메뉴 건너뛰기




Volumn 177, Issue 7, 2019, Pages 1888-1902.e21

Comprehensive Integration of Single-Cell Data

Author keywords

integration; multi modal; scATAC seq; scRNA seq; single cell; single cell ATAC sequencing; single cell RNA sequencing

Indexed keywords

ARTICLE; BONE MARROW CELL; EPIGENETICS; GENE EXPRESSION; HUMAN; IMMUNOPHENOTYPING; INTERNEURON; LYMPHOCYTE SUBPOPULATION; MARKER GENE; NONHUMAN; PANCREAS ISLET CELL; PRIORITY JOURNAL; PROTEIN EXPRESSION; PROTEOMICS; RNA SEQUENCE; SINGLE CELL ANALYSIS; TRANSCRIPTOMICS; GENE EXPRESSION PROFILING; NUCLEIC ACID DATABASE; SEQUENCE ANALYSIS; SOFTWARE;

EID: 85066448459     PISSN: 00928674     EISSN: 10974172     Source Type: Journal    
DOI: 10.1016/j.cell.2019.05.031     Document Type: Article
Times cited : (8581)

References (103)
  • 3
    • 85066927830 scopus 로고    scopus 로고
    • Allen Brain Data Portal.
    • Allen Institute. 2018. Allen Brain Data Portal. http://celltypes.brain-map.org/api/v2/well_known_file_download/694413985.
    • (2018)
    • Allen Institute1
  • 4
    • 85066926463 scopus 로고    scopus 로고
    • Fast Nearest Neighbour Search (Wraps ANN Library) Using L2 Metric.
    • Arya, S., Mount, D., Kemp, S.E., and Jefferis, G. (2018). RANN: Fast Nearest Neighbour Search (Wraps ANN Library) Using L2 Metric. https://cran.r-project.org/web/packages/RANN/index.html.
    • (2018)
    • Arya, S.1    Mount, D.2    Kemp, S.E.3    Jefferis, G.R.4
  • 5
    • 85066927024 scopus 로고    scopus 로고
    • 2018. irlba: Fast Truncated Singular Value Decomposition and Principal Components Analysis for Large Dense and Sparse Matrices.
    • Baglama, J., Reichel, L., and Lewis, B.W. 2018. irlba: Fast Truncated Singular Value Decomposition and Principal Components Analysis for Large Dense and Sparse Matrices. https://cran.r-project.org/web/packages/irlba/index.html.
    • Baglama, J.1    Reichel, L.2    Lewis, B.W.3
  • 7
    • 70450203033 scopus 로고    scopus 로고
    • mixtools: An R Package for Analyzing Finite Mixture Models
    • Benaglia, T., Chauveau, D., Hunter, D.R., Young, D.S., mixtools: An R Package for Analyzing Finite Mixture Models. J. Stat. Softw. 32 (2009), 1–29.
    • (2009) J. Stat. Softw. , vol.32 , pp. 1-29
    • Benaglia, T.1    Chauveau, D.2    Hunter, D.R.3    Young, D.S.4
  • 9
    • 80053342456 scopus 로고    scopus 로고
    • Domain adaptation with structural correspondence learning. Proc. Conf. Empir
    • Blitzer, J., McDonald, R., Pereira, F., Domain adaptation with structural correspondence learning. Proc. Conf. Empir. Methods Nat. Lang. Process., 2006, 120–128.
    • (2006) Methods Nat. Lang. Process. , pp. 120-128
    • Blitzer, J.1    McDonald, R.2    Pereira, F.3
  • 10
    • 85046298440 scopus 로고    scopus 로고
    • Integrating single-cell transcriptomic data across different conditions, technologies, and species
    • Butler, A., Hoffman, P., Smibert, P., Papalexi, E., Satija, R., Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat. Biotechnol. 36 (2018), 411–420.
