trajectories revealing progenitor cell progression during development
    • COI: 1:CAS:528:DC%2BC28XhtFSqtLbP, PID: 27356503
    • Chen, J., Schlitzer, A., Chakarov, S., Ginhoux, F. & Poidinger, M. Mpath maps multi-branching single-cell trajectories revealing progenitor cell progression during development. Nat. Commun. 7, 11988 (2016).
    • (2016) Nat. Commun. , vol.7
    • Chen, J.1    Schlitzer, A.2    Chakarov, S.3    Ginhoux, F.4    Poidinger, M.5
  • 47
    • 85048881841 scopus 로고    scopus 로고
    • Recovering gene interactions from single-cell data using data diffusion
    • PID: 29961576
    • van Dijk, D. et al. Recovering gene interactions from single-cell data using data diffusion. Cell 174, 716–729 (2018).
    • (2018) Cell , vol.174 , pp. 716-729
    • van Dijk, D.1
  • 48
    • 85045314028 scopus 로고    scopus 로고
    • An accurate and robust imputation method scImpute for single-cell RNA-seq data
    • PID: 29520097
    • Li, W. V. & Li, J. J. An accurate and robust imputation method scImpute for single-cell RNA-seq data. Nat. Commun. 9, 997 (2018).
    • (2018) Nat. Commun. , vol.9
    • Li, W.V.1    Li, J.J.2
  • 49
    • 80052521697 scopus 로고    scopus 로고
    • Synthetic spike-in standards for RNA-seq experiments
    • COI: 1:CAS:528:DC%2BC3MXhtFGisLnM, PID: 21816910
    • Jiang, L. et al. Synthetic spike-in standards for RNA-seq experiments. Genome Res. 21, 1543–1551 (2011).
    • (2011) Genome Res. , vol.21 , pp. 1543-1551
    • Jiang, L.1
  • 50
    • 84901831004 scopus 로고    scopus 로고
    • Validation of noise models for single-cell transcriptomics
    • PID: 24747814
    • Grün, D., Kester, L. & van Oudenaarden, A. Validation of noise models for single-cell transcriptomics. Nat. Methods 11, 637–640 (2014).
    • (2014) Nat. Methods , vol.11 , pp. 637-640
    • Grün, D.1    Kester, L.2    van Oudenaarden, A.3
  • 51
    • 84959189722 scopus 로고    scopus 로고
    • Characterizing transcriptional heterogeneity through pathway and gene set overdispersion analysis
    • COI: 1:CAS:528:DC%2BC28Xps1Gjtw%3D%3D, PID: 26780092
    • Fan, J. et al. Characterizing transcriptional heterogeneity through pathway and gene set overdispersion analysis. Nat. Methods 13, 241–244 (2016).
    • (2016) Nat. Methods , vol.13 , pp. 241-244
    • Fan, J.1
  • 52
    • 84903574951 scopus 로고    scopus 로고
    • Bayesian approach to single-cell differential expression analysis
    • COI: 1:CAS:528:DC%2BC2cXotFCjs70%3D, PID: 24836921
    • Kharchenko, P. V., Silberstein, L. & Scadden, D. T. Bayesian approach to single-cell differential expression analysis. Nat. Methods 11, 740–742 (2014).
    • (2014) Nat. Methods , vol.11 , pp. 740-742
    • Kharchenko, P.V.1    Silberstein, L.2    Scadden, D.T.3
  • 53
    • 85021816036 scopus 로고    scopus 로고
    • Normalizing single-cell RNA sequencing data: challenges and opportunities
    • COI: 1:CAS:528:DC%2BC2sXnslKkt7o%3D, PID: 28504683
    • Vallejos, C. A., Risso, D., Scialdone, A., Dudoit, S. & Marioni, J. C. Normalizing single-cell RNA sequencing data: challenges and opportunities. Nat. Methods 14, 565–571 (2017).
    • (2017) Nat. Methods , vol.14 , pp. 565-571
    • Vallejos, C.A.1    Risso, D.2    Scialdone, A.3    Dudoit, S.4    Marioni, J.C.5
  • 54
    • 85044318374 scopus 로고    scopus 로고
    • BEARscc determines robustness of single-cell clusters using simulated technical replicates
    • COI: 1:STN:280:DC%2BC1MnjvF2jtw%3D%3D, PID: 29567991
    • Severson, D. T., Owen, R. P., White, M. J., Lu, X. & Schuster-Böckler, B. BEARscc determines robustness of single-cell clusters using simulated technical replicates. Nat. Commun. 9, 1187 (2018).
