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  VariantVisualiser: Ensuring precise diagnoses of genetic disorders through the development of intuitive software that facilitates the integration and visualisation of complex informatics with biological and clinical data.


   Department of Computer Science

  ,  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Rare diseases affect <1-in-2,000 people, but ~8,000 rare genetic diseases impact ~10% of births globally. These arise from variations in patients’ DNA sequences. To reach a diagnosis, an ecosystem of clinicians, journal publishers and databases must understand one another and agree on the specific variant(s) they are talking about. A standardised name is given to each variant so that associated diagnostic evidence can be shared. However, dataflow into clinical databases is hindered by incorrect naming of variants in the scientific literature which renders evidence undiscoverable. Additionally, there is no standardised way to record diagnostic evidence that clinicians use to classify variants as disease-causing, yielding disparities in the reliability of evidence. These seemingly minor issues contribute to ~3,000 children born annually in the UK who never receive a diagnosis. Consequently, families cannot access support they need, and up to 3,000 children die undiagnosed each year.

This proposal builds on substantial efforts of a Human Genome Organization committee which has proposed a unified professional-standard for representing genomic data which, when finalised, will be adopted world-wide. We will create visualisation software to enable the professional-standard in a framework intended to better communicate genetic data throughout the human genomics cimmunity. The framework captures precise names for variants and documents the clinical evidence used to classify them. We will upgrade the VariantValidator infrastructure to create the framework. We will then replace the existing VariantValidator interface with a new display, facilitating precise communication and interpretation of the stored clinical genomic data. Translation into tangible benefits will be facilitated by integrating of the resources into NHS training, and embedding resources into clinical pipelines, literature management systems and clinical databases. This holistic intervention will increase availability of diagnostic data enabling hundreds of thousands of children globally each year to receive a diagnosis.

Eligibility

Candidates are expected to hold (or be about to obtain) a minimum upper second-class honours degree (or equivalent) in an area/subject related to Bioinformatics or Computer Science. Programming skills in Python are essential, as is experience in SQL databases. An ideal candidate will also have experience or an interest in HTML, JavaScript, React JS.

Funding

At Manchester we offer a range of scholarships, studentships and awards at university, faculty and department level, to support both UK and overseas postgraduate researchers applying for competition and self-funded projects.

For more information, visit our funding page or search our funding database for specific scholarships, studentships and awards you may be eligible for.

Before you apply

We strongly recommend that you contact the supervisor(s) for this project before you apply.

How to apply

Apply online through our website: https://uom.link/pgr-apply-fap

When applying, you’ll need to specify the full name of this project, the name of your supervisor, if you already having funding or if you wish to be considered for available funding through the university, details of your previous study, and names and contact details of two referees.

Your application will not be processed without all of the required documents submitted at the time of application, and we cannot accept responsibility for late or missed deadlines. Incomplete applications will not be considered.

After you have applied you will be asked to upload the following supporting documents:

  • Final Transcript and certificates of all awarded university level qualifications
  • Interim Transcript of any university level qualifications in progress
  • CV
  • Contact details for two referees (please make sure that the contact email you provide is an official university/work email address as we may need to verify the reference)
  • Supporting statement: A one or two page statement outlining your motivation to pursue postgraduate research and why you want to undertake postgraduate research at Manchester, any relevant research or work experience, the key findings of your previous research experience, and techniques and skills you’ve developed. (This is mandatory for all applicants and the application will be put on hold without it. 
  • English Language certificate (if applicable)

If you have any questions about making an application, please contact our admissions team by emailing .

Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact.

We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status.

We also support applications from those returning from a career break or other roles. We consider offering flexible study arrangements (including part-time: 50%, 60% or 80%, depending on the project/funder).

Biological Sciences (4) Computer Science (8)

Funding Notes

At The University of Manchester, we offer a range of scholarships, studentships and awards at university, faculty and department level, to support both UK and overseas postgraduate researchers. Please see the project description for further details.

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