Bioinformatics Core Director at The University of Sheffield
I am setting-up a Bioinformatics Core at The University of Sheffield. We will provide high-quality Bioinformatics service to assist researchers in the planning, analysis, visualisation and interpretation of their high-throughput data. We will also provide training courses on essential data analysis skills and more-specialised training in the analysis of NGS-related data.
Biography
2015 – 2017: Bioinformatics Training Co-ordinator, Cancer Research Uk, Cambridge Institute
2009 – 2015: Bioinformatics Analyst / Senior Bioinformatics Analyst, Cancer Research Uk Cambridge Institute
2005 – 2009: PhD (Oncology) University of Cambridge
2004 – 2005: Msc (Data Analysis, Networks and Nonlinear Dynamics) University of York
1999 – 2004: Bsc (Mathematics and Computer Science) University of York
I obtained my PhD in the Statistics and Computational Biology group of Simon Tavare at The University of Cambridge. As part of my thesis I developed open-source software for the analysis of Illumina microarray data, which is available through the Bioconductor project.
I joined the Bioinformatics Core at Cancer Research Uk Cambridge Institute and played a key role in the analysis of gene expression profiles as part of the METABRIC project, which identified and described new subtypes of breast cancer. I also participated in the pilot phases of the International Cancer Genome Consortium (ICGC) project by developing computational pipelines to process the whole-genome sequencing data from Oesophageal cancer patients.
During my time in the Bioinformatics Core I also developed a passion for teaching and commenced a role dedicated to organising and delivering Bioinformatics training courses, with the aim of empowering wet-lab scientists to begin to explore data for themselves and foster more-productive collaborations with Bioinformaticians.
I have a strong commitment to reproducible research and making my research outputs available to other researchers, and indeed members of the public who may have funded the research in the first place. For instance, I recently developed and deployed a Shiny application that allows interested parties to query various prostate cancer datasets.
In keeping with my open access principles, the code underlying the application is available via github and utilises data sets that can be downloaded from Bioconductor. I have also recently investigated technologies such as Galaxy and Docker to ease the deployment of software and facilitate reproducible research.
Research
High-throughput technologies such as next generation sequencing (NGS) can routinely produce massive amounts of data that can be used for tasks such as identifying biological samples with aberrant expression patterns or allow us to describe all variants in a genome. However, such datasets pose new challenges in the way the data have to be analyzed, annotated and interpreted which are not trivial and are daunting to the wet-lab biologist. My interests lie in making the analysis of high-throughput datasets accessible to the non-bioinformatician; via specialised training courses and by developing computational pipelines and workflow. I am currently exploring technologies that facilitate reproducible research and promote an open attitude to scientific research, and endeavour to make my talks, code, and analyses available whenever.
Publications
1. Dunning, M.J, Vowler, S.L., Lalonde, E., Ross-Adams. H,. Boutros, P., Mills, I.G., Lynch, A.G, and Lamb A.D., “Mining Human Prostate Cancer Datasets: The camcAPP Shiny App“ EBio Medicine 17, (2017)
2. Ross-Adams, H., Lamb, A.D., Dunning, M.J., Halim, S., Lindberg, J., Massie, C.M., Egevad, L.A., Russell, R., Ramos-Montoya, A., Vowler, S.L., Sharma, N.L., Kay, J., Whitaker, H., Clark, J., Hurst, R., Gnanapragasam, V.J, Shah, N.C, Warren, A.Y., Cooper, C.S., Lynch, A.G., Stark, R., Mills, I.G., Gronberg, H. and Neal, D.E., “Integration of copy number and transcriptomics provides risk stratification in prostate cancer: A discovery and validation cohort study“ EBio Medicine 2(9):1133-1144, (2015).
3. Weaver, J.M.J., Shannon, N., Lynch, A.G., Ross-Innes, C.S., Forshew, T., Barbera, M., Ong, C.J., Lao-Sirieix, P., Dunning, M.J., Smith, L., Smith, M., Carvalho, B., O’Donovan. M., Underwood, T., Murtaza, M., May, A.P., Grehan, N., Hardwick, R., Davies, J., Olomi, A., Aparicio, S., Rozenfeld, N., Eldridge, M., Caldas, C., Edwards, P.A.W., Tavare, S. and Fitzgerald, R.C. “Ordering of mutations in preinvasive disease stages of esophageal carcinogenesis” Nature Genetics epub ahead of print (2014) ?
