Projects
Applied statistical genetics- The Applied Statistical Genetics group, led by Eleftheria Zeggini, aims to help identify the genetic determinants of complex human traits by using next-generation association studies to detect novel disease loci
Cancer genome project- Mike Stratton, Andy Futreal, Peter Campbell and Ultan McDermott use sequence and high-throughput mutation detection to identify genes critical in the development of cancers
Genetic epidemiology- Manj Sandhu's team explores genomic diversity and its impact on infectious and cardiometabolic risk factors among populations
Genetics of common neurological diseases- Aarno Palotie's team identifies genes and variants contributing to neurological diseases to better understand pathogenic mechanisms
Genetics of complex traits in humans- Panos Deloukas and his team explore common disease and variable response to drugs through large-scale genome-wide association studies
Genomic mutation and genetic disease- Matt Hurles' team aims to elucidate the genetic architecture of developmental disorders, and characterise mutation processes in mammalian genomes
Genomics of quantitative variation- Nicole Soranzo's team uses quantitative intermediate traits to unravel novel mechanisms underlying common, complex diseases
Human evolution- Chris Tyler-Smith's team investigates genetic variation in apes and humans to understand our evolutionary past and its implications for our current health
Metabolic disease group- Inês Barroso's team identifies genes linked to type 2 diabetes and obesity to better understand the aetiology of the diseases
Molecular cytogenetics- Nigel Carter's team aims to detect rare structural changes in chromosomes to understand the causes of certain inherited disorders
Regulatory evolution in mammalian tissues- Duncan Odom's group compares how transcription and transcriptional regulation vary during evolution, and the implications this regulatory plasticity has for diseases such as cancer.
Statistical and computational genetics- Jeffrey Barrett's team elucidates the genetic basis of common human disease using statistical and computational approaches
Statistical genetics- Carl Anderson's team aims to understand common human disease by identifying and characterising mutations underlying disease susceptibility
Collaborations and resources
1000 Genomes Project- Sequences the genomes of a large number of people, to provide a comprehensive resource on human genetic variation
arcOGEN- Aims to find genetic determinants of osteoarthritis and elucidate the genetic architecture of the disease
BASIS- Aims to genetically characterise the most common class of breast cancer (known as ER+, HER2-)
Bloodomics- Aims to discover genetic markers for the prediction of thrombus formation and to design better anti-thrombotics for improved prevention and treatment
Cardiogenics- Aims to discover genetic variations leading to coronary artery disease, thereby uncovering the underlying disease mechanisms and helping to develop new treatments
Copy Number Variation project- Investigates gains and losses of large chunks of DNA sequence to understand the contribution of CNV to the common, complex diseases
COSMIC- Stores and displays somatic mutation information and related details, and contains information relating to human cancers
DECIPHER- Collects and displays clinical information about chromosomal microdeletions, duplications, insertions, translocations and inversions
Deciphering Developmental Disorders (DDD)- Advances clinical genetic practice for children with developmental disorders by applying the latest microarray and sequencing methods while addressing key ethical challenges
ENCODE and GENCODE- Aims to identify all functional elements across the entire human genome sequence and annotate evidence-based gene features at a high accuracy
Ensembl genome browser- Produces genome databases for vertebrates and other eukaryotic species and makes this information freely available online
Genome analysis pipelines- The pipelines are dedicated to high-throughput sample logistics, genome-wide data generation, PCR target preparation for re-sequencing, genotyping, data quality control, analysis and storage
Genome Reference Consortium (GRC)- Aims to ensure that the human, mouse and zebrafish reference assemblies are biologically relevant by closing gaps, fixing errors and representing complex variation
International HapMap Project- Describes common patterns of human DNA sequence variation and helps researchers to identify genes affecting health, disease, and responses to drugs and environmental factors
International Serious Adverse Events Consortium- Aims to identify DNA-variants useful in predicting the risk of drug-related serious adverse events
HAVANA- The HAVANA group provides the manual annotation of human, mouse, zebrafish and other vertebrate genomes that appears in the Vega browser
InterAct- Discovers how genetic and lifestyle behavioural factors interact to influence the risk of type 2 diabetes and investigates how to prevent development of the condition
International Cancer Genome Consortium- Aims to obtain comprehensive descriptions of genomic, transcriptomic and epigenomic changes in tumor types and/or subtypes of importance across the globe
Scat (Bone Cancer Trust)- Aims to sequence osteosarcoma genomes in order to identify new osteosarcoma cancer genes and develop new clinically applicable strategies for monitoring of patient disease burden
WTCCC- Looks at genetic variation in the human population and the role this plays in disease susceptibility
UK10K- Aims to understand the link between low-frequency and rare genetic changes, and human disease by studying the genetic code of 10,000 people
