VariantCurator: A “spell-checker” for genomic variant data that will improve diagnostic rates by improving the accuracy of genetic data in clinical literature and increasing the findability of data in historic literature

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 efforts of a Human Genome Organization committee which proposed a unified professional-standard for representing genomic data. We will create AI guided curation software to enable the professional-standard via a framework intended to better communicate genetic data throughout the human genomics community. The framework captures precise names for variants and documents the clinical evidence used to classify them. We will upgrade the VariantValidator infrastructure by developing an AI approach that extracts variant names and evidence from clinical literature. Uniquely, we will employ a systematic approach which engages the user in the process, e.g. informing the user if required information is missing and asking for it to be to provided. This tool will provide authors of with an automated “spell-checker” for variant data applicable to both literature in production as well as historical literature. Use of the tool will increase the quality and accessibility of genomics data in clinical literature and, in time, increase diagnostic rates.

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 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.

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

How to apply

Click here to apply.

When you apply, 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

•  You will be asked to supply contact details for two referees on the application form (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 require an English qualification to study in the UK, you can apply now and send this in at a later date. 

If you have any queries regarding making an application please contact our admissions team FSE.doctoralacademy.admissions@manchester.ac.uk.

The start date is January 2025. The duration of the PhD is 3.5 years.

Before you apply

We strongly recommend that you contact the supervisor to discuss the application before you apply. 

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).