Research Group Leader
John Marioni obtained his PhD in Applied Mathematics in the University of Cambridge in 2008 and did his postdoctoral research in the Department of Human Genetics, University of Chicago. He joined EMBL-EBI as Research Group Leader in Computational and Evolutionary Genomics in 2010. His group develops the computational and statistical tools necessary to exploit high-throughput genomics data, with the aim of understanding the regulation of gene expression and modelling developmental and evolutionary processes. Within this context, the Marioni group focuses on understanding how the divergence of gene expression levels is regulated, using gene expression as a definition of the molecular fingerprint of individual cells to study the evolution of cell types, and modelling spatial variability in gene-expression levels within a tissue or organism. These three strands of research are brought together by single-cell sequencing technologies. John has a joint appointment at the Wellcome Trust Sanger Institute and the Cancer Research UK Cambridge Institute, which is part of the University of Cambridge.
marioni [at] ebi.ac.uk
ORCID iD: 0000-0001-9092-0852
Tel:+ 44 (0) 1223 494 583 / Fax:+ 44 (0) 1223 492 621
Human Cell Atlas
The Human Cell Atlas at EMBL-EBI
Scientists in the Human Cell Atlas (HCA) are rethinking human anatomy by defining cells according to their genetics, rather than their appearance. The goal of this international collaboration is to create an open, accessible reference map of the healthy human body using RNA sequencing technology.
The European Bioinformatics Institute (EMBL-EBI) is one of four partners developing the architecture to make the HCA work.
A Cloud-based, Modular Data Coordination Platform
The tens of millions of datasets generated in HCA experiments will be available for anyone to analyse on an open-source, modular Data Coordination Platform (HCA-DCP). The platform is developed jointly by:
- University of California Santa Cruz
- the Broad Institute
- the Chan Zuckerberg Initiative
The HCA-DCP features cloud-based pipelines that allow participating scientists to upload their datasets. It is built to make data accessible from anywhere via cloud access, and provides standard analysis outputs. It also provides a platform for building tools to analyse data across sites, for example to make meaningful comparisons between healthy and diseased tissues.
HCA-DCP services support innovation in diverse communities, for example by offering different approaches to data visualisation and analysis, collaboration and user/developer experience.
Partners working on the platform are striving to minimise barriers to entry over the longer term. To do this, they are putting in place features that make it easier to submit and use the data, and to contribute new methods.
Open Source and an Open Mind
The DCP takes a neutral, generalised approach to delivery because it supports such a broad range of scientific assays, data modalities and computational methods.
User Experience research and design have been a core aspect of the project. The Data Coordination Platform is implementing functionality that is essentially useful to the project and provides features that foster collaboration and analysis. At the same time, there is plenty of room for others to innovate on this open framework to serve the diverse communities who wish to explore these rich, well-described datasets.
The HCA uses a combination of technologies, some of which are developed within the DCP team and others that are part of existing infrastructure. Any software built by the DCP project team may be used by non-HCA entities.
The HCA-DCP Project Team at EMBL-EBI
Members of the HCA-DCP project team are based at the four partner organisations.
Leadership and Guidance
The HCA-DCP project team is led by the Data Coordination Platform Steering Committee and the HCA-DCP Governance Group, comprising members of the HCA scientific leadership.