Testimonials from CGAT Fellows

“CGAT was a great opportunity for me. Having just finished my PhD I was not ready to be an independent researcher as I felt I required much more training in the analysis of large datasets, as well as in statistics and genome biology. Having had no ‘real’ experience using linux or python when I arrived, I found the training to be challenging, with a very steep learning curve. However, the technical ability that the senior scientists possess meant that the support was always there, and there was nothing that I wanted to do that couldn’t be achieved. In addition, the framework in which CGAT works in terms of computational infrastructure and code organisation is very impressive and will serve as a model for me in my future career as a computational biologist.

In addition to technical support, the capacity that CGAT has for funding outside training has facilitated a deeper understanding of methods and statistics (through course attendance) and biology in general (through conferences).

The CGAT model has also provided me with key skills required for collaborations. Although daunting at first, the opportunity to lead on high quality research projects with leading academics is invaluable. With the biological insights and rigour of the senior scientists, projects have been able to proceed towards interesting conclusions and publication preparation.

The exposure that CGAT has provided in various NGS techniques and applications has also aided me in deciding on my future career path. I have become increasingly interested in the human microbiome and how it interacts with the environment to cause disease. With the computational and collaborative skills that I have acquired over this time, I am confident that I can pursue this field of research.”

Dr Nicolas Ilott, Genomics Training Fellow (joined January 2011)

“I have been with CGAT for slightly over a year now. Although I came from an experimental background, I wasn’t completely new to computational analysis when I started. My computational work, however, was rudimentary, naive and laborious. How could I convince anyone else to believe in my work when I didn’t have any confidence in it myself! Through working on collaborative projects in a supportive environment CGAT has given me the space and time I needed to develop my skills, and to become familiar with the ins and outs of the various techniques while knowing that mistakes will be caught and corrected. Also, via the opportunity to take courses, I have been able to fill the holes in my knowledge, particularly with regard to my statistics. Together these benefits have given me the confidence to tackle computational problems, and have strengthened my belief in my own work.”

Dr Ian Sudbery, Genomics Training Fellow (joined November 2011)


“I joined CGAT from a broad biological background, but with an overriding interest in the relationship between nutrition, fitness, and disease. During my PhD I studied the nutritional ecology of marine herbivorous fishes and, amongst other things, considered the relationship between diet and the gut microbial environment.

Much of my previous experience is directly transferrable to my new field and applicable to medical research. However, aside from a CGAT fellowship, I do not know of any other opportunity that would have enabled me to so effectively combine my existing interests with such a relevant and useful field as computational genomics.

For me, the principal advantage of CGAT over other similar career-stage opportunities is its ability to combine training with active research. The individual nature of the training means that I’m able to focus specifically on topics relevant to my existing and future research interests. The opportunity to combine training with collaborative research is only possible because of the expertise and support available both within CGAT and within the wider research environment with which it is integrated.

Prior to joining CGAT I came to recognise that advances in high-throughput sequencing technologies have the potential to make a major contribution to the areas of research in which I am interested. However, I was also aware that my background precluded me from making full use of such technologies. I am using my time at CGAT to extend my research experience, so that in future I may enter into productive collaborations and, ultimately, direct my own research.”

Dr Jethro Johnson, Genomics Training Fellow (joined April 2012)

“I came to realise that, compared to reliance on external bioinformatic services, an analysis done by someone who understands both the experiment and its scientific background can result in much better insight. However, I also became aware of the limitations of my “self-taught” approach and my need for further computational training. CGAT has provided me with a unique opportunity to acquire new computational and statistical skills, while still building on my experimental expertise and research interests.

In the future, I would like to establish my independent research career, where I hope to utilise the large amount of data already available in genomic datasets, as well as both established and new experimental collaborations, to drive new hypotheses in transcriptional research. I believe my experience with CGAT will give me the best possible chance of achieving this, thanks to both the training programme and the experience of a wide range of NGS approaches that I gain while working on projects.

I really appreciate the intellectual environment at CGAT, where members not only help each other in acquiring computational skills, but also benefit from sharing their diverse range of expertise in various areas of biomedical research.”

Dr Martin Dienstbier, Genomics Training Fellow (joined September 2012)

“I joined CGAT to develop programming skills and gain expertise in genome data analysis. I have a background in clinical medicine and functional genomics and aim to bridge these areas. CGAT has met and exceeded my expectations so far. It has the necessary resources, environment and experience in place to make a very steep learning curve an enjoyable challenge instead of a barrier. Its focus on gaining practical computational skills while interpreting the broader implications of key biological experiments makes it ideal for training, both scientifically and technically. I would like to pursue an independent career in academic research after the fellowship and CGAT is an ideal launch pad for this.”

Dr. Antonio J. Berlanga-Taylor, Genomics Training Fellow (joined October 2012)

“I joined CGAT on 8th October 2012 because I wanted to learn how to use computational tools and statistics to derive biological meaning from large next-generation sequencing datasets. My background is in human disease genetics. I completed my PhD at the Wellcome Trust Sanger Institute studying the genetics of type 2 diabetes, obesity and related metabolic traits and my first post-doc at the UCL Institute of Neurology studying the genetics of neuromuscular diseases. When I started my career, next-generation sequencing was still in its infancy and not widely used whereas now it is the most powerful approach used for identifying novel and known human disease genes and mutations. Moreover, a variety of types of next-generation sequencing data such as RNAseq data and ChIPseq data are also beginning to be applied to the problem of human disease aetiology and elucidating pathological mechanisms. One of the challenges facing medical geneticists will be the interpretation of such vast amounts of data. At CGAT I am hoping to familiarise myself with next-generation sequencing technology and analysis and to learn how to interrogate these datasets to discover how the genome, and its interaction with the environment, gives rise to human phenotypic variation, in particular brain-related traits.

Before joining CGAT I had limited experience of informatics and statistics and limited opportunities to gain sufficient depth of knowledge in these areas. During my first two months at CGAT I have made a lot of progress learning the Python programming language and some powerful unix command-line tools. I have also started to study some stand-alone OU statistics modules. I am finding the environment at CGAT is extremely conducive to developing these skills because time is allotted for training purposes and I am surrounded by approachable experts in computational biology. Regular training meetings with the leaders of CGAT and Professor Chris Ponting enable me to discuss my training needs in the context of my career goals, and how these needs can be met. Once my informatics skills are sufficient I will start to work on one or more projects with the groups collaborating with CGAT. This will involve communicating effectively with collaborators and taking joint responsibility for the direction of the project. I will need to think about how the resources at CGAT (including computational expertise and infrastructure) can be used to add value to the data received. Weekly lab meetings will provide me with a forum to present and discuss my project with other members of CGAT and the MRC Functional Genomics Unit and to discover what other science is going on in the unit. My training budget also allows me to attend other meetings and conferences outside the unit enabling me to keep in touch with progress in my field and communicate with potential future collaborators.

In conclusion, I think CGAT affords a unique opportunity for someone from a biological background to gain the expertise necessary to use new, powerful technologies to answer the biological questions that interest them.”

Dr Katherine Fawcett, Genomics Training Fellow (joined October 2012)