Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells

Cited by (200)

Items 101–200 of 200

1. Bacterial droplet-based single-cell RNA-seq reveals antibiotic-associated heterogeneous cellular states
   Ma, Peijun, Amemiya, Haley M., He, Lorrie L., Gandhi, Shivam J., Nicol, Robert, Bhattacharyya, Roby P., Smillie, Christopher S., Hung, Deborah T. · 2023 · Cell
2. A systematic performance evaluation of clustering methods for single-cell RNA-seq data
   Duò, Angelo, Robinson, Mark D., Soneson, Charlotte · 2018 · F1000Research
3. High-throughput, single-microbe genomics with strain resolution, applied to a human gut microbiome
   Zheng, Wenshan, Zhao, Shijie, Yin, Yehang, Zhang, Huidan, Needham, David M., Evans, Ethan D., Dai, Chengzhen L., Lu, Peter J., Alm, Eric J., Weitz, David A. · 2022 · Science
4. The promises and challenges of human brain organoids as models of neuropsychiatric disease
   Quadrato, Giorgia, Brown, Juliana, Arlotta, Paola · 2016 · Nature Medicine
5. Joint profiling of histone modifications and transcriptome in single cells from mouse brain
   Zhu, Chenxu, Zhang, Yanxiao, Li, Yang Eric, Lucero, Jacinta, Behrens, M. Margarita, Ren, Bing · 2021 · Nature Methods
6. Disentangling neural cell diversity using single-cell transcriptomics
   Poulin, Jean-Francois, Tasic, Bosiljka, Hjerling-Leffler, Jens, Trimarchi, Jeffrey M, Awatramani, Rajeshwar · 2016 · Nature Neuroscience
7. Challenges in measuring and understanding biological noise
   Eling, Nils, Morgan, Michael D., Marioni, John C. · 2019 · Nature Reviews Genetics
8. Using single-cell genomics to understand developmental processes and cell fate decisions
   Griffiths, Jonathan A, Scialdone, Antonio, Marioni, John C · 2018 · Molecular Systems Biology
9. Single-cell technologies in hepatology: new insights into liver biology and disease pathogenesis
   Ramachandran, Prakash, Matchett, Kylie P., Dobie, Ross, Wilson-Kanamori, John R., Henderson, Neil C. · 2020 · Nature Reviews Gastroenterology & Hepatology
10. Genome-wide base-resolution mapping of DNA methylation in single cells using single-cell bisulfite sequencing (scBS-seq)
    Clark, Stephen J, Smallwood, Sébastien A, Lee, Heather J, Krueger, Felix, Reik, Wolf, Kelsey, Gavin · 2017 · Nature Protocols
11. Single-Cell Analysis of the Liver Epithelium Reveals Dynamic Heterogeneity and an Essential Role for YAP in Homeostasis and Regeneration
    Pepe-Mooney, Brian J., Dill, Michael T., Alemany, Anna, Ordovas-Montanes, Jose, Matsushita, Yuki, Rao, Anuradha, Sen, Anushna, Miyazaki, Makoto, Anakk, Sayeepriyadarshini, Dawson, Paul A. et al. · 2019 · Cell Stem Cell
12. Molecular and anatomical organization of the dorsal raphe nucleus
    Huang, Kee Wui, Ochandarena, Nicole E, Philson, Adrienne C, Hyun, Minsuk, Birnbaum, Jaclyn E, Cicconet, Marcelo, Sabatini, Bernardo L · 2019 · eLife
13. On the design of CRISPR-based single-cell molecular screens
    Hill, Andrew J, McFaline-Figueroa, José L, Starita, Lea M, Gasperini, Molly J, Matreyek, Kenneth A, Packer, Jonathan, Jackson, Dana, Shendure, Jay, Trapnell, Cole · 2018 · Nature Methods
14. scSLAM-seq reveals core features of transcription dynamics in single cells
    Erhard, Florian, Baptista, Marisa A. P., Krammer, Tobias, Hennig, Thomas, Lange, Marius, Arampatzi, Panagiota, Jürges, Christopher S., Theis, Fabian J., Saliba, Antoine-Emmanuel, Dölken, Lars · 2019 · Nature
