The effects of common genetic variation and non-genetic factors on the risk of cardiomyopathy and heart failure in at risk populations
Breast cancer Cancer of unknown primary Childhood solid cancers Colorectal cancer Glioma Haematological malignancies Head and neck cancer Lung cancer Melanoma Neuroendocrine tumours Ovarian and endometrial cancer Pan cancer (across cancers) Prostate cancer Renal (kidney) cell carcinoma Sarcoma Testicular cancer Upper gastrointestinal cancer
Project TitleProject Lead Project Date
Research projects for Electronic health records
Role of Infections and autoimmune disorders in Schizophrenia and associated genetic determinants in HLA genes
Prediction of Pan-cancer Critical Care Outcomes
Assessing the genetic contribution to disease heterogeneity in selected neurological diseases.
Pan-cancer analysis of genetic and clinical factors in early detection, prognosis and outcomes
Feasibility analyses to evaluate how Genomics England can support a Full RWE Study in unresectable and metastatic NSCLC with HER2 variants
Machine Learning Enabled Patient Insights in Neurological Diseases
Overall Statistics and Summary Information for GEL data for Project Development
Machine Learning Enabled Patient Insights in Parkinson’s Disease
The Genetics of Symptom Severity in COVID-19 Infections
Towards better shielding of rare disease patients during COVID-19 pandemic via data-driven fine management
Methodology of linking and analysing real world genomics and clinical outcomes data
Multi-view learning for pan-cancer analysis on Genomics England (GeL), Genomic and Clinical, data
An EHR-wide association study on all cancers in Genomics England (GeL)
The Genomics England biobank resource with phenotyping and genomic data: A capacity building tutorial with a focus on glioma cancer
Co-morbidity and trajectory for carriers of clinically significant variants.
Association of health characteristics, comorbidities and tumour mutational burden with outcomes in patients treated with chemotherapy and immunotherapy
Project Title: Using neuropsychiatric comorbid to identify pathogenic ID variants and understand effect of variants on neurodevelopmental trajectories.
Impact of mental health comorbidity in Genomics England participants
Identifying subtypes of Glioblastoma (GBM) patients via Network Approaches