    • (2018) Nat. Commun. , vol.9
    • Severson, D.T.1    Owen, R.P.2    White, M.J.3    Lu, X.4    Schuster-Böckler, B.5
  • 56
    • 84977929803 scopus 로고    scopus 로고
    • A reanalysis of mouse ENCODE comparative gene expression data. [version 1; referees: 3 approved, 1 approved with reservations]
    • PID: 26236466
    • Gilad, Y. & Mizrahi-Man, O. A reanalysis of mouse ENCODE comparative gene expression data. [version 1; referees: 3 approved, 1 approved with reservations]. F1000Res 4, 121 (2015).
    • (2015) F1000Res , vol.4 , pp. 121
    • Gilad, Y.1    Mizrahi-Man, O.2
  • 57
    • 85008384488 scopus 로고    scopus 로고
    • Batch effects and the effective design of single-cell gene expression studies
    • COI: 1:CAS:528:DC%2BC2sXkslChtg%3D%3D, PID: 28045081
    • Tung, P.-Y. et al. Batch effects and the effective design of single-cell gene expression studies. Sci. Rep. 7, 39921 (2017).
    • (2017) Sci. Rep. , vol.7
    • Tung, P.-Y.1
  • 58
    • 85046289733 scopus 로고    scopus 로고
    • Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors
    • COI: 1:CAS:528:DC%2BC1cXmslKrtLo%3D, PID: 29608177
    • Haghverdi, L., Lun, A. T. L., Morgan, M. D. & Marioni, J. C. Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors. Nat. Biotechnol. 36, 421–427 (2018).
    • (2018) Nat. Biotechnol. , vol.36 , pp. 421-427
    • Haghverdi, L.1    Lun, A.T.L.2    Morgan, M.D.3    Marioni, J.C.4
  • 59
    • 85046298440 scopus 로고    scopus 로고
    • Integrating single-cell transcriptomic data across different conditions, technologies, and species
    • COI: 1:CAS:528:DC%2BC1cXmslKrtL0%3D, PID: 29608179, References 58 and 59 present the first two methods for correcting batch effects to merge samples
    • Butler, A., Hoffman, P., Smibert, P., Papalexi, E. & Satija, R. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat. Biotechnol. 36, 411–420 (2018). References 58 and 59 present the first two methods for correcting batch effects to merge samples.
    • (2018) Nat. Biotechnol. , vol.36 , pp. 411-420
    • Butler, A.1    Hoffman, P.2    Smibert, P.3    Papalexi, E.4    Satija, R.5
  • 60
  • 61
    • 84903729955 scopus 로고    scopus 로고
    • RNA-seq: impact of RNA degradation on transcript quantification
    • PID: 24885439
    • Gallego Romero, I., Pai, A. A., Tung, J. & Gilad, Y. RNA-seq: impact of RNA degradation on transcript quantification. BMC Biol. 12, 42 (2014).
    • (2014) BMC Biol. , vol.12
    • Gallego Romero, I.1    Pai, A.A.2    Tung, J.3    Gilad, Y.4
  • 62
    • 85042028817 scopus 로고    scopus 로고
    • The effects of death and post-mortem cold ischemia on human tissue transcriptomes
    • PID: 29440659
    • Ferreira, P. G. et al. The effects of death and post-mortem cold ischemia on human tissue transcriptomes. Nat. Commun. 9, 490 (2018).
    • (2018) Nat. Commun. , vol.9
    • Ferreira, P.G.1
  • 63
    • 85031794820 scopus 로고    scopus 로고
    • Detecting activated cell populations using single-cell RNA-seq
    • COI: 1:CAS:528:DC%2BC2sXhs1GlsLbI, PID: 29024657
    • Wu, Y. E., Pan, L., Zuo, Y., Li, X. & Hong, W. Detecting activated cell populations using single-cell RNA-seq. Neuron 96, 313–329 (2017).
