A5075505965- Genetic Associations and Epidemiology
- Bioinformatics and Genomic Networks
- Image Processing and 3D Reconstruction
- Machine Learning and Data Classification
- Gene expression and cancer classification
- Genetic Mapping and Diversity in Plants and Animals
- Genetic and phenotypic traits in livestock
- Multiple Myeloma Research and Treatments
- Fault Detection and Control Systems
- T-cell and B-cell Immunology
- interferon and immune responses
- Single-cell and spatial transcriptomics
- NF-κB Signaling Pathways
- Reservoir Engineering and Simulation Methods
- CRISPR and Genetic Engineering
- Quinazolinone synthesis and applications
- Chronic Kidney Disease and Diabetes
- Research Data Management Practices
- Transcranial Magnetic Stimulation Studies
- RNA and protein synthesis mechanisms
- Diabetes Management and Research
- Data Analysis with R
- RNA regulation and disease
- Pain Management and Treatment
- Scientific Computing and Data Management
Age UK
2023-2024
MRC Biostatistics Unit
2019-2022
Royal Hobart Hospital
2020-2022
University of Cambridge
2020-2022
MRC Laboratory of Molecular Biology
2020
The Royal Melbourne Hospital
2000
Spatial heterogeneity influences the distribution, prevalence, and diversity of haemosporidian parasites. Previous studies have found complex patterns prevalence with respect to habitat characteristics parasite genotype, their interactions, but there is little information regarding how parasitemia intensity co-infections may vary in space. Here, using both molecular methods microscopy, we report an analysis variation avian parasites (Plasmodium Haemoproteus species) 2 common African birds...
Abstract Background Drug targets with genetic evidence are expected to increase clinical success by at least twofold. Yet, translating disease-associated variants into functional knowledge remains a fundamental challenge of drug discovery. A key issue is that the vast majority complex disease associations cannot be cleanly mapped gene. Immune enriched within regulatory elements found in T-cell-specific open chromatin regions. Results To identify genes and molecular programs modulated these...
Genome Wide Association Studies (GWAS) have successfully identified thousands of loci associated with human diseases. Bayesian genetic fine-mapping studies aim to identify the specific causal variants within GWAS responsible for each association, reporting credible sets plausible variants, which are interpreted as containing variant some "coverage probability". Here, we use simulations demonstrate that coverage probabilities over-conservative in most situations. We show this is because data...
Article1 April 2020Open Access Transparent process Resolving mechanisms of immune-mediated disease in primary CD4 T cells Christophe Bourges Cambridge Institute Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, Campus, University Cambridge, UK Department Medicine, School Clinical Addenbrooke's Hospital, Search for more papers by this author Abigail F Groff Stem Cell Regenerative Biology, Harvard University, MA, USA Oliver S Burren Chiara Gerhardinger Kaia...
Genome-wide association studies (GWAS) have identified thousands of genetic variants that are associated with complex traits. However, a stringent significance threshold is required to identify robust associations. Leveraging relevant auxiliary covariates has the potential boost statistical power exceed threshold. Particularly, abundant pleiotropy and non-random distribution SNPs across various functional categories suggests leveraging GWAS test statistics from related traits and/or genomic...
ABSTRACT Deriving mechanisms of immune-mediated disease from GWAS data remains a formidable challenge, with attempts to identify causal variants being frequently hampered by linkage disequilibrium. To determine whether could be identified via their functional effects, we adapted massively-parallel reporter assay for use in primary CD4 T-cells, key effectors many diseases. Using the results guide further study, provide generalisable framework resolving non-coding associations – illustrated...
Abstract Genome Wide Association Studies (GWAS) have successfully identified thousands of loci associated with human diseases. Bayesian genetic fine-mapping studies aim to identify the specific causal variants within GWAS responsible for each association, reporting credible sets plausible variants, which are interpreted as containing variant some “coverage probability”. Here, we use simulations demonstrate that coverage probabilities over-conservative in most situations. We show this is...
Abstract Drug targets with human genetic evidence are expected to increase clinical success by at least two-fold. Yet, translating disease-associated variants into functional knowledge remains a fundamental challenge of early drug discovery. A key issue is that, currently, the vast majority complex disease associations cannot be cleanly mapped gene. Immune enriched within regulatory elements, such as distal enhancers, found in T cell-specific open chromatin regions. To identify genes and...
Genome-wide association studies (GWAS) are limited in power to detect associations that exceed the stringent genome-wide significance threshold. This limitation can be alleviated by leveraging relevant auxiliary data, such as functional genomic data. Frameworks utilising conditional false discovery rate have been developed for this purpose, and shown increase GWAS whilst controlling rate. However, methods currently only applicable continuous data cannot used leverage with a binary...
The complexity of analysis pipelines in biomedical sciences poses a severe challenge for the transparency and reproducibility results. Researchers are increasingly incorporating software development technologies methods into their analyses, but this is quickly evolving landscape teams may lack capabilities to set up own complex IT infrastructure aid reproducibility. Basing reproducible research strategy on readily available solutions with zero or low set-up costs whilst maintaining...
Abstract Summary GWAS discovery is limited in power to detect associations that exceed the stringent genome-wide significance threshold, but this limitation can be alleviated by leveraging relevant auxiliary data. Frameworks utilising conditional false rate (cFDR) used leverage continuous data (including and functional genomic data) with test statistics have been shown increase for whilst controlling FDR. Here, we describe an extension cFDR framework binary (such as whether SNPs reside...
Abstract Genome-wide association studies (GWAS) have identified thousands of genetic variants that are associated with complex traits. However, a stringent significance threshold is required to identify robust associations. Leveraging relevant auxiliary covariates has the potential boost statistical power exceed threshold. Particularly, abundant pleiotropy and non-random distribution SNPs across various functional categories suggests leveraging GWAS test statistics from related traits and/or...
Abstract Identifying genetic determinants for longitudinal changes in albumin excretion individuals with type 1 diabetes may help identify those that are predisposed to renal, retinal and cardiovascular complications. Most studies have focussed on predisposition diabetic kidney disease used cross-sectional measurements of urinary excretion, but limited success. Here, we utilise the wealth data bio-samples collected from cohorts childhood-onset followed over last 30 years describe a novel...