Entering the era of single-cell transcriptomics in biology and medicine

Cancer Genome Landscapes

Vogelstein, B., Papadopoulos, N., Velculescu, V. E., Zhou, S., Diaz, L. A., & Kinzler, K. W. (2013) · Science · doi:10.1126/science.1235122 · Cited by 7,863

Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing

Gerlinger, M., Rowan, A. J., Horswell, S., Larkin, J., Endesfelder, D., Gronroos, E., Martinez, P., Matthews, N., Stewart, A., Tarpey, P., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1113205 · Cited by 7,774

Alternative isoform regulation in human tissue transcriptomes

Wang, E. T., Sandberg, R., Luo, S., Khrebtukova, I., Zhang, L., Mayr, C., Kingsmore, S. F., Schroth, G. P., & Burge, C. B. (2008) · Nature · doi:10.1038/nature07509 · Cited by 5,181

Full-length RNA-seq from single cells using Smart-seq2

Picelli, S., Faridani, O. R., Björklund, Å. K., Winberg, G., Sagasser, S., & Sandberg, R. (2014) · Nature Protocols · doi:10.1038/nprot.2014.006 · Cited by 4,137

Smart-seq2 for sensitive full-length transcriptome profiling in single cells

Picelli, S., Björklund, Å. K., Faridani, O. R., Sagasser, S., Winberg, G., & Sandberg, R. (2013) · Nature Methods · doi:10.1038/nmeth.2639 · Cited by 2,358

Widespread Shortening of 3′UTRs by Alternative Cleavage and Polyadenylation Activates Oncogenes in Cancer Cells

Mayr, C., & Bartel, D. P. (2009) · Cell · doi:10.1016/j.cell.2009.06.016 · Cited by 1,613

Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells

Shalek, A. K., Satija, R., Adiconis, X., Gertner, R. S., Gaublomme, J. T., Raychowdhury, R., Schwartz, S., Yosef, N., Malboeuf, C., Lu, D., et al. (2013) · Nature · doi:10.1038/nature12172 · Cited by 1,190

Single-cell sequencing-based technologies will revolutionize whole-organism science

Shapiro, E., Biezuner, T., & Linnarsson, S. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3542 · Cited by 1,177

Counting absolute numbers of molecules using unique molecular identifiers

Kivioja, T., Vähärautio, A., Karlsson, K., Bonke, M., Enge, M., Linnarsson, S., & Taipale, J. (2012) · Nature Methods · doi:10.1038/nmeth.1778 · Cited by 1,010

ENZYME INDUCTION AS AN ALL-OR-NONE PHENOMENON

Novick, A., & Weiner, M. (1957) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.43.7.553 · Cited by 891

The Cellular Phase of Alzheimer’s Disease

De Strooper, B., & Karran, E. (2016) · Cell · doi:10.1016/j.cell.2015.12.056 · Cited by 1,990

Comparative Analysis of Single-Cell RNA Sequencing Methods

Ziegenhain, C., Vieth, B., Parekh, S., Reinius, B., Guillaumet-Adkins, A., Smets, M., Leonhardt, H., Heyn, H., Hellmann, I., & Enard, W. (2017) · Molecular Cell · doi:10.1016/j.molcel.2017.01.023 · Cited by 1,494

Single-Cell Transcriptome Profiling of Human Pancreatic Islets in Health and Type 2 Diabetes

Segerstolpe, Å., Palasantza, A., Eliasson, P., Andersson, E.-M., Andréasson, A.-C., Sun, X., Picelli, S., Sabirsh, A., Clausen, M., Bjursell, M. K., et al. (2016) · Cell Metabolism · doi:10.1016/j.cmet.2016.08.020 · Cited by 1,550

Computational and analytical challenges in single-cell transcriptomics

Stegle, O., Teichmann, S. A., & Marioni, J. C. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3833 · Cited by 1,170

The art of using t-SNE for single-cell transcriptomics

Kobak, D., & Berens, P. (2019) · Nature Communications · doi:10.1038/s41467-019-13056-x · Cited by 1,115

Tn5 transposase and tagmentation procedures for massively scaled sequencing projects

Picelli, S., Björklund, Å. K., Reinius, B., Sagasser, S., Winberg, G., & Sandberg, R. (2014) · Genome Research · doi:10.1101/gr.177881.114 · Cited by 973

Single-cell RNA counting at allele and isoform resolution using Smart-seq3

Hagemann-Jensen, M., Ziegenhain, C., Chen, P., Ramsköld, D., Hendriks, G.-J., Larsson, A. J. M., Faridani, O. R., & Sandberg, R. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0497-0 · Cited by 700

Visualization and analysis of single-cell RNA-seq data by kernel-based similarity learning

Wang, B., Zhu, J., Pierson, E., Ramazzotti, D., & Batzoglou, S. (2017) · Nature Methods · doi:10.1038/nmeth.4207 · Cited by 706

Electrophysiological, transcriptomic and morphologic profiling of single neurons using Patch-seq