    • (2017) Neuron , vol.96 , pp. 313-329
    • Wu, Y.E.1    Pan, L.2    Zuo, Y.3    Li, X.4    Hong, W.5
  • 64
    • 85048936988 scopus 로고    scopus 로고
    • dropEst: pipeline for accurate estimation of molecular counts in droplet-based single-cell RNA-seq experiments
    • PID: 29921301
    • Petukhov, V. et al. dropEst: pipeline for accurate estimation of molecular counts in droplet-based single-cell RNA-seq experiments. Genome Biol. 19, 78 (2018).
    • (2018) Genome Biol. , vol.19
    • Petukhov, V.1
  • 65
    • 84958058589 scopus 로고    scopus 로고
    • Classification of low quality cells from single-cell RNA-seq data
    • PID: 26887813
    • Ilicic, T. et al. Classification of low quality cells from single-cell RNA-seq data. Genome Biol. 17, 29 (2016).
    • (2016) Genome Biol. , vol.17
    • Ilicic, T.1
  • 66
    • 85052908223 scopus 로고    scopus 로고
    • DoubletDecon: cell-state aware removal of single-cell RNA-seq doublets
    • Preprint at
    • DePasquale, E. A. K. et al. DoubletDecon: cell-state aware removal of single-cell RNA-seq doublets. Preprint at bioRxiv 10.1101/364810 (2018).
    • (2018) bioRxiv
    • DePasquale, E.A.K.1
  • 67
    • 85052881156 scopus 로고    scopus 로고
    • Scrublet: computational identification of cell doublets in single-cell transcriptomic data
    • Preprint at
    • Wolock, S. L., Lopez, R. & Klein, A. M. Scrublet: computational identification of cell doublets in single-cell transcriptomic data. Preprint at bioRxiv 10.1101/357368 (2018).
    • (2018) bioRxiv
    • Wolock, S.L.1    Lopez, R.2    Klein, A.M.3
  • 68
    • 85064579132 scopus 로고    scopus 로고
    • DoubletFinder: doublet detection in single-cell RNA sequencing data using artificial nearest neighbors
    • Preprint at
    • McGinnis, C. S., Murrow, L. M. & Gartner, Z. J. DoubletFinder: doublet detection in single-cell RNA sequencing data using artificial nearest neighbors. Preprint at bioRxiv 10.1101/352484 (2018).
    • (2018) bioRxiv
    • McGinnis, C.S.1    Murrow, L.M.2    Gartner, Z.J.3
  • 69
    • 85059492831 scopus 로고    scopus 로고
    • Comparison of clustering tools in R for medium-sized 10x Genomics single-cell RNA-sequencing data. [version 1; referees: 1 approved, 2 approved with reservations]
    • PID: 30228881
    • Freytag, S., Tian, L., Lönnstedt, I., Ng, M. & Bahlo, M. Comparison of clustering tools in R for medium-sized 10x Genomics single-cell RNA-sequencing data. [version 1; referees: 1 approved, 2 approved with reservations]. F1000Res 7, 1297 (2018).
    • (2018) F1000Res , vol.7 , pp. 1297
    • Freytag, S.1    Tian, L.2    Lönnstedt, I.3    Ng, M.4    Bahlo, M.5
  • 70
    • 84923292191 scopus 로고    scopus 로고
    • Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells
    • COI: 1:CAS:528:DC%2BC2MXhtFKjsLs%3D, PID: 25599176
    • Buettner, F. et al. Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells. Nat. Biotechnol. 33, 155–160 (2015).
    • (2015) Nat. Biotechnol. , vol.33 , pp. 155-160
    • Buettner, F.1
  • 71
    • 84939772971 scopus 로고    scopus 로고
    • Computational assignment of cell-cycle stage from single-cell transcriptome data
    • COI: 1:CAS:528:DC%2BC2MXhtF2kurjF, PID: 26142758
    • Scialdone, A. et al. Computational assignment of cell-cycle stage from single-cell transcriptome data. Methods 85, 54–61 (2015).
    • (2015) Methods , vol.85 , pp. 54-61
    • Scialdone, A.1
  • 72
    • 85016091925 scopus 로고    scopus 로고
    • Single-cell RNA-seq supports a developmental hierarchy in human oligodendroglioma
    • PID: 27806376
    • Tirosh, I. et al. Single-cell RNA-seq supports a developmental hierarchy in human oligodendroglioma. Nature 539, 309–313 (2016).
