Aim 3

Integration of multisource data for effective use in the clinic

The TGMI is working on integration of multisource molecular and clinical data to provide robust clinical variant interpretation at speed and at scale. We have built a plugin to Ensembl’s VEP to optimise variant interpretation processes for G2P genes (VEP-G2P).  Using the completed G2P datasets from aim 1 with the VEP-G2P plugin enables a large number of variant filtering criteria to be tested on previously characterised cohorts, both with and without relevant clinical presentation. In turn, this will enable us to develop rules-based diagnostic approaches using genome-wide sequencing data and statistically assess their sensitivity and precision.

We are developing tools to enable the use of protein structure with genetic data to improve clinical variant interpretation, including a VEP plugin that uses protein family information in variant interpretation. In association with ACGS, we will write guidelines to inform the use of protein structure information in genomic variant interpretation.

In collaboration with gnomAD, we are developing systematic methods for using variant frequency information with disease priors to improve variant interpretation. We are working to build a platform to view rare disease data alongside gnomAD variants to allow quantitative interpretive calculations.

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