The Centre recognises that to complete the cycle of discovery, findings from trials need to be enriched through investment in bioinformatics support. The Bioinformatics Core is an entity developed between the Centre, the Department of Oncology and the Oxford Institute, which provides expertise in cancer genomics, next generation sequencing, statistical genetics and metabolomics, and functional and clinical genomics.
The Bioinformatics Core is available to all Centre Members. Find out more from the team, below.
We are a computational biology group within the CRUK Oxford Centre. We are located in on the Old Road Campus, our office is in the basement of the ORCRB (The Green Building), room 50.B. The mission of the Core is to develop collaborative research projects and to maintain state of the art computational approaches to cancer genomics, proteomics and clinical trials, as well as to ensure coordination of experimental and analytics approaches through the different phases of a research project.
We work on projects of all sizes and are happy to discuss anything from a long-term collaboration on a data-rich project to a problem that we can help solve in less than a week!
Areas of Expertise
Our research couples state of the art computational and experimental techniques to interpret the genotype-phenotype map in cancer, as well as to delineate mechanisms of tumor growth, metastasis, and resistance to treatment.
- Whole genome/exome sequencing and resequencing data analysis
- Genetic variants calling and functional annotation
- Copy Number Variation, Structural Varaition analysis
- De novo genome/transcriptome assemblies
- RNASeq: differential expression, alternative isoform expression
- ChIPSeq: peak calling algorithms, annotate bound regions with gene information
- Ribosome protection/footprint assay analysis
- Methods to map protein–RNA binding sites in vivo e.g. HITS-CLIP, PAR-CLIP, iCLIP
- Nanopore and single cell sequencing data analysis
Integrative analysis of large-scale genomic datasets: next generation sequencing data, microarray experiments, whole genome RNAi screens and mass spectrometry data.
- *omics data mapping and integration, including expression, epistatic, knock-out, RNAi, proteomics, splicing, RNASeq, CGH, and GWAS
- Identification of related and orthogonal datasets
- Network and pathway analysis
- Gene Ontology and pathway over-representation analysis
- Exploratory data analysis, including but not limited to TCGA and ICGC data mining
- Design and analysis of high content tissue and cellular image–based screens
- miRNA: Characterisation and quantification of small regulatory RNA moleclues
- Expertise on experimental design
- Conduct experiment quality control
- Development of novel statistical analysis methods
- Statistical analysis of behavioral or other complex data sets
- Survival analysis
- Statistical Genetics (population genetics, stratification and imputation)
- Clinical Studies
- Mathematical Modelling
- Evaluate analysis software for novel high-throughput applications
- Software and Database development and maintenance
- Generate figures for presentation and publication
- Composition of biostatistics methodology sections for grant proposals and publications
- Seminars and workshops on bioinformatics/biostatistical methods
Meet the team
Dr. Anastasia Samsonova
I received my Ph.D. degree from the University of Cambridge and the EMBL-EBI, where I had been working in the Functional Genomics Team. Prior to joining the Core, I was a senior postdoctoral research fellow in the laboratory of Professor Norbert Perrimon at the Department of Genetics, Harvard Medical School.
I am keen to work closely with biologists and clinicians, to establish collaborations in interdisciplinary research projects, as well as to integrate of advancements in genomics research, computational and molecular biology with clinical applications.
Dr. Alexander Kanapin
I graduated from the Moscow University (Russia) and got my PhD in biophysics in Russian Academy of Sciences. Before joining the Department I worked at WTCHG, CSHL, Ontario Institute for Cancer Research (Canada), running projects on cancer genome analysis with machine learning algorithms. I also spent significant part of my career at European Bioinformatics Institute as one of key developers and managers of InterPro - integrated database for protein domains and functional sites. I developed and managed high-throughput analytical pipelines for Oxford-Illumina WGS500 initiative.
Dr. Anas Ahmad Rana
I come to oncology after graduating with a Physics degree from Imperial College London and a P.h.D. from the University of Warwick of which I spent two years at the Netherlands Cancer Institute (NKI Amsterdam) working on heterogeneity in cell populations undergoing transition.
I have a keen interest in a collaborative approach to integrative omics data and the interesting challenges posed by heterogeneity in this context.