    • (2016) Nature , vol.539 , pp. 309-313
    • Tirosh, I.1
  • 73
    • 85048731044 scopus 로고    scopus 로고
    • Performance assessment and selection of normalization procedures for single-cell RNA-seq
    • Preprint at
    • Cole, M. B. et al. Performance assessment and selection of normalization procedures for single-cell RNA-seq. Preprint at bioRxiv 10.1101/235382 (2017).
    • (2017) bioRxiv
    • Cole, M.B.1
  • 74
    • 85009446777 scopus 로고    scopus 로고
    • Massively parallel digital transcriptional profiling of single cells
    • COI: 1:CAS:528:DC%2BC2sXht1WlsLo%3D, PID: 28091601
    • Zheng, G. X. Y. et al. Massively parallel digital transcriptional profiling of single cells. Nat. Commun. 8, 14049 (2017).
    • (2017) Nat. Commun. , vol.8
    • Zheng, G.X.Y.1
  • 75
    • 84976875133 scopus 로고    scopus 로고
    • GiniClust: detecting rare cell types from single-cell gene expression data with Gini index
    • PID: 27368803
    • Jiang, L., Chen, H., Pinello, L. & Yuan, G.-C. GiniClust: detecting rare cell types from single-cell gene expression data with Gini index. Genome Biol. 17, 144 (2016).
    • (2016) Genome Biol. , vol.17
    • Jiang, L.1    Chen, H.2    Pinello, L.3    Yuan, G.-C.4
  • 76
    • 85018582872 scopus 로고    scopus 로고
    • Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors
    • PID: 28428369, This study is a good example of how scRNA-seq was used to identify new cell types, which were subsequently confirmed by functional assays
    • Villani, A.-C. et al. Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors. Science 356, eaah4573 (2017). This study is a good example of how scRNA-seq was used to identify new cell types, which were subsequently confirmed by functional assays.
    • (2017) Science , vol.356 , pp. eaah4573
    • Villani, A.-C.1
  • 77
    • 85011634407 scopus 로고    scopus 로고
    • A molecular census of arcuate hypothalamus and median eminence cell types
    • COI: 1:CAS:528:DC%2BC2sXisV2kt7o%3D, PID: 28166221
    • Campbell, J. N. et al. A molecular census of arcuate hypothalamus and median eminence cell types. Nat. Neurosci. 20, 484–496 (2017).
    • (2017) Nat. Neurosci. , vol.20 , pp. 484-496
    • Campbell, J.N.1
  • 80
    • 84931072284 scopus 로고    scopus 로고
    • Identification of cell types from single-cell transcriptomes using a novel clustering method
    • COI: 1:CAS:528:DC%2BC28Xht1egu7fN, PID: 25805722
    • Xu, C. & Su, Z. Identification of cell types from single-cell transcriptomes using a novel clustering method. Bioinformatics 31, 1974–1980 (2015).
    • (2015) Bioinformatics , vol.31 , pp. 1974-1980
    • Xu, C.1    Su, Z.2
  • 81
    • 84922321862 scopus 로고    scopus 로고
    • Low-coverage single-cell mRNA sequencing reveals cellular heterogeneity and activated signaling pathways in developing cerebral cortex
    • COI: 1:CAS:528:DC%2BC2cXht1Gqt7zJ, PID: 25086649, This study shows that shallow sequencing can be sufficient to distinguish cell types
    • Pollen, A. A. et al. Low-coverage single-cell mRNA sequencing reveals cellular heterogeneity and activated signaling pathways in developing cerebral cortex. Nat. Biotechnol. 32, 1053–1058 (2014). This study shows that shallow sequencing can be sufficient to distinguish cell types.
    • (2014) Nat. Biotechnol. , vol.32 , pp. 1053-1058
    • Pollen, A.A.1
  • 82
    • 84947748539 scopus 로고    scopus 로고
    • Single cell RNA-sequencing of pluripotent states unlocks modular transcriptional variation
    • COI: 1:CAS:528:DC%2BC2MXhsFaqsbnO, PID: 26431182
    • Kolodziejczyk, A. A. et al. Single cell RNA-sequencing of pluripotent states unlocks modular transcriptional variation. Cell Stem Cell 17, 471–485 (2015).
