This project will build on a major public database of disease genetics (GWAS Central,
https://www.gwascentral.org) to provide new methods and interfaces to: (a) visually and programmatically interrogate GWAS Central data using a range of research and clinical terms; and (b) integrate and compare GWAS Central data with similar data from other public sources including those of other species. Possible extensions include: (i) GWAS data publishing and linking via the semantic web of ‘Linked Data’; (ii) natural language processing of GWAS publications to extract genotype and phenotype information; and (iii) developing and implementing an application ontology for GWAS summary-level metadata.
More specifically, genome-wide association studies (GWAS) identify genetic variants associated with phenotypes. The comprehensive and widely used GWAS Central database (Beck et al, 2014) collates published summary-level GWAS findings from thousands of studies. The phenotype descriptions in GWAS Central are standardised with the use of publicly available “ontologies”. Ontologies are controlled vocabularies where the terms are precisely defined and related to each other in meaningful ways, and they are widely used by bioinformaticians to integrate and compare heterogeneous datasets.
GWAS Central currently uses ontologies that have been developed with a research-focus. However, greater integration with clinical datasets will be achieved by additionally using ontologies that have a clinical-focus, such as those used by the NHS. Furthermore, GWAS data will be integrated with genetic data from other mammalian species, such as mouse, by mapping the human phenotype to the mouse equivalent. International efforts to map between ontologies provide a foundation for enabling this.
Entry requirements
The ideal applicant will have a detailed understanding of Computer Science or Bioinformatics and hold/or expect to obtain a UK Bachelor Degree 2:1 or better in a relevant subject. Applicants with degrees in Biological Sciences would need to demonstrate advanced computing skills including working with databases (relational or non-relational) and have the ability to code original applications in languages commonly used in bioinformatics, such as Python or Perl.
The University of Leicester English language requirements apply where applicable:
https://le.ac.uk/study/research-degrees/entry-reqs/eng-lang-reqs/ielts-65 How to apply
You should submit your application using our online application system:
https://www2.le.ac.uk/research-degrees/phd/applyphd Apply for a PhD in Genetics
In the funding section of the application please indicate you wish to be considered for a CLS/GGB Studentship
In the proposal section please provide the name of the supervisor and project title. You do not need to submit a proposal but we do require a personal statement detailing why you are interested in the project.
Project / Funding Enquiries
You are encouraged to make informal enquiries in the first instance, by contacting Dr Tim Beck
[email protected] Application enquiries to
[email protected] Closing date for applications 29 March 2019
References
Beck T, Hastings RK, Gollapudi S, Free RC, Brookes AJ. GWAS Central: a comprehensive resource for the comparison and interrogation of genome-wide association studies. Eur J Hum Genet. 2014 Jul;22(7):949-52.
