Marioni, John C.

RNA-seq: An assessment of technical reproducibility and comparison with gene expression arrays

Marioni, J. C., Mason, C. E., Mane, S. M., Stephens, M., & Gilad, Y. (2008) · Genome Research

Genomics and Phylogenetic StudiesGene expression and cancer classification

Cited by 2,771

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. (2018) · Nature Biotechnology

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 2,416

The human cell atlas

Regev, A., Teichmann, S. A., Lander, E. S., Amit, I., Benoist, C., Birney, E., Bodenmiller, B., Campbell, P., Carninci, P., Clatworthy, M., et al. (2017) · eLife

Single-cell and spatial transcriptomicsGene Regulatory Network Analysis

Cited by 2,232

Resolving the fibrotic niche of human liver cirrhosis at single-cell level

Ramachandran, P., Dobie, R., Wilson-Kanamori, J. R., Dora, E. F., Henderson, B. E. P., Luu, N. T., Portman, J. R., Matchett, K. P., Brice, M., Marwick, J. A., et al. (2019) · Nature

Liver physiology and pathologyLiver Diseases and Immunity

Cited by 1,784

Intratumor heterogeneity in human glioblastoma reflects cancer evolutionary dynamics

Sottoriva, A., Spiteri, I., Piccirillo, S. G. M., Touloumis, A., Collins, V. P., Marioni, J. C., Curtis, C., Watts, C., & Tavaré, S. (2013) · Proceedings of the National Academy of Sciences

Cancer Genomics and DiagnosticsGlioma Diagnosis and Treatment

Cited by 1,737

Multi-Omics Factor Analysis—a framework for unsupervised integration of multi-omics data sets

Argelaguet, R., Velten, B., Arnol, D., Dietrich, S., Zenz, T., Marioni, J. C., Buettner, F., Huber, W., & Stegle, O. (2018) · Molecular Systems Biology

Bioinformatics and Genomic NetworksSingle-cell and spatial transcriptomics

Cited by 1,510

The Technology and Biology of Single-Cell RNA Sequencing

Kolodziejczyk, A. A., Kim, J. K., Svensson, V., Marioni, J. C., & Teichmann, S. A. (2015) · Molecular Cell

Single-cell and spatial transcriptomicsGenomics and Phylogenetic Studies

Cited by 1,487

Eleven grand challenges in single-cell data science

Lähnemann, D., Köster, J., Szczurek, E., McCarthy, D. J., Hicks, S. C., Robinson, M. D., Vallejos, C. A., Campbell, K. R., Beerenwinkel, N., Mahfouz, A., et al. (2020) · Genome Biology

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 1,327

Understanding mechanisms underlying human gene expression variation with RNA sequencing

Pickrell, J. K., Marioni, J. C., Pai, A. A., Degner, J. F., Engelhardt, B. E., Nkadori, E., Veyrieras, J.-B., Stephens, M., Gilad, Y., & Pritchard, J. K. (2010) · Nature

Genetic Associations and EpidemiologyRNA Research and Splicing

Cited by 1,256

Computational and analytical challenges in single-cell transcriptomics

Stegle, O., Teichmann, S. A., & Marioni, J. C. (2015) · Nature Reviews Genetics

Single-cell and spatial transcriptomicsGenomics and Phylogenetic Studies

Cited by 1,170

Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells

Buettner, F., Natarajan, K. N., Casale, F. P., Proserpio, V., Scialdone, A., Theis, F. J., Teichmann, S. A., Marioni, J. C., & Stegle, O. (2015) · Nature Biotechnology

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 1,136

Pooling across cells to normalize single-cell RNA sequencing data with many zero counts

L. Lun, A. T., Bach, K., & Marioni, J. C. (2016) · Genome Biology

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 1,108

MOFA+: a statistical framework for comprehensive integration of multi-modal single-cell data

Argelaguet, R., Arnol, D., Bredikhin, D., Deloro, Y., Velten, B., Marioni, J. C., & Stegle, O. (2020) · Genome Biology