    • (2015) Cell Stem Cell , vol.17 , pp. 471-485
    • Kolodziejczyk, A.A.1
  • 83
    • 84937703271 scopus 로고    scopus 로고
    • Single-cell RNA-seq transcriptome analysis of linear and circular RNAs in mouse preimplantation embryos
    • PID: 26201400
    • Fan, X. et al. Single-cell RNA-seq transcriptome analysis of linear and circular RNAs in mouse preimplantation embryos. Genome Biol. 16, 148 (2015).
    • (2015) Genome Biol. , vol.16
    • Fan, X.1
  • 84
    • 84992437479 scopus 로고    scopus 로고
    • In situ transcription profiling of single cells reveals spatial organization of cells in the mouse hippocampus
    • COI: 1:CAS:528:DC%2BC28XhslSqtr%2FM, PID: 27764670
    • Shah, S., Lubeck, E., Zhou, W. & Cai, L. In situ transcription profiling of single cells reveals spatial organization of cells in the mouse hippocampus. Neuron 92, 342–357 (2016).
    • (2016) Neuron , vol.92 , pp. 342-357
    • Shah, S.1    Lubeck, E.2    Zhou, W.3    Cai, L.4
  • 85
    • 84555189571 scopus 로고    scopus 로고
    • RNAscope: a novel in situ RNA analysis platform for formalin-fixed, paraffin-embedded tissues
    • COI: 1:CAS:528:DC%2BC38XhvVCrtL0%3D, PID: 22166544
    • Wang, F. et al. RNAscope: a novel in situ RNA analysis platform for formalin-fixed, paraffin-embedded tissues. J. Mol. Diagn. 14, 22–29 (2012).
    • (2012) J. Mol. Diagn. , vol.14 , pp. 22-29
    • Wang, F.1
  • 86
    • 84928395184 scopus 로고    scopus 로고
    • RNA imaging. Spatially resolved, highly multiplexed RNA profiling in single cells
    • PID: 25858977
    • Chen, K. H., Boettiger, A. N., Moffitt, J. R., Wang, S. & Zhuang, X. RNA imaging. Spatially resolved, highly multiplexed RNA profiling in single cells. Science 348, aaa6090 (2015).
    • (2015) Science , vol.348 , pp. aaa6090
    • Chen, K.H.1    Boettiger, A.N.2    Moffitt, J.R.3    Wang, S.4    Zhuang, X.5
  • 87
    • 84994641696 scopus 로고    scopus 로고
    • A single-cell transcriptomic map of the human and mouse pancreas reveals inter- and intra-cell population structure
    • COI: 1:CAS:528:DC%2BC2sXhtFalsrk%3D, PID: 27667365
    • Baron, M. et al. A single-cell transcriptomic map of the human and mouse pancreas reveals inter- and intra-cell population structure. Cell Syst. 3, 346–360 (2016).
    • (2016) Cell Syst. , vol.3 , pp. 346-360
    • Baron, M.1
  • 88
    • 84994589771 scopus 로고    scopus 로고
    • A single-cell transcriptome atlas of the human pancreas
    • COI: 1:CAS:528:DC%2BC2sXhtFamu74%3D, PID: 27693023
    • Muraro, M. J. et al. A single-cell transcriptome atlas of the human pancreas. Cell Syst. 3, 385–394 (2016).
    • (2016) Cell Syst. , vol.3 , pp. 385-394
    • Muraro, M.J.1
  • 89
    • 84989205113 scopus 로고    scopus 로고
    • Single-cell transcriptomics of the human endocrine pancreas
    • COI: 1:CAS:528:DC%2BC28XhvFOrtL7M, PID: 5033269
    • Wang, Y. J. et al. Single-cell transcriptomics of the human endocrine pancreas. Diabetes 65, 3028–3038 (2016).
    • (2016) Diabetes , vol.65 , pp. 3028-3038
    • Wang, Y.J.1
  • 90
    • 84992364302 scopus 로고    scopus 로고
    • Single-cell transcriptome profiling of human pancreatic islets in health and type 2 diabetes
    • COI: 1:CAS:528:DC%2BC28XhsFGru7zN, PID: 27667667
    • Segerstolpe, Å. et al. Single-cell transcriptome profiling of human pancreatic islets in health and type 2 diabetes. Cell Metab. 24, 593–607 (2016).