15. TCR Transgenic Mice Reveal Stepwise, Multi-site Acquisition of the Distinctive Fat-Treg Phenotype
    Li, Chaoran, DiSpirito, Joanna R., Zemmour, David, Spallanzani, Raul German, Kuswanto, Wilson, Benoist, Christophe, Mathis, Diane · 2018 · Cell
16. Single-cell transcriptome sequencing: recent advances and remaining challenges
    Liu, Serena, Trapnell, Cole · 2016 · F1000Research
17. Accuracy, robustness and scalability of dimensionality reduction methods for single-cell RNA-seq analysis
    Sun, Shiquan, Zhu, Jiaqiang, Ma, Ying, Zhou, Xiang · 2019 · Genome biology
18. Slide-tags enables single-nucleus barcoding for multimodal spatial genomics
    Russell, Andrew J. C., Weir, Jackson A., Nadaf, Naeem M., Shabet, Matthew, Kumar, Vipin, Kambhampati, Sandeep, Raichur, Ruth, Marrero, Giovanni J., Liu, Sophia, Balderrama, Karol S. et al. · 2024 · Nature
19. Tutorial: guidelines for the experimental design of single-cell RNA sequencing studies
    Lafzi, Atefeh, Moutinho, Catia, Picelli, Simone, Heyn, Holger · 2018 · Nature Protocols
20. Analytic Pearson residuals for normalization of single-cell RNA-seq UMI data
    Lause, Jan, Berens, Philipp, Kobak, Dmitry · 2021 · Genome Biology
21. Cell fixation and preservation for droplet-based single-cell transcriptomics
    Alles, Jonathan, Karaiskos, Nikos, Praktiknjo, Samantha D., Grosswendt, Stefanie, Wahle, Philipp, Ruffault, Pierre-Louis, Ayoub, Salah, Schreyer, Luisa, Boltengagen, Anastasiya, Birchmeier, Carmen et al. · 2017 · BMC Biology
22. Overcoming confounding plate effects in differential expression analyses of single-cell RNA-seq data
    Lun, Aaron T. L., Marioni, John C. · 2017 · Biostatistics
23. Genetic determinants of co-accessible chromatin regions in activated T cells across humans
    Gate, Rachel E., Cheng, Christine S., Aiden, Aviva P., Siba, Atsede, Tabaka, Marcin, Lituiev, Dmytro, Machol, Ido, Gordon, M. Grace, Subramaniam, Meena, Shamim, Muhammad et al. · 2018 · Nature Genetics
24. Using neural networks for reducing the dimensions of single-cell RNA-Seq data
    Lin, Chieh, Jain, Siddhartha, Kim, Hannah, Bar-Joseph, Ziv · 2017 · Nucleic Acids Research
25. Multiplexed single-cell transcriptional response profiling to define cancer vulnerabilities and therapeutic mechanism of action
    McFarland, James M., Paolella, Brenton R., Warren, Allison, Geiger-Schuller, Kathryn, Shibue, Tsukasa, Rothberg, Michael, Kuksenko, Olena, Colgan, William N., Jones, Andrew, Chambers, Emily et al. · 2020 · Nature Communications
26. Experimental Considerations for Single-Cell RNA Sequencing Approaches
    Nguyen, Quy H., Pervolarakis, Nicholas, Nee, Kevin, Kessenbrock, Kai · 2018 · Frontiers in Cell and Developmental Biology
27. NEBULA is a fast negative binomial mixed model for differential or co-expression analysis of large-scale multi-subject single-cell data
    He, Liang, Davila-Velderrain, Jose, Sumida, Tomokazu S., Hafler, David A., Kellis, Manolis, Kulminski, Alexander M. · 2021 · Communications Biology
28. Transcriptional Heterogeneity in Naive and Primed Human Pluripotent Stem Cells at Single-Cell Resolution
    Messmer, Tobias, von Meyenn, Ferdinand, Savino, Aurora, Santos, Fátima, Mohammed, Hisham, Lun, Aaron Tin Long, Marioni, John C., Reik, Wolf · 2019 · Cell Reports