Single-cell and spatial transcriptomicsBioinformatics and Genomic Networks

Cited by 1,091

A single-cell molecular map of mouse gastrulation and early organogenesis

Pijuan-Sala, B., Griffiths, J. A., Guibentif, C., Hiscock, T. W., Jawaid, W., Calero-Nieto, F. J., Mulas, C., Ibarra-Soria, X., Tyser, R. C. V., Ho, D. L. L., et al. (2019) · Nature

Single-cell and spatial transcriptomicsDevelopmental Biology and Gene Regulation

Cited by 1,033

Accounting for technical noise in single-cell RNA-seq experiments

Brennecke, P., Anders, S., Kim, J. K., Kołodziejczyk, A. A., Zhang, X., Proserpio, V., Baying, B., Benes, V., Teichmann, S. A., Marioni, J. C., et al. (2013) · Nature Methods

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 979

Differential abundance testing on single-cell data using k-nearest neighbor graphs

Dann, E., Henderson, N. C., Teichmann, S. A., Morgan, M. D., & Marioni, J. C. (2022) · Nature Biotechnology

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 938

Unsupervised removal of systematic background noise from droplet-based single-cell experiments using CellBender

Fleming, S. J., Chaffin, M. D., Arduini, A., Akkad, A.-D., Banks, E., Marioni, J. C., Philippakis, A. A., Ellinor, P. T., & Babadi, M. (2023) · Nature Methods

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 867

Single-cell multi-omics analysis of the immune response in COVID-19

Cambridge Institute of Therapeutic Immunology and Infectious Disease-National Institute of Health Research (CITIID-NIHR) COVID-19 BioResource Collaboration, Stephenson, E., Reynolds, G., Botting, R. A., Calero-Nieto, F. J., Morgan, M. D., Tuong, Z. K., Bach, K., Sungnak, W., Worlock, K. B., et al. (2021) · Nature Medicine

COVID-19 Clinical Research StudiesSARS-CoV-2 and COVID-19 Research

Cited by 742

Classification of low quality cells from single-cell RNA-seq data

Ilicic, T., Kim, J. K., Kolodziejczyk, A. A., Bagger, F. O., McCarthy, D. J., Marioni, J. C., & Teichmann, S. A. (2016) · Genome Biology

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 693

scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells

Clark, S. J., Argelaguet, R., Kapourani, C.-A., Stubbs, T. M., Lee, H. J., Alda-Catalinas, C., Krueger, F., Sanguinetti, G., Kelsey, G., Marioni, J. C., et al. (2018) · Nature Communications

Epigenetics and DNA MethylationSingle-cell and spatial transcriptomics

Cited by 657

The human body at cellular resolution: the NIH Human Biomolecular Atlas Program

HuBMAP Consortium, Writing Group, Snyder, M. P., Lin, S., Posgai, A., Atkinson, M., Regev, A., Rood, J., Rozenblatt-Rosen, O., Gaffney, L., et al. (2019) · Nature

Single-cell and spatial transcriptomicsGenomics and Chromatin Dynamics

Cited by 595

Single Cell RNA-Sequencing of Pluripotent States Unlocks Modular Transcriptional Variation

Kolodziejczyk, A. A., Kim, J. K., Tsang, J. C. H., Ilicic, T., Henriksson, J., Natarajan, K. N., Tuck, A. C., Gao, X., Bühler, M., Liu, P., et al. (2015) · Cell Stem Cell

Pluripotent Stem Cells ResearchSingle-cell and spatial transcriptomics

Cited by 570

Effect of read-mapping biases on detecting allele-specific expression from RNA-sequencing data.

Degner, J. F., Marioni, J. C., Pai, A. A., Pickrell, J. K., Nkadori, E., Gilad, Y., & Pritchard, J. K. (2009) · Bioinformatics

Genomics and Phylogenetic StudiesRNA Research and Splicing

Cited by 502

Heterogeneity in Oct4 and Sox2 Targets Biases Cell Fate in 4-Cell Mouse Embryos

Goolam, M., Scialdone, A., Graham, S. J. L., Macaulay, I. C., Jedrusik, A., Hupalowska, A., Voet, T., Marioni, J. C., & Zernicka-Goetz, M. (2016) · Cell

Pluripotent Stem Cells ResearchDevelopmental Biology and Gene Regulation

Cited by 484