    • (2016) Cell Metab. , vol.24 , pp. 593-607
    • Segerstolpe, Å.1
  • 91
    • 84992427889 scopus 로고    scopus 로고
    • RNA sequencing of single human islet cells reveals type 2 diabetes genes
    • COI: 1:CAS:528:DC%2BC28XhsFGru7%2FN, PID: 27667665
    • Xin, Y. et al. RNA sequencing of single human islet cells reveals type 2 diabetes genes. Cell Metab. 24, 608–615 (2016).
    • (2016) Cell Metab. , vol.24 , pp. 608-615
    • Xin, Y.1
  • 92
    • 85046289245 scopus 로고    scopus 로고
    • scmap: projection of single-cell RNA-seq data across data sets
    • COI: 1:CAS:528:DC%2BC1cXmslKrurw%3D, PID: 29608555
    • Kiselev, V. Y., Yiu, A. & Hemberg, M. scmap: projection of single-cell RNA-seq data across data sets. Nat. Methods 15, 359–362 (2018).
    • (2018) Nat. Methods , vol.15 , pp. 359-362
    • Kiselev, V.Y.1    Yiu, A.2    Hemberg, M.3
  • 93
    • 85042801480 scopus 로고    scopus 로고
    • Characterizing the replicability of cell types defined by single cell RNA-sequencing data using MetaNeighbor
    • PID: 29491377, References 92 and 93 present methods for comparing clusters across data sets without merging
    • Crow, M., Paul, A., Ballouz, S., Huang, Z. J. & Gillis, J. Characterizing the replicability of cell types defined by single cell RNA-sequencing data using MetaNeighbor. Nat. Commun. 9, 884 (2018). References 92 and 93 present methods for comparing clusters across data sets without merging.
    • (2018) Nat. Commun. , vol.9
    • Crow, M.1    Paul, A.2    Ballouz, S.3    Huang, Z.J.4    Gillis, J.5
  • 94
    • 0034069495 scopus 로고    scopus 로고
    • Gene ontology: tool for the unification of biology
    • COI: 1:CAS:528:DC%2BD3cXjtFSlsbc%3D, PID: 3037419
    • Ashburner, M. et al. Gene ontology: tool for the unification of biology. Nat. Genet. 25, 25–29 (2000).
    • (2000) Nat. Genet. , vol.25 , pp. 25-29
    • Ashburner, M.1
  • 95
    • 85064579405 scopus 로고    scopus 로고
    • CellFishing.jl: an ultrafast and scalable cell search method for single-cell RNA-sequencing
    • Preprint at
    • Sato, K., Tsuyuzaki, K., Shimizu, K. & Nikaido, I. CellFishing.jl: an ultrafast and scalable cell search method for single-cell RNA-sequencing. Preprint at bioRxiv 10.1101/374462 (2018).
    • (2018) bioRxiv
    • Sato, K.1    Tsuyuzaki, K.2    Shimizu, K.3    Nikaido, I.4
  • 96
    • 85050864655 scopus 로고    scopus 로고
    • CellAtlasSearch: a scalable search engine for single cells
    • PID: 29788498
    • Srivastava, D., Iyer, A., Kumar, V. & Sengupta, D. CellAtlasSearch: a scalable search engine for single cells. Nucleic Acids Res. 46, W141–W147 (2018).
    • (2018) Nucleic Acids Res. , vol.46 , pp. W141-W147
    • Srivastava, D.1    Iyer, A.2    Kumar, V.3    Sengupta, D.4
  • 97
    • 78650789238 scopus 로고    scopus 로고
    • Logical development of the cell ontology
    • PID: 21208450
    • Meehan, T. F. et al. Logical development of the cell ontology. BMC Bioinformatics 12, 6 (2011).
    • (2011) BMC Bioinformatics , vol.12
    • Meehan, T.F.1
  • 98
    • 85048609035 scopus 로고    scopus 로고
    • Cell type discovery using single-cell transcriptomics: implications for ontological representation
    • COI: 1:CAS:528:DC%2BC1cXitlGmtb7E, PID: 29590361
    • Aevermann, B. D. et al. Cell type discovery using single-cell transcriptomics: implications for ontological representation. Hum. Mol. Genet. 27, R40–R47 (2018).