29. scDeepSort: a pre-trained cell-type annotation method for single-cell transcriptomics using deep learning with a weighted graph neural network
    Shao, Xin, Yang, Haihong, Zhuang, Xiang, Liao, Jie, Yang, Penghui, Cheng, Junyun, Lu, Xiaoyan, Chen, Huajun, Fan, Xiaohui · 2021 · Nucleic Acids Research
30. Multimodal profiling of single-cell morphology, electrophysiology, and gene expression using Patch-seq
    Cadwell, Cathryn R, Scala, Federico, Li, Shuang, Livrizzi, Giulia, Shen, Shan, Sandberg, Rickard, Jiang, Xiaolong, Tolias, Andreas S · 2017 · Nature Protocols
31. Multiplexed, targeted profiling of single-cell proteomes and transcriptomes in a single reaction
    Genshaft, Alex S, Li, Shuqiang, Gallant, Caroline J., Darmanis, Spyros, Prakadan, Sanjay M., Ziegler, Carly G. K., Lundberg, Martin, Fredriksson, Simon, Hong, Joyce, Regev, Aviv et al. · 2016 · Genome Biology
32. Single-Cell Genomics: A Stepping Stone for Future Immunology Discoveries
    Giladi, Amir, Amit, Ido · 2018 · Cell
33. powsimR: power analysis for bulk and single cell RNA-seq experiments
    Vieth, Beate, Ziegenhain, Christoph, Parekh, Swati, Enard, Wolfgang, Hellmann, Ines · 2017 · Bioinformatics
34. Low Dimensionality in Gene Expression Data Enables the Accurate Extraction of Transcriptional Programs from Shallow Sequencing
    Heimberg, Graham, Bhatnagar, Rajat, El-Samad, Hana, Thomson, Matt · 2016 · Cell Systems
35. The evolving concept of cell identity in the single cell era
    Morris, Samantha A. · 2019 · Development
36. Fast and precise single-cell data analysis using a hierarchical autoencoder
    Tran, Duc, Nguyen, Hung, Tran, Bang, La Vecchia, Carlo, Luu, Hung N., Nguyen, Tin · 2021 · Nature Communications
37. Single-cell analysis reveals a close relationship between differentiating dopamine and subthalamic nucleus neuronal lineages
    Kee, Nigel, Volakakis, Nikolaos, Kirkeby, Agnete, Dahl, Lina, Storvall, Helena, Nolbrant, Sara, Lahti, Laura, Björklund, Åsa K., Gillberg, Linda, Joodmardi, Eliza et al. · 2017 · Cell stem cell
38. Single-cell RNA-seq uncovers a robust transcriptional response to morphine by glia
    Avey, Denis, Sankararaman, Sumithra, Yim, Aldrin K.Y., Barve, Ruteja, Milbrandt, Jeffrey, Mitra, Robi D. · 2018 · Cell Reports
39. Impact of similarity metrics on single-cell RNA-seq data clustering
    Kim, Taiyun, Chen, Irene Rui, Lin, Yingxin, Wang, Andy Yi-Yang, Yang, Jean Yee Hwa, Yang, Pengyi · 2019 · Briefings in Bioinformatics
40. Genetically Defined Syngeneic Mouse Models of Ovarian Cancer as Tools for the Discovery of Combination Immunotherapy
    Iyer, Sonia, Zhang, Shuang, Yucel, Simge, Horn, Heiko, Smith, Sean G., Reinhardt, Ferenc, Hoefsmit, Esmee, Assatova, Bimarzhan, Casado, Julia, Meinsohn, Marie-Charlotte et al. · 2021 · Cancer Discovery
41. A scalable platform for the development of cell-type-specific viral drivers
    Hrvatin, Sinisa, Tzeng, Christopher P, Nagy, M Aurel, Stroud, Hume, Koutsioumpa, Charalampia, Wilcox, Oren F, Assad, Elena G, Green, Jonathan, Harvey, Christopher D, Griffith, Eric C et al. · 2019 · eLife
42. scMatch: a single-cell gene expression profile annotation tool using reference datasets
    Hou, Rui, Denisenko, Elena, Forrest, Alistair R R · 2019 · Bioinformatics