    • (2018) Nat. Biotechnol. , vol.36 , pp. 411-420
    • Butler, A.1    Hoffman, P.2    Smibert, P.3    Papalexi, E.4    Satija, R.5
  • 11
    • 85046700621 scopus 로고    scopus 로고
    • Assessment of batch-correction methods for scRNA-seq data with a new test metric
    • Büttner, M., Miao, Z., Wolf, F.A., Teichmann, S.A., Theis, F.J., Assessment of batch-correction methods for scRNA-seq data with a new test metric. bioRxiv, 2017, 10.1101/200345.
    • (2017) bioRxiv
    • Büttner, M.1    Miao, Z.2    Wolf, F.A.3    Teichmann, S.A.4    Theis, F.J.5
  • 16
    • 84908137383 scopus 로고    scopus 로고
    • Impact of interferon-γ on hematopoiesis
    • de Bruin, A.M., Voermans, C., Nolte, M.A., Impact of interferon-γ on hematopoiesis. Blood 124 (2014), 2479–2486.
    • (2014) Blood , vol.124 , pp. 2479-2486
    • de Bruin, A.M.1    Voermans, C.2    Nolte, M.A.3
  • 19
    • 0036489046 scopus 로고    scopus 로고
    • Comparison of discrimination methods for the classification of tumors using gene expression data
    • Dudoit, S., Fridlyans, J., Speed, T.P., Comparison of discrimination methods for the classification of tumors using gene expression data. J. Am. Stat. Assoc. 97 (2002), 77–87.
    • (2002) J. Am. Stat. Assoc. , vol.97 , pp. 77-87
    • Dudoit, S.1    Fridlyans, J.2    Speed, T.P.3
  • 20
    • 33846689706 scopus 로고    scopus 로고
    • Using GOstats to test gene lists for GO term association
    • Falcon, S., Gentleman, R., Using GOstats to test gene lists for GO term association. Bioinformatics 23 (2007), 257–258.
    • (2007) Bioinformatics , vol.23 , pp. 257-258
    • Falcon, S.1    Gentleman, R.2
  • 21
    • 0023084055 scopus 로고
    • Progressive sequence alignment as a prerequisite to correct phylogenetic trees
    • Feng, D.-F., Doolittle, R.F., Progressive sequence alignment as a prerequisite to correct phylogenetic trees. J. Mol. Evol. 25 (1987), 351–360.
    • (1987) J. Mol. Evol. , vol.25 , pp. 351-360
    • Feng, D.-F.1    Doolittle, R.F.2
  • 24
    • 85066928572 scopus 로고    scopus 로고
    • Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression
    • Hafemeister, C., Satija, R., Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression. bioRxiv, 2019, 10.1101/576827.
    • (2019) bioRxiv
    • Hafemeister, C.1    Satija, R.2
  • 25
    • 85046289733 scopus 로고    scopus 로고
    • Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors
    • 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 (2018), 421–427.
    • (2018) Nat. Biotechnol. , vol.36 , pp. 421-427
    • Haghverdi, L.1    Lun, A.T.L.2    Morgan, M.D.3    Marioni, J.C.4
  • 26
    • 84973315339 scopus 로고    scopus 로고
    • Statistical Genomics: Methods and Protocols. Springer New York, New York
    • Ch. Visualizing Genomic Data Using Gviz and Bioconductor NY
    • Hahne, F., Ivanek, R., Statistical Genomics: Methods and Protocols. Springer New York, New York. 2016, Ch. Visualizing Genomic Data Using Gviz and Bioconductor, NY, 335–351.
    • (2016) , pp. 335-351
    • Hahne, F.1    Ivanek, R.2
  • 28
    • 77952567987 scopus 로고    scopus 로고
    • Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities
    • Heinz, S., Benner, C., Spann, N., Bertolino, E., Lin, Y.C., Laslo, P., Cheng, J.X., Murre, C., Singh, H., Glass, C.K., Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38 (2010), 576–589.