    • (2018) Hum. Mol. Genet. , vol.27 , pp. R40-R47
    • Aevermann, B.D.1
  • 99
    • 85038899097 scopus 로고    scopus 로고
    • Cell type discovery and representation in the era of high-content single cell phenotyping
    • PID: 29322913
    • Bakken, T. et al. Cell type discovery and representation in the era of high-content single cell phenotyping. BMC Bioinformatics 18, 559 (2017).
    • (2017) BMC Bioinformatics , vol.18
    • Bakken, T.1
  • 100
    • 85048568809 scopus 로고    scopus 로고
    • A single-cell atlas of cell types, states, and other transcriptional patterns from nine regions of the adult mouse brain
    • Preprint at
    • Saunders, A. et al. A single-cell atlas of cell types, states, and other transcriptional patterns from nine regions of the adult mouse brain. Preprint at bioRxiv 10.1101/299081 (2018).
    • (2018) bioRxiv
    • Saunders, A.1
  • 101
    • 85032583384 scopus 로고    scopus 로고
    • SCENIC: single-cell regulatory network inference and clustering
    • COI: 1:CAS:528:DC%2BC2sXhs1aitL7P, PID: 28991892
    • Aibar, S. et al. SCENIC: single-cell regulatory network inference and clustering. Nat. Methods 14, 1083–1086 (2017).
    • (2017) Nat. Methods , vol.14 , pp. 1083-1086
    • Aibar, S.1
  • 102
    • 84942940566 scopus 로고    scopus 로고
    • Defining cell types and states with single-cell genomics
    • COI: 1:CAS:528:DC%2BC2MXhs1Oitb%2FK, PID: 26430159
    • Trapnell, C. Defining cell types and states with single-cell genomics. Genome Res. 25, 1491–1498 (2015).
    • (2015) Genome Res. , vol.25 , pp. 1491-1498
    • Trapnell, C.1
  • 103
    • 85051624261 scopus 로고    scopus 로고
    • A revised airway epithelial hierarchy includes CFTR-expressing ionocytes
    • COI: 1:CAS:528:DC%2BC1cXhsVensrjJ, PID: 30069044
    • Montoro, D. T. et al. A revised airway epithelial hierarchy includes CFTR-expressing ionocytes. Nature 560, 319–324 (2018).
    • (2018) Nature , vol.560 , pp. 319-324
    • Montoro, D.T.1
  • 104
    • 85051647983 scopus 로고    scopus 로고
    • A single-cell atlas of the airway epithelium reveals the CFTR-rich pulmonary ionocyte
    • COI: 1:CAS:528:DC%2BC1cXhsVensrnM, PID: 30069046
    • Plasschaert, L. W. et al. A single-cell atlas of the airway epithelium reveals the CFTR-rich pulmonary ionocyte. Nature 560, 377–381 (2018).
    • (2018) Nature , vol.560 , pp. 377-381
    • Plasschaert, L.W.1
  • 105
    • 85034642667 scopus 로고    scopus 로고
    • Construction of developmental lineage relationships in the mouse mammary gland by single-cell RNA profiling
    • PID: 29158510
    • Pal, B. et al. Construction of developmental lineage relationships in the mouse mammary gland by single-cell RNA profiling. Nat. Commun. 8, 1627 (2017).
    • (2017) Nat. Commun. , vol.8
    • Pal, B.1
  • 106
    • 85046653336 scopus 로고    scopus 로고
    • Single cell multi-omics technology: methodology and application
    • PID: 29732369
    • Hu, Y. et al. Single cell multi-omics technology: methodology and application. Front. Cell Dev. Biol. 6, 28 (2018).
    • (2018) Front. Cell Dev. Biol. , vol.6 , pp. 28
    • Hu, Y.1
  • 107
    • 84969504939 scopus 로고    scopus 로고
    • Multi-omics of single cells: strategies and applications
    • COI: 1:CAS:528:DC%2BC28XmslSgurc%3D, PID: 27212022
    • Bock, C., Farlik, M. & Sheffield, N. C. Multi-omics of single cells: strategies and applications. Trends Biotechnol. 34, 605–608 (2016).