43. Computational approaches for interpreting sc<scp>RNA</scp>‐seq data
    Rostom, Raghd, Svensson, Valentine, Teichmann, Sarah A., Kar, Gozde · 2017 · FEBS Letters
44. Single-cell epigenomic variability reveals functional cancer heterogeneity
    Litzenburger, Ulrike M., Buenrostro, Jason D., Wu, Beijing, Shen, Ying, Sheffield, Nathan C., Kathiria, Arwa, Greenleaf, William J., Chang, Howard Y. · 2017 · Genome Biology
45. TCR sequencing paired with massively parallel 3′ RNA-seq reveals clonotypic T cell signatures
    Tu, Ang A., Gierahn, Todd M., Monian, Brinda, Morgan, Duncan M., Mehta, Naveen K., Ruiter, Bert, Shreffler, Wayne G., Shalek, Alex K., Love, J. Christopher · 2019 · Nature Immunology
46. Determining sequencing depth in a single-cell RNA-seq experiment
    Zhang, Martin Jinye, Ntranos, Vasilis, Tse, David · 2020 · Nature Communications
47. Single-nuclei isoform RNA sequencing unlocks barcoded exon connectivity in frozen brain tissue
    Hardwick, Simon A., Hu, Wen, Joglekar, Anoushka, Fan, Li, Collier, Paul G., Foord, Careen, Balacco, Jennifer, Lanjewar, Samantha, Sampson, Maureen McGuirk, Koopmans, Frank et al. · 2022 · Nature Biotechnology
48. UMI-count modeling and differential expression analysis for single-cell RNA sequencing
    Chen, Wenan, Li, Yan, Easton, John, Finkelstein, David, Wu, Gang, Chen, Xiang · 2018 · Genome Biology
49. Multiplexed single-cell RNA-seq via transient barcoding for simultaneous expression profiling of various drug perturbations
    Shin, Dongju, Lee, Wookjae, Lee, Ji Hyun, Bang, Duhee · 2019 · Science Advances
50. Anatomical and single-cell transcriptional profiling of the murine habenular complex
    Wallace, Michael L, Huang, Kee Wui, Hochbaum, Daniel, Hyun, Minsuk, Radeljic, Gianna, Sabatini, Bernardo L · 2020 · eLife
51. A multicenter study benchmarking single-cell RNA sequencing technologies using reference samples
    Chen, Wanqiu, Zhao, Yongmei, Chen, Xin, Yang, Zhaowei, Xu, Xiaojiang, Bi, Yingtao, Chen, Vicky, Li, Jing, Choi, Hannah, Ernest, Ben et al. · 2021 · Nature Biotechnology
52. From tissues to cell types and back: single-cell gene expression analysis of tissue architecture
    Chen, Xi, Teichmann, Sarah A., Meyer, Kerstin B. · 2018 · Annual Review of Biomedical Data Science
53. DMSO cryopreservation is the method of choice to preserve cells for droplet-based single-cell RNA sequencing
    Wohnhaas, Christian T., Leparc, Germán G., Fernandez-Albert, Francesc, Kind, David, Gantner, Florian, Viollet, Coralie, Hildebrandt, Tobias, Baum, Patrick · 2019 · Scientific Reports
54. The role of biomarkers in personalized immunotherapy
    Sankar, Kamya, Ye, Jing Christine, Li, Zihai, Zheng, Lei, Song, Wenru, Hu-Lieskovan, Siwen · 2022 · Biomarker Research
55. Droplet-based single cell RNAseq tools: a practical guide
    Salomon, Robert, Kaczorowski, Dominik, Valdes-Mora, Fatima, Nordon, Robert E., Neild, Adrian, Farbehi, Nona, Bartonicek, Nenad, Gallego-Ortega, David · 2019 · Lab on a Chip
56. Combined quantification of intracellular (phospho-)proteins and transcriptomics from fixed single cells
    Gerlach, Jan. P., van Buggenum, Jessie A. G., Tanis, Sabine E. J., Hogeweg, Mark, Heuts, Branco M. H., Muraro, Mauro J., Elze, Lisa, Rivello, Francesca, Rakszewska, Agata, van Oudenaarden, Alexander et al. · 2019 · Scientific Reports
