Bioinformatics Analyst

Research Group Home Page: 


After his MSc in genetics, Stephane obtained his PhD in Medical Sciences as a bioinformatician developing tools to help identify variants linked to psychosis using comparative genomics to include in association studies and to manage results of the experiments.

Appreciating the importance of patterns of normal variation in the quest for aetiologically significant polymorphisms, he then identified regions in the human genome informative on the phylogeography of human populations by mining publicly available data, and selecting several for experimental validation.

To return to medical research, Stephane then contributed to large-scale population-based genome-wide association studies on cancer, including gene-by-gene interaction.

To study how the information encoded in the DNA he had so far focused on is expressed in human and affect its health, he joined a multi-omics project on asthma, in a gorup responsible for its large-scale transcriptomic study and the integrative analysis of the clinical and various omics data sets.

Stephane then joined the Bioinformatics core, attracted by the various research groups, cores and appraoches used in the institute.

Types of analysis performed at the CRUK CI

  • Genomics
    • bulk RNA-seq
    • single-cell RNA-seq (10X so far)
    • ChIP-seq
    • variant calling (Whole-Genome sequencing)
    • copy number variant analysis (shallow and deep Whole-Genome sequencing)
  • Proteomics
    • RIME
    • TMT-RIME


Design and analysis of large-scale multi-site genomics and transcriptomics studies in collaboration with geneticists and clinicians.

Experience with contemporary bioinformatics utilities, web resources and databases: functional analysis, gene and motif prediction, NGS analysis, comparative genomics, molecular evolution, phylogenetics, population and statistical genetics, pathway and network analysis and visualisation, omics data fusion,

Shell scripting, awk, sed, Perl, BioPerl, Ensembl API, C, (Pascal, CGI/HTML,) use of computer cluster, analysis pipelines.


ORCID: 0000-0002-8479-3110

Work address: 
Cancer Research UK Cambridge Institute University of Cambridge Li Ka Shing Centre Robinson Way Cambridge CB2 0RE