    • (2010) Mol. Cell , vol.38 , pp. 576-589
    • Heinz, S.1    Benner, C.2    Spann, N.3    Bertolino, E.4    Lin, Y.C.5    Laslo, P.6    Cheng, J.X.7    Murre, C.8    Singh, H.9    Glass, C.K.10
  • 29
    • 85065343062 scopus 로고    scopus 로고
    • Efficient integration of heterogeneous single-cell transcriptomes using Scanorama
    • Hie, B., Bryson, B., Berger, B., Efficient integration of heterogeneous single-cell transcriptomes using Scanorama. Nat. Biotechnol., 2019.
    • (2019) Nat. Biotechnol.
    • Hie, B.1    Bryson, B.2    Berger, B.3
  • 31
    • 85030630310 scopus 로고    scopus 로고
    • Single-cell epigenomics: Recording the past and predicting the future
    • Kelsey, G., Stegle, O., Reik, W., Single-cell epigenomics: Recording the past and predicting the future. Science 358 (2017), 69–75.
    • (2017) Science , vol.358 , pp. 69-75
    • Kelsey, G.1    Stegle, O.2    Reik, W.3
  • 32
    • 85052874515 scopus 로고    scopus 로고
    • A Structured Tumor-Immune Microenvironment in Triple Negative Breast Cancer Revealed by Multiplexed Ion Beam Imaging
    • Keren, L., Bosse, M., Marquez, D., Angoshtari, R., Jain, S., Varma, S., Yang, S.R., Kurian, A., Van Valen, D., West, R., et al. A Structured Tumor-Immune Microenvironment in Triple Negative Breast Cancer Revealed by Multiplexed Ion Beam Imaging. Cell 174 (2018), 1373–1387.
    • (2018) Cell , vol.174 , pp. 1373-1387
    • Keren, L.1    Bosse, M.2    Marquez, D.3    Angoshtari, R.4    Jain, S.5    Varma, S.6    Yang, S.R.7    Kurian, A.8    Van Valen, D.9    West, R.10
  • 33
    • 85046289245 scopus 로고    scopus 로고
    • scmap: projection of single-cell RNA-seq data across data sets
    • Kiselev, V.Y., Yiu, A., Hemberg, M., scmap: projection of single-cell RNA-seq data across data sets. Nat. Methods 15 (2018), 359–362.
    • (2018) Nat. Methods , vol.15 , pp. 359-362
    • Kiselev, V.Y.1    Yiu, A.2    Hemberg, M.3
  • 35
    • 60549111634 scopus 로고    scopus 로고
    • WGCNA: an R package for weighted correlation network analysis
    • Langfelder, P., Horvath, S., WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics, 9, 2008, 559.
    • (2008) BMC Bioinformatics , vol.9 , pp. 559
    • Langfelder, P.1    Horvath, S.2
  • 36
    • 62349130698 scopus 로고    scopus 로고
    • Ultrafast and memory-efficient alignment of short DNA sequences to the human genome
    • Langmead, B., Trapnell, C., Pop, M., Salzberg, S.L., Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol., 10, 2009, R25.
    • (2009) Genome Biol. , vol.10 , pp. R25
    • Langmead, B.1    Trapnell, C.2    Pop, M.3    Salzberg, S.L.4
  • 38
    • 85012994420 scopus 로고    scopus 로고
    • Single-cell transcriptomes identify human islet cell signatures and reveal cell-type-specific expression changes in type 2 diabetes
    • Lawlor, N., George, J., Bolisetty, M., Kursawe, R., Sun, L., Sivakamasundari, V., Kycia, I., Robson, P., Stitzel, M.L., Single-cell transcriptomes identify human islet cell signatures and reveal cell-type-specific expression changes in type 2 diabetes. Genome Res. 27 (2017), 208–222.
    • (2017) Genome Res. , vol.27 , pp. 208-222
    • Lawlor, N.1    George, J.2    Bolisetty, M.3    Kursawe, R.4    Sun, L.5    Sivakamasundari, V.6    Kycia, I.7    Robson, P.8    Stitzel, M.L.9
  • 43
    • 85066923324 scopus 로고    scopus 로고
    • Data and code availability
    • Linnarsson, S. 2018. Data and code availability. http://linnarssonlab.org/osmFISH/availability.