57. Single cell transcriptomics in neuroscience: cell classification and beyond
    Tasic, Bosiljka · 2018 · Current Opinion in Neurobiology
58. Single-cell joint detection of chromatin occupancy and transcriptome enables higher-dimensional epigenomic reconstructions
    Xiong, Haiqing, Luo, Yingjie, Wang, Qianhao, Yu, Xianhong, He, Aibin · 2021 · Nature Methods
59. scMAGeCK links genotypes with multiple phenotypes in single-cell CRISPR screens
    Yang, Lin, Zhu, Yuqing, Yu, Hua, Cheng, Xiaolong, Chen, Sitong, Chu, Yulan, Huang, He, Zhang, Jin, Li, Wei · 2020 · Genome Biology
60. Simultaneous multiplexed amplicon sequencing and transcriptome profiling in single cells
    Saikia, Mridusmita, Burnham, Philip, Keshavjee, Sara H., Wang, Michael F. Z., Heyang, Michael, Moral-Lopez, Pablo, Hinchman, Meleana M., Danko, Charles G., Parker, John S. L., De Vlaminck, Iwijn · 2019 · Nature Methods
61. Quantitation of mRNA Transcripts and Proteins Using the BD Rhapsody™ Single-Cell Analysis System
    Shum, Eleen Y., Walczak, Elisabeth M., Chang, Christina, Christina Fan, H. · 2019 · Advances in Experimental Medicine and Biology
62. Mouse embryonic stem cells can differentiate via multiple paths to the same state
    Briggs, James Alexander, Li, Victor C, Lee, Seungkyu, Woolf, Clifford J, Klein, Allon, Kirschner, Marc W · 2017 · eLife
63. Using single‐cell multiple omics approaches to resolve tumor heterogeneity
    Ortega, Michael A., Poirion, Olivier, Zhu, Xun, Huang, Sijia, Wolfgruber, Thomas K., Sebra, Robert, Garmire, Lana X. · 2017 · Clinical and Translational Medicine
64. Neuronal cell types in the fly: single-cell anatomy meets single-cell genomics
    Bates, Alexander Shakeel, Janssens, Jasper, Jefferis, Gregory SXE, Aerts, Stein · 2019 · Current Opinion in Neurobiology
65. Integrated analysis of single cell transcriptomic data across conditions, technologies, and species
    Butler, Andrew, Satija, Rahul · 2017
66. Comprehensive generation, visualization, and reporting of quality control metrics for single-cell RNA sequencing data
    Hong, Rui, Koga, Yusuke, Bandyadka, Shruthi, Leshchyk, Anastasia, Wang, Yichen, Akavoor, Vidya, Cao, Xinyun, Sarfraz, Irzam, Wang, Zhe, Alabdullatif, Salam et al. · 2022 · Nature Communications
67. Bayesian sparse regression analysis documents the diversity of spinal inhibitory interneurons
    Gabitto, Mariano I., Pakman, Ari, Bikoff, Jay B., Abbott, L.F., Jessell, Thomas M., Paninski, Liam · 2016 · Cell
68. bigSCale: an analytical framework for big-scale single-cell data
    Iacono, Giovanni, Mereu, Elisabetta, Guillaumet-Adkins, Amy, Corominas, Roser, Cuscó, Ivon, Rodríguez-Esteban, Gustavo, Gut, Marta, Pérez-Jurado, Luis Alberto, Gut, Ivo, Heyn, Holger · 2018 · Genome Research
69. Network modeling of single-cell omics data: challenges, opportunities, and progresses
    Blencowe, Montgomery, Arneson, Douglas, Ding, Jessica, Chen, Yen-Wei, Saleem, Zara, Yang, Xia · 2019 · Emerging Topics in Life Sciences
70. Multiscale PHATE identifies multimodal signatures of COVID-19
    Kuchroo, Manik, Huang, Jessie, Wong, Patrick, Grenier, Jean-Christophe, Shung, Dennis, Tong, Alexander, Lucas, Carolina, Klein, Jon, Burkhardt, Daniel B., Gigante, Scott et al. · 2022 · Nature Biotechnology
