| RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays JC Marioni, CE Mason, SM Mane, M Stephens, Y Gilad Genome research 18 (9), 1509-1517, 2008 | 3497 | 2008 |
| The human cell atlas A Regev, SA Teichmann, ES Lander, I Amit, C Benoist, E Birney, ... elife 6, e27041, 2017 | 2067 | 2017 |
| Intratumor heterogeneity in human glioblastoma reflects cancer evolutionary dynamics A Sottoriva, I Spiteri, SGM Piccirillo, A Touloumis, VP Collins, JC Marioni, ... Proceedings of the National Academy of Sciences 110 (10), 4009-4014, 2013 | 1929 | 2013 |
| Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors L Haghverdi, ATL Lun, MD Morgan, JC Marioni Nature biotechnology 36 (5), 421-427, 2018 | 1841 | 2018 |
| Understanding mechanisms underlying human gene expression variation with RNA sequencing JK Pickrell, JC Marioni, AA Pai, JF Degner, BE Engelhardt, E Nkadori, ... Nature 464 (7289), 768-772, 2010 | 1548 | 2010 |
| A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor ATL Lun, DJ McCarthy, JC Marioni F1000Research 5, 2016 | 1488 | 2016 |
| The technology and biology of single-cell RNA sequencing AA Kolodziejczyk, JK Kim, V Svensson, JC Marioni, SA Teichmann Molecular cell 58 (4), 610-620, 2015 | 1307 | 2015 |
| Computational and analytical challenges in single-cell transcriptomics O Stegle, SA Teichmann, JC Marioni Nature Reviews Genetics 16 (3), 133-145, 2015 | 1266 | 2015 |
| Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells F Buettner, KN Natarajan, FP Casale, V Proserpio, A Scialdone, FJ Theis, ... Nature biotechnology 33 (2), 155-160, 2015 | 1240 | 2015 |
| Resolving the fibrotic niche of human liver cirrhosis at single-cell level P Ramachandran, R Dobie, JR Wilson-Kanamori, EF Dora, ... Nature 575 (7783), 512-518, 2019 | 1102 | 2019 |
| Pooling across cells to normalize single-cell RNA sequencing data with many zero counts AT L. Lun, K Bach, JC Marioni Genome biology 17, 1-14, 2016 | 1086 | 2016 |
| Accounting for technical noise in single-cell RNA-seq experiments P Brennecke, S Anders, JK Kim, AA Kołodziejczyk, X Zhang, V Proserpio, ... Nature methods 10 (11), 1093-1095, 2013 | 1044 | 2013 |
| Eleven grand challenges in single-cell data science D Lähnemann, J Köster, E Szczurek, DJ McCarthy, SC Hicks, ... Genome biology 21, 1-35, 2020 | 996 | 2020 |
| Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets R Argelaguet, B Velten, D Arnol, S Dietrich, T Zenz, JC Marioni, F Buettner, ... Molecular systems biology 14 (6), e8124, 2018 | 865 | 2018 |
| A Bayesian deconvolution strategy for immunoprecipitation-based DNA methylome analysis TA Down, VK Rakyan, DJ Turner, P Flicek, H Li, E Kulesha, S Graef, ... Nature biotechnology 26 (7), 779-785, 2008 | 783 | 2008 |
| A single-cell molecular map of mouse gastrulation and early organogenesis B Pijuan-Sala, JA Griffiths, C Guibentif, TW Hiscock, W Jawaid, ... Nature 566 (7745), 490-495, 2019 | 743 | 2019 |
| Classification of low quality cells from single-cell RNA-seq data T Ilicic, JK Kim, AA Kolodziejczyk, FO Bagger, DJ McCarthy, JC Marioni, ... Genome biology 17, 1-15, 2016 | 672 | 2016 |
| EmptyDrops: distinguishing cells from empty droplets in droplet-based single-cell RNA sequencing data ATL Lun, S Riesenfeld, T Andrews, TP Dao, T Gomes, ... Genome biology 20, 1-9, 2019 | 657 | 2019 |
| Effect of read-mapping biases on detecting allele-specific expression from RNA-sequencing data JF Degner, JC Marioni, AA Pai, JK Pickrell, E Nkadori, Y Gilad, ... Bioinformatics 25 (24), 3207-3212, 2009 | 625 | 2009 |
| scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells SJ Clark, R Argelaguet, CA Kapourani, TM Stubbs, HJ Lee, ... Nature communications 9 (1), 781, 2018 | 603 | 2018 |
