Bioinformatics & Biostatistics

The Bioinformatics & Biostatistics (BBS) team is focused on the development and application of computational methods and bioinformatics pipelines for working with different types of high-throughput data arising from modern experimental technologies. Our objective is to facilitate the discovery of cancer biomarkers through integrative analysis of multiple biological and clinical data types, and to develop these biomarkers and associated computational tools to inform clinical decision-making and improve patient outcomes.

We work with experimental data produced by other NBC teams, including sequencing data from patient tissue and liquid biopsies, as well as patient-derived pre-clinical models, either from snapshot profiling or longitudinal studies. This data includes multiple omics layers: genomics, transcriptomics, proteomics and epigenomics, measured at different resolutions (bulk, single-cell and spatial). We also leverage the wealth of data stored in large-scale open repositories (TCGA, ICGC, etc). We develop and apply bioinformatics pipelines, and statistics/machine learning approaches to process and analyse these data, to characterise and further our understanding of tumour initiation and progression, and to develop molecular signatures as clinically relevant biomarkers (e.g. for diagnosis, prognosis and treatment response).

Ongoing projects include studies of circulating tumour DNA (liquid biopsies) with the objective of cancer type identification from somatic mutations or revealing the cancer type for patients with cancer of unknown primary from DNA methylation, as well as detailed analysis of cancer cell plasticity during metastatic spread at the level of single cell transcriptome.

The team is highly collaborative, working closely with the other NBC teams, clinicians and external partners. The expertise of the team is diverse, covering computational biology, bioinformatics, biostatistics, machine learning and software engineering. In addition to pipeline/tool development and data analysis, the team also collaborates with NBC lab scientists to ensure appropriate experimental design, provide statistical support and training, and develop user-friendly interactive tools that enable non-bioinformaticians to explore data and perform some of their own data analysis.  

Across all our work, we aim to produce robust and reproducible workflows, and we endeavour to make our pipelines/tools freely available for use by the wider research community.