71. Computational methods for single-cell multi-omics integration and alignment
    Stanojevic, Stefan, Li, Yijun, Ristivojevic, Aleksandar, Garmire, Lana X. · 2022 · Genomics, Proteomics &amp; Bioinformatics
72. Categorical Analysis of Human T Cell Heterogeneity with One-Dimensional Soli-Expression by Nonlinear Stochastic Embedding
    Cheng, Yang, Wong, Michael T, van der Maaten, Laurens, Newell, Evan W · 2016 · The Journal of Immunology
73. Deterministic scRNA-seq captures variation in intestinal crypt and organoid composition
    Bues, Johannes, Biočanin, Marjan, Pezoldt, Joern, Dainese, Riccardo, Chrisnandy, Antonius, Rezakhani, Saba, Saelens, Wouter, Gardeux, Vincent, Gupta, Revant, Sarkis, Rita et al. · 2022 · Nature Methods
74. Exploring single cells in space and time during tissue development, homeostasis and regeneration
    Mayr, Urs, Serra, Denise, Liberali, Prisca · 2019 · Development
75. Single-cell profiling of proteins and chromatin accessibility using PHAGE-ATAC
    Fiskin, Evgenij, Lareau, Caleb A., Ludwig, Leif S., Eraslan, Gökcen, Liu, Feimei, Ring, Aaron M., Xavier, Ramnik J., Regev, Aviv · 2022 · Nature Biotechnology
76. High-content phenotypic and pathway profiling to advance drug discovery in diseases of unmet need
    Hughes, Rebecca E., Elliott, Richard J.R., Dawson, John C., Carragher, Neil O. · 2021 · Cell Chemical Biology
77. A joint model of unpaired data from scRNA-seq and spatial transcriptomics for imputing missing gene expression measurements
    Lopez, Romain, Nazaret, Achille, Langevin, Maxime, Samaran, Jules, Regier, Jeffrey, Jordan, Michael I., Yosef, Nir · 2019 · arXiv
78. Scrublet: computational identification of cell doublets in single-cell transcriptomic data
    Wolock, Samuel L., Lopez, Romain, Klein, Allon M. · 2018
79. Estimating the frequency of multiplets in single-cell RNA sequencing from cell-mixing experiments
    Bloom, Jesse D. · 2018 · PeerJ
80. A comparison of methods accounting for batch effects in differential expression analysis of UMI count based single cell RNA sequencing
    Chen, Wenan, Zhang, Silu, Williams, Justin, Ju, Bensheng, Shaner, Bridget, Easton, John, Wu, Gang, Chen, Xiang · 2020 · Computational and Structural Biotechnology Journal
81. Single-Cell Computational Strategies for Lineage Reconstruction in Tissue Systems
    Herring, Charles A., Chen, Bob, McKinley, Eliot T., Lau, Ken S. · 2018 · Cellular and Molecular Gastroenterology and Hepatology
82. GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge
    Wagner, Florian · 2015 · PLOS ONE
83. A Comprehensive Survey of Statistical Approaches for Differential Expression Analysis in Single-Cell RNA Sequencing Studies
    Das, Samarendra, Rai, Anil, Merchant, Michael L., Cave, Matthew C., Rai, Shesh N. · 2021 · Genes
84. Engineering cell heterogeneity into organs-on-a-chip
    Mertz, David R., Ahmed, Tasdiq, Takayama, Shuichi · 2018 · Lab on a Chip
85. Encoding Method of Single-cell Spatial Transcriptomics Sequencing
    Zhou, Ying, Jia, Erteng, Pan, Min, Zhao, Xiangwei, Ge, Qinyu · 2020 · International Journal of Biological Sciences
86. A community-based transcriptomics classification and nomenclature of neocortical cell types
    Yuste, Rafael, Hawrylycz, Michael, Aalling, Nadia, Aguilar-Valles, Argel, Arendt, Detlev, Armañanzas, Ruben, Ascoli, Giorgio A., Bielza, Concha, Bokharaie, Vahid, Bergmann, Tobias Borgtoft et al. · 2020 · Nature Neuroscience