    • (2018)
    • Linnarsson, S.1
  • 44
    • 85057586270 scopus 로고    scopus 로고
    • Deep generative modeling for single-cell transcriptomics
    • Lopez, R., Regier, J., Cole, M.B., Jordan, M.I., Yosef, N., Deep generative modeling for single-cell transcriptomics. Nat. Methods 15 (2018), 1053–1058.
    • (2018) Nat. Methods , vol.15 , pp. 1053-1058
    • Lopez, R.1    Regier, J.2    Cole, M.B.3    Jordan, M.I.4    Yosef, N.5
  • 45
    • 84924629414 scopus 로고    scopus 로고
    • Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
    • Love, M.I., Huber, W., Anders, S., Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol., 15, 2014, 550.
    • (2014) Genome Biol. , vol.15 , pp. 550
    • Love, M.I.1    Huber, W.2    Anders, S.3
  • 46
    • 85010931059 scopus 로고    scopus 로고
    • A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor
    • 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. F1000Res., 5, 2016, 2122.
    • (2016) F1000Res. , vol.5 , pp. 2122
    • Lun, A.T.L.1    McCarthy, D.J.2    Marioni, J.C.3
  • 50
    • 85066961510 scopus 로고    scopus 로고
    • A Library for Approximate Nearest Neighbor Searching.
    • Mount, D.M., and Arya, S. (2010). ANN: A Library for Approximate Nearest Neighbor Searching. http://www.cs.umd.edu/∼mount/ANN/.
    • (2010)
    • Mount, D.M.1    Arya, S.A.2
  • 54
    • 85060474248 scopus 로고    scopus 로고
    • A discriminative learning approach to differential expression analysis for single-cell RNA-seq
    • Ntranos, V., Yi, L., Melsted, P., Pachter, L., A discriminative learning approach to differential expression analysis for single-cell RNA-seq. Nat. Methods 16 (2019), 163–166.
    • (2019) Nat. Methods , vol.16 , pp. 163-166
    • Ntranos, V.1    Yi, L.2    Melsted, P.3    Pachter, L.4
  • 56
    • 1042304216 scopus 로고    scopus 로고
    • APE: Analyses of phylogenetics and evolution in R language
    • Paradis, E., Claude, J., Strimmer, K., APE: Analyses of phylogenetics and evolution in R language. Bioinformatics 20 (2004), 289–290.
    • (2004) Bioinformatics , vol.20 , pp. 289-290
    • Paradis, E.1    Claude, J.2    Strimmer, K.3
  • 59
    • 85041914298 scopus 로고    scopus 로고
    • Single-nucleus analysis of accessible chromatin in developing mouse forebrain reveals cell-type-specific transcriptional regulation
    • Preissl, S., Fang, R., Huang, H., Zhao, Y., Raviram, R., Gorkin, D.U., Zhang, Y., Sos, B.C., Afzal, V., Dickel, D.E., et al. Single-nucleus analysis of accessible chromatin in developing mouse forebrain reveals cell-type-specific transcriptional regulation. Nat. Neurosci. 21 (2018), 432–439.
    • (2018) Nat. Neurosci. , vol.21 , pp. 432-439
    • Preissl, S.1    Fang, R.2    Huang, H.3    Zhao, Y.4    Raviram, R.5    Gorkin, D.U.6    Zhang, Y.7    Sos, B.C.8    Afzal, V.9    Dickel, D.E.10
  • 61
    • 77951770756 scopus 로고    scopus 로고
    • BEDTools: a flexible suite of utilities for comparing genomic features
    • Quinlan, A.R., Hall, I.M., BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26 (2010), 841–842.
    • (2010) Bioinformatics , vol.26 , pp. 841-842
    • Quinlan, A.R.1    Hall, I.M.2
  • 62
    • 34547971961 scopus 로고    scopus 로고
    • Self-taught Learning: Transfer Learning from Unlabeled Data. Proc. Int. Conf
    • Raina, R., Battle, A., Lee, H., Packer, B., Ng, A.Y., Self-taught Learning: Transfer Learning from Unlabeled Data. Proc. Int. Conf. Mach. Learn, 2007, 759–766.
