Marioni Group | Single cell genomics

Marioni Group | Single cell genomics

Marioni Group

People

Marioni, John
Dr John Marioni
Group Leader

John Marioni's group develop computational and statistical tools to exploit high-throughput genomics data to understand the regulation of gene expression and to model developmental and evolutionary processes. His team has pioneered approaches for analysing single-cell transcriptomics data and, together with four colleagues, he co-ordinates the Sanger Institute-EBI Single-Cell Genomics Centre.

Key Projects, Collaborations, Tools & Data

Research Programmes

Partners and Funders

Internal Partners

Publications

  • CTCF maintains regulatory homeostasis of cancer pathways.

    Aitken SJ, Ibarra-Soria X, Kentepozidou E, Flicek P, Feig C et al.

    Genome biology 2018;19;1;106

  • T cell cytolytic capacity is independent of initial stimulation strength.

    Richard AC, Lun ATL, Lau WWY, Göttgens B, Marioni JC and Griffiths GM

    Nature immunology 2018

  • Detection and removal of barcode swapping in single-cell RNA-seq data.

    Griffiths JA, Richard AC, Bach K, Lun ATL and Marioni JC

    Nature communications 2018;9;1;2667

  • CpG island composition differences are a source of gene expression noise indicative of promoter responsiveness.

    Morgan MD and Marioni JC

    Genome biology 2018;19;1;81

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

    Argelaguet R, Velten B, Arnol D, Dietrich S, Zenz T et al.

    Molecular systems biology 2018;14;6;e8124

  • Specificity of RNAi, LNA and CRISPRi as loss-of-function methods in transcriptional analysis.

    Stojic L, Lun ATL, Mangei J, Mascalchi P, Quarantotti V et al.

    Nucleic acids research 2018

  • Using single-cell genomics to understand developmental processes and cell fate decisions.

    Griffiths JA, Scialdone A and Marioni JC

    Molecular systems biology 2018;14;4;e8046

  • Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors.

    Haghverdi L, Lun ATL, Morgan MD and Marioni JC

    Nature biotechnology 2018

  • SRSF3 maintains transcriptome integrity in oocytes by regulation of alternative splicing and transposable elements.

    Do DV, Strauss B, Cukuroglu E, Macaulay I, Wee KB et al.

    Cell discovery 2018;4;33

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

    Goolam M, Scialdone A, Graham SJL, Macaulay IC, Jedrusik A et al.

    Cell 2016;165;1;61-74