Antibody repertoire analytics: the development of a visualization toolkit and its application to high-throughput Ig-seq data

Next Generation Sequencing (NGS) of antibodies (Abs) – known as Ig-seq or Rep-seq – is increasingly used to address fundamental immunological questions, such as: How do immune responses to pathogens, vaccines and therapeutic Abs differ? And what are the differences between healthy Ab repertoires and those associated with immune dysfunction? A typical Ig-seq dataset consists of millions of partial mRNA Ab sequences.

The aim of this project is to develop a toolkit for visually analysing Ig-seq, enabling biologists to rapidly explore their data, generate novel hypotheses and make new discoveries. The priority will be to support whole Ab repertoire analytics and to characterize fundamental properties (repertoire diversity, Ab convergence within and between repertoires, and the dynamics of repertoire evolution) relevant to vaccine design and therapeutic Ab discovery.

The student on this project will engage in two complementary activities: tool development and immunology research. S/he will benefit from the preliminary work undertaken within the group to evaluate open-source network visualization platforms such as Cytoscape and Gephi, and interactive visualization of Ig-seq data using a Data-Driven Documents (D3) framework. Both activities will be undertaken in close collaboration with our collaborators at UCB, the leading UK company focusing on therapeutic Ab discovery.

Skills/experience of ideal applicant: This project would suit a student with good programming skills who is interested in apply these skills to an area of biology that is of immediate therapeutic relevance.