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GIFTs and PepVEP glue projects

This project aims to create an infrastructure to facilitate mapping and data flow between DNA and proteins, with the goal of maintaining up-to-date Ensembl to UniProt mappings. It will deliver a database and API for frequent and comprehensive data sharing, as well as an automated genome-protein mapping pipeline and a framework for manual validation and editing.

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GIFTs and PepVEP glue projects

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  1. GIFTs and PepVEP glue projects

  2. Genome Integration with FuncTion and Sequence (GIFTS) • What: to create an infrastructure to facilitate the mapping and data flow between DNA and proteins • Aim: to maintain up-to-date Ensembl to UniProt mappings • Deliverables • Database and API for frequent and comprehensive data sharing • Automated genome–protein mapping pipeline • Framework for manual validation and editing • GIFTS resource with agreed gene and protein sets– file downloads

  3. PepVEPAn integrated platform for interpreting the functional effects of variants • What: to create an integrated framework to deliver functional information per residue • Aim: to facilitate the functional Interpretation of genomic variants • By building on publicly available services: • Ensembl Variant Effect Predictor (VEP) (Genome variation) • UniProt functional residue annotation (Protein function) • PDBe structural residue annotation (Protein structures) • The VarSite service (Janet Thorton’s group) variant effects reports

  4. PepVEPintegrated framework to deliver functional information per residue Genome (Ensembl) <-> Proteins (UniProt) mapping infrastructure Proteins (UniProt) <-> Structures (PDBe) mapping infrastructure

  5. PepVEP representation in these resources

  6. User research 2017 13 users : 3 clinicians, 2 systems medicine researchers 3 clinical data scientists from industry 5 bioinformaticians from academia/ hospital

  7. User Research 2018 Determine if the PepVEP prototype meets the proposed usability goals and identify any potential usability problems. Usability goals: • User interface is useful and easy to use • The content information is helpful and constructive • The design concepts and workflow corresponds to the user requirements • Gather user feedback on expected data A usability test was conducted with a group 10 users. Participant background

  8. User Profiles • Processes larger sets of variants to quickly identify candidates. Candidates are then analysed in detail, and summary of the assessment is made. • High-throughput driven. Ideally wants an API to do everything programmatically. • Looks at a subset of variants of specific diseases in order to understand and interpret the results in the clinical context. • Is very unlikely to run a set of raw variants through a pipeline. These users are interested in drawing their own conclusions and generating a report. Bioinformatician PI, Snr Clinical Geneticist • Analyses a set of variants in order to identify key variants in their study. Users are less experienced with the data, so they need a clear and concise explanation of the content. • Less likely to quickly asses the data because of their lack of experience. • Wants to get a detailed report on clinical and biological consequences for a set of variants to identify the variant(s) most likely to be causing the disease. • Will use all information available and the presented evidence basis. Clinical Geneticist Student • Interested in the clinical context and the biochemical/bio-molecular information to be able to better understand a variant. • Wants understand the biological consequences of a variant to better develop their software. Clinician Computer scientist

  9. Usability test- detailed report • Summary of what users prefered between the two designs tested Content Design A Design B • Clear and useful • Relevant terminology and vocabulary used • Easy to scan and navigate Design layout • By categorizing the information the prototype: • Easy to use • Easy to navigate • Clean design • Jump to a desired subsection VS Summary description • More informative and detailed • Overview of the content provided

  10. Usability test findings

  11. Some points discussed • Use a common source of variation data (e.g. EVA for genomics variations, VarSite? for protein variation) • Use tools (e.g James tool) to map different versions of the genome (e.g. GRCh37 to GRCh38) • Use and/or reengineer VarSite/MutFunc back-end (e.g. store consequences of aa changes for quick access) • Maintain good VEP REST service performance

  12. Staff members & Acknowledgments Janet Thornton Roman Laksowski James Stephenson Jie Luo, Xavier Watkins Carla Oliveira Mahdi Mahmoudy Andrew Nightingale

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