    • (2016) Trends Biotechnol. , vol.34 , pp. 605-608
    • Bock, C.1    Farlik, M.2    Sheffield, N.C.3
  • 108
    • 85009781625 scopus 로고    scopus 로고
    • Single-cell multiomics: multiple measurements from single cells
    • COI: 1:CAS:528:DC%2BC2sXlt12ktQ%3D%3D, PID: 28089370
    • Macaulay, I. C., Ponting, C. P. & Voet, T. Single-cell multiomics: multiple measurements from single cells. Trends Genet. 33, 155–168 (2017).
    • (2017) Trends Genet. , vol.33 , pp. 155-168
    • Macaulay, I.C.1    Ponting, C.P.2    Voet, T.3
  • 109
    • 84872522528 scopus 로고    scopus 로고
    • Latent enhancers activated by stimulation in differentiated cells
    • COI: 1:CAS:528:DC%2BC3sXht1ygtbo%3D, PID: 23332752
    • Ostuni, R. et al. Latent enhancers activated by stimulation in differentiated cells. Cell 152, 157–171 (2013).
    • (2013) Cell , vol.152 , pp. 157-171
    • Ostuni, R.1
  • 110
    • 85047617654 scopus 로고    scopus 로고
    • Tracing the temporal-spatial transcriptome landscapes of the human fetal digestive tract using single-cell RNA-sequencing
    • COI: 1:CAS:528:DC%2BC1cXhtVaisLnO, PID: 29802404
    • Gao, S. et al. Tracing the temporal-spatial transcriptome landscapes of the human fetal digestive tract using single-cell RNA-sequencing. Nat. Cell Biol. 20, 721–734 (2018).
    • (2018) Nat. Cell Biol. , vol.20 , pp. 721-734
    • Gao, S.1
  • 111
    • 85045437597 scopus 로고    scopus 로고
    • Identification of spatial expression trends in single-cell gene expression data
    • PID: 29553578
    • Edsgärd, D., Johnsson, P. & Sandberg, R. Identification of spatial expression trends in single-cell gene expression data. Nat. Methods 15, 339–342 (2018).
    • (2018) Nat. Methods , vol.15 , pp. 339-342
    • Edsgärd, D.1    Johnsson, P.2    Sandberg, R.3
  • 112
    • 85057943596 scopus 로고    scopus 로고
    • Building a tumor atlas: integrating single-cell RNA-Seq data with spatial transcriptomics in pancreatic ductal adenocarcinoma
    • Preprint at
    • Moncada, R. et al. Building a tumor atlas: integrating single-cell RNA-Seq data with spatial transcriptomics in pancreatic ductal adenocarcinoma. Preprint at bioRxiv 10.1101/254375 (2018).
    • (2018) bioRxiv
    • Moncada, R.1
  • 113
    • 85044604944 scopus 로고    scopus 로고
    • Comprehensive identification and spatial mapping of habenular neuronal types using single-cell RNA-seq
    • COI: 1:CAS:528:DC%2BC1cXlvVOhtbc%3D, PID: 29576475
    • Pandey, S., Shekhar, K., Regev, A. & Schier, A. F. Comprehensive identification and spatial mapping of habenular neuronal types using single-cell RNA-seq. Curr. Biol. 28, 1052–1065 (2018).
    • (2018) Curr. Biol. , vol.28 , pp. 1052-1065
    • Pandey, S.1    Shekhar, K.2    Regev, A.3    Schier, A.F.4
  • 114
    • 84966667709 scopus 로고    scopus 로고
    • destiny: diffusion maps for large-scale single-cell data in R
    • COI: 1:CAS:528:DC%2BC28XhtlGqurvE
    • Angerer, P. et al. destiny: diffusion maps for large-scale single-cell data in R. Bioinformatics 32, 1241–1243 (2016).
    • (2016) Bioinformatics , vol.32 , pp. 1241-1243
    • Angerer, P.1
  • 115
    • 84990895380 scopus 로고    scopus 로고
    • De novo prediction of stem cell identity using single-cell transcriptome data
    • PID: 27345837
    • Grün, D. et al. De novo prediction of stem cell identity using single-cell transcriptome data. Cell Stem Cell 19, 266–277 (2016).
    • (2016) Cell Stem Cell , vol.19 , pp. 266-277
    • Grün, D.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.