    • (2007) Mach. Learn , pp. 759-766
    • Raina, R.1    Battle, A.2    Lee, H.3    Packer, B.4    Ng, A.Y.5
  • 67
    • 0023453329 scopus 로고
    • Silhouettes: A graphical aid to the interpretation and validation of cluster analysis
    • Rousseeuw, P.J., Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. J. Comput. Appl. Math. 20 (1987), 53–65.
    • (1987) J. Comput. Appl. Math. , vol.20 , pp. 53-65
    • Rousseeuw, P.J.1
  • 70
    • 85056285806 scopus 로고    scopus 로고
    • Barcoded Plate-Based Single Cell RNA-seq
    • Satija Lab. Barcoded Plate-Based Single Cell RNA-seq. Protocols.io, 2018, 10.17504/protocols.io.nkgdctw.
    • (2018) Protocols.io
  • 73
    • 85066952419 scopus 로고    scopus 로고
    • The Tabula Muris Consortium. Single-cell RNA-seq data from Smart-seq2 sequencing of FACS sorted cells.
    • The Tabula Muris Consortium. (2017). Single-cell RNA-seq data from Smart-seq2 sequencing of FACS sorted cells. https://figshare.com/articles/Single-cell_RNA-seq_data_from_Smart-seq2_sequencing_of_FACS_sorted_cells/5715040.
    • (2017)
  • 74
    • 85066956797 scopus 로고    scopus 로고
    • The Tabula Muris Consortium. (2018a). Single-cell RNA-seq data from microfluidic emulsion.
    • The Tabula Muris Consortium. (2018a). Single-cell RNA-seq data from microfluidic emulsion. https://figshare.com/articles/Single-cell_RNA-seq_data_from_microfluidic_emulsion_v2_/5968960.
  • 75
    • 85055080981 scopus 로고    scopus 로고
    • Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris
    • The Tabula Muris Consortium. Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris. Nature 562 (2018), 367–372.
    • (2018) Nature , vol.562 , pp. 367-372
  • 81
  • 82
    • 0042424602 scopus 로고    scopus 로고
    • Statistical significance for genomewide studies
    • Storey, J.D., Tibshirani, R., Statistical significance for genomewide studies. Proc. Natl. Acad. Sci. USA 100 (2003), 9440–9445.
    • (2003) Proc. Natl. Acad. Sci. USA , vol.100 , pp. 9440-9445
    • Storey, J.D.1    Tibshirani, R.2
  • 83
    • 85060917516 scopus 로고    scopus 로고
    • Integrative single-cell analysis
    • Stuart, T., Satija, R., Integrative single-cell analysis. Nat. Rev. Genet 20 (2019), 257–272.
    • (2019) Nat. Rev. Genet , vol.20 , pp. 257-272
    • Stuart, T.1    Satija, R.2
  • 85
    • 85044252958 scopus 로고    scopus 로고
    • Exponential scaling of single-cell RNA-seq in the past decade
    • Svensson, V., Vento-Tormo, R., Teichmann, S.A., Exponential scaling of single-cell RNA-seq in the past decade. Nat. Protoc. 13 (2018), 599–604.
    • (2018) Nat. Protoc. , vol.13 , pp. 599-604
    • Svensson, V.1    Vento-Tormo, R.2    Teichmann, S.A.3
  • 86
    • 0242363120 scopus 로고    scopus 로고
    • Expression of T cell receptor beta locus in central nervous system neurons
    • Syken, J., Shatz, C.J., Expression of T cell receptor beta locus in central nervous system neurons. Proc. Natl. Acad. Sci. USA 100 (2003), 13048–13053.
    • (2003) Proc. Natl. Acad. Sci. USA , vol.100 , pp. 13048-13053
    • Syken, J.1    Shatz, C.J.2
  • 87
    • 85017360311 scopus 로고    scopus 로고
    • Scaling single-cell genomics from phenomenology to mechanism
    • Tanay, A., Regev, A., Scaling single-cell genomics from phenomenology to mechanism. Nature 541 (2017), 331–338.
