Professor Jean-Baptiste Cazier PhD

Professor Jean-Baptiste Cazier

Institute of Cancer and Genomic Sciences
Chair of Bioinformatics
Programme Director, Online MSc in Bioinformatics

Contact details

Institute of Cancer and Genomic Sciences
Haworth Building
University of Birmingham
B15 2TT

Jean-Baptiste Cazier is a Professor of Bioinformatics with interest across the broad spectrum of Computational and Mathematical modelling of natural phenomena.

He has three main area of interest: Cancer Genetics, Population Genetics, Swarming and Metabonomics.

His life-long goal is to integrate all his eclectic, and ever expending, fields of interest.

Jean-Baptiste was part of a team of colleagues who launched the UK Coronavirus Cancer Monitoring Project – a national project which uses rapid integration of data from across the UK to deliver in near-real-time information to clinicians and cancer patients about how anti-cancer treatments affect COVID-19. This close collaboration between oncologists and the team of data scientists that he led through the Centre for Computational Biology illustrates how expert use of data can have an immediate impact on patients’ lives.


  • PhD in Trädgårdsproduktlära, SLU/Lund, Sweden, 2000
  • DEA en Mathématiques Appliquées, spécialisé dans les Equations aux Dérivées Partielles (EDP), Université Joseph Fourier, Grenoble, France, 1995
  • Ingénieur-Maitre en Mathématiques Appliquées et Industrielles, Université Joseph Fourier, , Grenoble, France 1994


Originally trained in mathematical modelling, Jean-Baptiste Cazier worked on various applications of partial differential equations until he reached the area of human genetics. He was introduced to this fast-evolving field in an academic spirit of research and excellence in Iceland at deCode Genetics, developing further methods combining linkage and case-control association to identify genes responsible for common complex diseases. He led a group in charge of diseases from cancer to asthma within the Statistics Department and found success in the association of loci to osteoporosis and prostate cancer, as well as in population genetics.

While employed at the LRI by CRUK, he worked alongside experts in most aspects of bioinformatics and biostatistics in the context of cancer. Simultaneously affiliated with QMUL, he collaborated with scientists and clinicians on genome-wide association, copy number variations or high-throughput sequencing, especially of colorectal cancer and leukaemia which led to the identification of many genomic susceptibility variants conferring higher, susceptibility and progression, risk of various cancers.

Joining the Wellcome Trust Centre for Human Genetics in Oxford, he collaborated with clinicians working on diverse medical conditions from central nervous system to cardiovascular diseases. In this latter context he developed new methods to perform metabonome quantitative trait association using Nuclear Magnetic Resonance profiles in animal models. The human side of the project involved genome-wide association in a Middle Eastern cohort, which required novel population genetics analysis. These further studies in population stratification and admixture mapping to perform more accurate analysis across heterogeneous cohorts led to new analytical methods being developed in collaboration with the Department of Statistics. These developments were made possible thanks to the academic settings with the supervision of DPhil students and postdocs in liaison with their mentors. This broad range of work sometimes leads to the development of interactive tools such as the Genome Recurrent Event ViEwer (GREVE). After serving as joint acting Head of the Bioinformatics and Statistical Genetics Core, Jean-Baptiste headed the Statistical Genetics and Functional Analysis group. He then supervised the development of analytical approaches and tools for the analysis of whole genome sequencing projects (WGS500) with a special focus on immune disorders and cancers. This latest project successfully brings afore new variants functionally associated with the development of diseases.

He then joined the Department of Oncology to create a Bioinformatics group to both provide support to the department and lead independently funded research. He commissioned a dedicated High Performance Computing solution and designed an entire Bioinformatics Course while assembling a world-class team. He continued being involved in the cancer part of the WGS500 by publishing the first tumour-based project, identifying new mutations and clinicopathological associations with mutation burden in Bladder Cancer.

In 2014, Jean-Baptiste Cazier joined the University of Birmingham taking up the new chair of Bioinformatics to create theCentre for Computational Biology. This university-wide effort aims to promote excellence in Computational Biology, Systems Biology, and Bioinformatics across the range of fundamental and applied sciences, in both the University and allied Health Care arenas.


McCarthy, D.J. et al. Choice of transcripts and software has a large effect on variant annotation. Genome Med 6, 26 (2014).

Cazier, J.B. et al. Whole-genome sequencing of bladder cancers reveals somatic CDKN1A mutations and clinicopathological associations with mutation burden. Nat Commun 5, 3756 (2014).

Waller-Evans, H. et al. Nutrigenomics of high fat diet induced obesity in mice suggests relationships between susceptibility to fatty liver disease and the proteasome. PLoS One 8, e82825 (2013).