4. Dawson, S.J., Tsui, D.W.Y, Murtaza, M., Biggs, H., Rueda, O.M., Chin, S.F., Dunning, M.J., Gale, D., Forshew, T., Mahler-Araujo, B., Rajan, S., Humphray, S., Becq, J., Halsall, D., Wallis, M., Bentley, D., Caldas, C. and Rosenfeld, N., “Analysis of Circulating Tumour DNA to Monitor Metastatic Breast Cancer” The New England Journal of Medicine 368:1199-1209, 2013 ?
5. Curtis, C., Shah S., Chin, S.F., Turashvili, G., Rueda, O.M., Dunning, M.J., Speed, D., Lynch, A.G., Samarajiwa, S., Y, Yuan., METABRIC Group et al “The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups.” Nature, 481(7381):389-93,2012 ?
6. Lynch, A.G., Chin, S.F., Dunning, M.J., Caldas, C., Tavare, S., and Curtis, C., “Calling sample mix-ups in cancer population studies” PLoS One, 7(8) e41815, 2012 ?
7. Ritchie, M.E., Dunning, M.J., Smith, M.L., Shi, W, and Lynch, A.G., “BeadArray expression analysis using bioconductor” PLoS Computational Biology 7(12) e1002276, 2011 ?
8. Dunning, M.J., Curtis, C., Barbosa-Morais, N.L., Caldas, C., Tavare, S. and Lynch, A.G., “The importance platform annotation in interpreting microarray data” Lancet Oncology 11(8):717, 2010 ?
9. Barbosa-Morais, N.L, Dunning, M.J., Samarajiwa, S.A., Darot, J.F.J., Ritchie, M.E., Lynch, A.G. and TavarE, S. “A re-annotation pipeline for Illumina BeadArrays: improving the interpretation of gene expression data” Nucleic Acids Research 38(3):e17, 2009 ?
10. Dunning, M.J., Barbosa-Morais, N.L, Lynch,. A.G., Tavare, S. and Ritchie, M.E. “Statistical issues in the analysis of Illumina data” BMC Bioinformatics 9:85, 2008 ?
11. Dunning, M.J. Smith, M.L., Ritchie, M.E. and Tavare, S. “beadarray: R classes and methods for Illumina bead-based data” Bioinformatics 23(16):2183-4
Teaching and Supervisions
2016/2017:
- An Introduction to Solving Biological Problems with R - Training Lead, Trainer
- Data Analysis and Visualisation in R - Training Lead, Trainer
- Analysis of publicly available microarray data - Training Lead, Trainer
- Introduction to visualising Next Generation Sequencing data with IGV - Training Lead, Trainer
- Introduction to Statistical Analysis - Training Lead, Trainer
- Analysis of RNA-seq data with Bioconductor - Training Lead, Trainer
- Avoiding data disasters - Best practices in Research Data Management for the Biological Sciences - Training Lead, Trainer
- Introduction to Linear Modelling with R - Training Lead, Trainer
- Beginners guide to version control with git - Training Lead, Trainer
- Experimental Design - Training Lead, Trainer
- Introduction to Scientific Figure Design - Training Lead, Trainer
2015/2016:
- Analysis of high-throughput sequencing data with Bioconductor - Training Lead, Trainer
- Introduction to Statistical Analysis - Training Lead, Trainer
- Beginners guide to version control with git - Training Lead, Trainer
- An Introduction to Solving Biological Problems with R - Training Lead, Trainer
- Data Analysis and Visualisation in R - Training Lead, Trainer
- Analysis of publicly available microarray data - Training Lead, Trainer
- Using Genome Browsers to visualise high-throughput data - Training Lead, Trainer
2014/2015:
- An Introduction to Solving Biological Problems with R - Training Lead, Trainer
- Analysis of high-throughput sequencing data with Bioconductor - Training Lead, Trainer
- Introduction to Statistical Analysis - Training Lead, Trainer