    • (2017) Nature , vol.541 , pp. 331-338
    • Tanay, A.1    Regev, A.2
  • 90
    • 0024390970 scopus 로고
    • T cell activation via Leu-23 (CD69)
    • Testi, R., Phillips, J.H., Lanier, L.L., T cell activation via Leu-23 (CD69). J. Immunol. 143 (1989), 1123–1128.
    • (1989) J. Immunol. , vol.143 , pp. 1123-1128
    • Testi, R.1    Phillips, J.H.2    Lanier, L.L.3
  • 91
    • 2342533421 scopus 로고    scopus 로고
    • Class prediction by nearest shrunken centroids, with applications to DNA microarrays
    • Tibshirani, R., Hastie, T., Narasimhan, B., Chu, G., Class prediction by nearest shrunken centroids, with applications to DNA microarrays. Stat. Sci. 18 (2003), 104–117.
    • (2003) Stat. Sci. , vol.18 , pp. 104-117
    • Tibshirani, R.1    Hastie, T.2    Narasimhan, B.3    Chu, G.4
  • 93
    • 65449136284 scopus 로고    scopus 로고
    • TopHat: discovering splice junctions with RNA-Seq
    • Trapnell, C., Pachter, L., Salzberg, S.L., TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 25 (2009), 1105–1111.
    • (2009) Bioinformatics , vol.25 , pp. 1105-1111
    • Trapnell, C.1    Pachter, L.2    Salzberg, S.L.3
  • 95
    • 84994807494 scopus 로고    scopus 로고
    • Differential expression of mGluR2 in the developing cerebral cortex of the mouse
    • Venkatadri, P.S., Lee, C.C., Differential expression of mGluR2 in the developing cerebral cortex of the mouse. J. Biomed. Sci. Eng. 7 (2014), 1030–1037.
    • (2014) J. Biomed. Sci. Eng. , vol.7 , pp. 1030-1037
    • Venkatadri, P.S.1    Lee, C.C.2
  • 97
    • 84863261451 scopus 로고    scopus 로고
    • Heterogeneous Domain Adaptation Using Manifold Alignment
    • Wang, C., Mahadevan, S., Heterogeneous Domain Adaptation Using Manifold Alignment. Proc. Int. Joint Conf. Artif. Intell, 2010, 1541–1546.
    • (2010) Proc. Int. Joint Conf. Artif. Intell , pp. 1541-1546
    • Wang, C.1    Mahadevan, S.2
  • 100
    • 85066449186 scopus 로고    scopus 로고
    • Single-Cell Multi-omic Integration Compares and Contrasts Features of Brain Cell Identity
    • this issue
    • Welch, J.D., Kozareva, V., Ferreira, A., Vanderburg, C., Martin, C., Macosko, E.Z., Single-Cell Multi-omic Integration Compares and Contrasts Features of Brain Cell Identity. Cell 177 (2019), 1873–1887 this issue.
    • (2019) Cell , vol.177 , pp. 1873-1887
    • Welch, J.D.1    Kozareva, V.2    Ferreira, A.3    Vanderburg, C.4    Martin, C.5    Macosko, E.Z.6
  • 101
    • 70149096300 scopus 로고    scopus 로고
    • A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis
    • Witten, D.M., Tibshirani, R., Hastie, T., A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis. Biostatistics 10 (2009), 515–534.
    • (2009) Biostatistics , vol.10 , pp. 515-534
    • Witten, D.M.1    Tibshirani, R.2    Hastie, T.3
  • 102
    • 85064408983 scopus 로고    scopus 로고
    • Scrublet: Computational identification of cell doublets in Single-Cell transcriptomic data
    • Wolock, S.L., Lopez, R., Klein, A.M., Scrublet: Computational identification of cell doublets in Single-Cell transcriptomic data. Cell Syst. 8 (2019), 281–291.
    • (2019) Cell Syst. , vol.8 , pp. 281-291
    • Wolock, S.L.1    Lopez, R.2    Klein, A.M.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.