Fernandez-Rozadilla, C. et al. A genome-wide association study on copy-number variation identifies a 11q11 loss as a candidate susceptibility variant for colorectal cancer. Hum Genet 133, 525-34 (2014).

Ulahannan, D., Kovac, M.B., Mulholland, P.J., Cazier, J.B. & Tomlinson, I. Technical and implementation issues in using next-generation sequencing of cancers in clinical practice. Br J Cancer 109, 827-35 (2013).

Fernandez-Rozadilla, C. et al. A colorectal cancer genome-wide association study in a Spanish cohort identifies two variants associated with colorectal cancer risk at 1p33 and 8p12. BMCGenomics 14, 55 (2013).

Sengupta, N. et al. Analysis of colorectal cancers in British Bangladeshi identifies early onset, frequent mucinous histotype and a high prevalence of RBFOX1 deletion. Mol Cancer 12, 1 (2013).

Palles, C. et al. Germline mutations affecting the proofreading domains of POLE and POLD1 predispose to colorectal adenomas and carcinomas. Nat Genet 45, 136-44 (2013).

Davies, J.L. et al. A novel test for gene-ancestry interactions in genome-wide association data. PLoS One 7, e48687 (2012).

Cazier, J.B., Holmes, C.C. & Broxholme, J. GREVE: Genomic Recurrent Event ViEwer to assist the identification of patterns across individual cancer samples. Bioinformatics 28, 2981-2 (2012).

Su, Z. et al. Common variants at the MHC locus and at chromosome 16q24.1 predispose to Barrett's esophagus. Nat Genet 44, 1131-6 (2012).

Dunlop, M.G. et al. Common variation near CDKN1A, POLD3 and SHROOM2 influences colorectal cancer risk. Nat Genet 44, 770-6 (2012).

Fernandez-Rozadilla, C. et al. Pharmacogenomics in colorectal cancer: a genome-wide association study to predict toxicity after 5-fluorouracil or FOLFOX administration. Pharmacogenomics J 13, 209-17 (2013).

Knight, S.J. et al. Quantification of subclonal distributions of recurrent genomic aberrations in paired pre-treatment and relapse samples from patients with B-cell chronic lymphocytic leukemia. Leukemia 26, 1564-75 (2012).

Spain, S.L. et al. Refinement of the associations between risk of colorectal cancer and polymorphisms on chromosomes 1q41 and 12q13.13. Hum Mol Genet 21, 934-46 (2012).

Cazier, J.B. et al. Untargeted metabolome quantitative trait locus mapping associates variation in urine glycerate to mutant glycerate kinase. J Proteome Res 11, 631-42 (2012).

Tomlinson, I.P. et al. Multiple common susceptibility variants near BMP pathway loci GREM1, BMP4, and BMP2 explain part of the missing heritability of colorectal cancer. PLoS Genet 7, e1002105 (2011).

Carvajal-Carmona, L.G. et al. Fine-mapping of colorectal cancer susceptibility loci at 8q23.3, 16q22.1 and 19q13.11: refinement of association signals and use of in silico analysis to suggest functional variation and unexpected candidate target genes. Hum Mol Genet 20, 2879-88 (2011).

Pontoizeau, C. et al. Broad-ranging natural metabotype variation drives physiological plasticity in healthy control inbred rat strains. J Proteome Res 10, 1675-89 (2011).

Wrench, D. et al. SNP rs6457327 in the HLA region on chromosome 6p is predictive of the transformation of follicular lymphoma. Blood 117, 3147-50 (2011).

Houlston, R.S. et al. Meta-analysis of three genome-wide association studies identifies susceptibility loci for colorectal cancer at 1q41, 3q26.2, 12q13.13 and 20q13.33. Nat Genet 42, 973-7 (2010).

Purdie, K.J. et al. High-resolution genomic profiling of human papillomavirus-associated vulval neoplasia. Br J Cancer 102, 1044-51 (2010).

Cazier, J.B. & Tomlinson, I. General lessons from large-scale studies to identify human cancer predisposition genes. J Pathol 220, 255-62 (2010).

Spain, S.L. et al. Colorectal cancer risk is not associated with increased levels of homozygosity in a population from the United Kingdom. Cancer Res 69, 7422-9 (2009).

Carvajal-Carmona, L.G. et al. Common variation at the adiponectin locus is not associated with colorectal cancer risk in the UK. Hum Mol Genet 18, 1889-92 (2009).

O'Shea, D. et al. Regions of acquired uniparental disomy at diagnosis of follicular lymphoma are associated with both overall survival and risk of transformation. Blood 113, 2298-301 (2009).

Purdie, K.J. et al. Single nucleotide polymorphism array analysis defines a specific genetic fingerprint for well-differentiated cutaneous SCCs. J Invest Dermatol 129, 1562-8 (2009).

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