87. BART-Seq: cost-effective massively parallelized targeted sequencing for genomics, transcriptomics, and single-cell analysis
    Uzbas, Fatma, Opperer, Florian, Sönmezer, Can, Shaposhnikov, Dmitry, Sass, Steffen, Krendl, Christian, Angerer, Philipp, Theis, Fabian J., Mueller, Nikola S., Drukker, Micha · 2019 · Genome Biology
88. Differential gene expression analysis for multi-subject single-cell RNA-sequencing studies with<i>aggregateBioVar</i>
    Thurman, Andrew L, Ratcliff, Jason A, Chimenti, Michael S, Pezzulo, Alejandro A · 2021 · Bioinformatics
89. Fundamental limits on dynamic inference from single cell snapshots
    Weinreb, Caleb, Wolock, Samuel, Tusi, Betsabeh K., Socolovsky, Merav, Klein, Allon M. · 2017
90. Spatial transcriptome sequencing of FFPE tissues at cellular level
    Liu, Yang, Enninful, Archibald, Deng, Yanxiang, Fan, Rong · 2020
91. Evaluation of genetic demultiplexing of single-cell sequencing data from model species
    Cardiello, Joseph F, Joven Araus, Alberto, Giatrellis, Sarantis, Helsens, Clement, Simon, András, Leigh, Nicholas D · 2023 · Life Science Alliance
92. Primary cilia-mediated regulation of microglial secretion in Alzheimer’s disease
    Yeo, Seungeun, Jang, Jaemyung, Jung, Hyun Jin, Lee, Hyeyoung, Choe, Youngshik · 2023 · Frontiers in Molecular Biosciences
93. Targeting individual cells by barcode in pooled sequence libraries
    Ranu, Navpreet, Villani, Alexandra-Chloé, Hacohen, Nir, Blainey, Paul C · 2019 · Nucleic Acids Research
94. Direct capture of CRISPR guides enables scalable, multiplexed, and multi-omic Perturb-seq
    Replogle, Joseph M., Xu, Albert, Norman, Thomas M., Meer, Elliott J., Terry, Jessica M., Riordan, Daniel, Srinivas, Niranjan, Mikkelsen, Tarjei S., Weissman, Jonathan S., Adamson, Britt · 2018
95. Multi-omic analyses in immune cell development with lessons learned from T cell development
    Cordes, Martijn, Pike-Overzet, Karin, Van Den Akker, Erik B., Staal, Frank J. T., Canté-Barrett, Kirsten · 2023 · Frontiers in Cell and Developmental Biology
96. Improved ClickTags enable live-cell barcoding for highly multiplexed single cell sequencing
    Zhao, Xinlu, Sun, Shiming, Yu, Wenhao, Zhu, Wenqi, Zhao, Zihan, Zhou, Yiqi, Ding, Xiuheng, Fang, Nan, Yang, Rong, Li, Jie P. · 2022 · RSC Chemical Biology
97. Ex Vivo Expansion of Phenotypic and Transcriptomic Chronic Myeloid Leukemia Stem Cells
    Patel, Sweta B., Kuznetsova, Valeriya, Matkins, Victoria R., Franceski, Alana M., Bassal, Mahmoud A., Welner, Robert S. · 2022 · Experimental Hematology
98. Research progress on immunotherapeutics for triple-negative breast cancer from a single-cell perspective
    Yuan, Zixuan, Liu, Zhiwei, Zhou, Mengying, Wen, Huijuan, Li, Bei · 2026 · Critical Reviews in Oncology/Hematology
99. scGraph2Vec: a deep generative model for gene embedding augmented by graph neural network and single-cell omics data
    Lin, Shiqi, Jia, Peilin · 2024 · GigaScience
100. Order Matters: Ambient RNA correction confounds doublet detection in single-cell RNA sequencing
     Meier, Michelle, Howitt, George, Grima, Calandra V, Dixit, Gunjan, King, Hamish, Gubbels, Liam, Levi, Eric, Davies, Karen, Shanthikumar, Shivanthan, Neeland, Melanie R. et al. · 2026