Cadwell, C. R., Palasantza, A., Jiang, X., Berens, P., Deng, Q., Yilmaz, M., Reimer, J., Shen, S., Bethge, M., Tolias, K. F., et al. (2016) · Nature Biotechnology · doi:10.1038/nbt.3445 · Cited by 581

High-throughput single-cell gene-expression profiling with multiplexed error-robust fluorescence in situ hybridization

Moffitt, J. R., Hao, J., Wang, G., Chen, K. H., Babcock, H. P., & Zhuang, X. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1612826113 · Cited by 580

Single-Cell Transcriptomics Reveals that Differentiation and Spatial Signatures Shape Epidermal and Hair Follicle Heterogeneity

Joost, S., Zeisel, A., Jacob, T., Sun, X., La Manno, G., Lönnerberg, P., Linnarsson, S., & Kasper, M. (2016) · Cell Systems · doi:10.1016/j.cels.2016.08.010 · Cited by 429

Single-cell DNA methylome sequencing and bioinformatic inference of epigenomic cell-state dynamics

Farlik, M., Sheffield, N. C., Nuzzo, A., Datlinger, P., Schönegger, A., Klughammer, J., & Bock, C. (2015) · Cell Reports · doi:10.1016/j.celrep.2015.02.001 · Cited by 422

Single Cell Isolation and Analysis

Hu, P., Zhang, W., Xin, H., & Deng, G. (2016) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2016.00116 · Cited by 384

Revealing the Critical Regulators of Cell Identity in the Mouse Cell Atlas

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Challenges and emerging directions in single-cell analysis

Yuan, G.-C., Cai, L., Elowitz, M., Enver, T., Fan, G., Guo, G., Irizarry, R., Kharchenko, P., Kim, J., Orkin, S., et al. (2017) · Genome Biology · doi:10.1186/s13059-017-1218-y · Cited by 341

Preparation of Single‐Cell RNA‐Seq Libraries for Next Generation Sequencing

Trombetta, J. J., Gennert, D., Lu, D., Satija, R., Shalek, A. K., & Regev, A. (2014) · Current Protocols in Molecular Biology · doi:10.1002/0471142727.mb0422s107 · Cited by 290

Autoimmune diseases — connecting risk alleles with molecular traits of the immune system

Gutierrez-Arcelus, M., Rich, S. S., & Raychaudhuri, S. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2015.33 · Cited by 256

Systematic determination of the mitochondrial proportion in human and mice tissues for single-cell RNA-sequencing data quality control

Osorio, D., & Cai, J. J. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btaa751 · Cited by 212

Single-cell sequencing of the small-RNA transcriptome

Faridani, O. R., Abdullayev, I., Hagemann-Jensen, M., Schell, J. P., Lanner, F., & Sandberg, R. (2016) · Nature Biotechnology · doi:10.1038/nbt.3701 · Cited by 212

Transformer for one stop interpretable cell type annotation

Chen, J., Xu, H., Tao, W., Chen, Z., Zhao, Y., & Han, J.-D. J. (2023) · Nature Communications · doi:10.1038/s41467-023-35923-4 · Cited by 189

Analysis of allelic expression patterns in clonal somatic cells by single-cell RNA–seq

Reinius, B., Mold, J. E., Ramsköld, D., Deng, Q., Johnsson, P., Michaëlsson, J., Frisén, J., & Sandberg, R. (2016) · Nature Genetics · doi:10.1038/ng.3678 · Cited by 149

MATCHER: manifold alignment reveals correspondence between single cell transcriptome and epigenome dynamics

Welch, J. D., Hartemink, A. J., & Prins, J. F. (2017) · Genome Biology · doi:10.1186/s13059-017-1269-0 · Cited by 140

Paradoxical changes in innate immunity in aging: recent progress and new directions

Montgomery, R. R., & Shaw, A. C. (2015) · Journal of Leukocyte Biology · doi:10.1189/jlb.5mr0315-104r · Cited by 147

Systems-based proteomics to resolve the biology of Alzheimer’s disease beyond amyloid and tau

Rayaprolu, S., Higginbotham, L., Bagchi, P., Watson, C. M., Zhang, T., Levey, A. I., Rangaraju, S., & Seyfried, N. T. (2021) · Neuropsychopharmacology · doi:10.1038/s41386-020-00840-3 · Cited by 118

Comparison of methods to detect differentially expressed genes between single-cell populations

Jaakkola, M. K., Seyednasrollah, F., Mehmood, A., & Elo, L. L. (2016) · Briefings in Bioinformatics · doi:10.1093/bib/bbw057 · Cited by 86

A Comprehensive Survey of Statistical Approaches for Differential Expression Analysis in Single-Cell RNA Sequencing Studies

Das, S., Rai, A., Merchant, M. L., Cave, M. C., & Rai, S. N. (2021) · Genes · doi:10.3390/genes12121947 · Cited by 35

Single-cell gene expression profiling and cell state dynamics: collecting data, correlating data points and connecting the dots

Marr, C., Zhou, J. X., & Huang, S. (2016) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2016.04.015 · Cited by 35