(INFORMATICS) The informatics needs of the ClinGen consortium are extensive. From developing user support tools to curatorial responsibility for the project data to oversight of analysts developing and comparing computational predicators, the Informatics team at Stanford/Baylor provides much of the IT backbone and infrastructure for the project. As such, the bulk of activity is concentrated in this component of the grant. During the first phase of ClinGen, we designed, developed, tested and deployed a Gene Curation Interface (GCI) and Variant Curation Interface (VCI), a suite of software products and databases designed to meet the curatorial needs of the project. During the second phase of this project, these resources will be significantly expanded to enable gene and variant curation at scale. For the VCI, we will first focus on improving the interpretation experience, through additional cycles of user/design feedback. We will also improve curation efficiency by identifying sources of curation discordancy. Two additional key goals of this second phase are (1) customizing VCI for specific gene and Clinical Domain workflows, and (2) Deploying API for sharing of machine-readable data. For the GCI, we will add support for additional types of evidence used in Gene:Disease Clinical Validity Classifications, including animal model data. We will also improve workflow for classification and data sharing among the GCI/VCI. Finally, we will develop training materials and workshops on the use of our software in curation workflows. A key component of the work we do is warehousing, indexing and merging of heterogeneous data sources. An excellent example is the ClinGen Allele Registry (CAR) we have developed for integrating information about different alleles in clinically relevant genes. The CAR serves as a critical ?network adapter? for translating between allelic representation standards, and for linking each allele to the rapidly growing global corpus of information. During the second phase of the project, this will be expanded to scale up capacity and bandwidth, develop a User Interface and broaden adoption outside the project. To meet the needs of our clinical colleagues in implementing the ACMG pathogenicity interpretation standards, we developed the ClinGen Pathogenicity Calculator. Currently, users enter the applicable ACMG evidence tags for a specific allele with links to supporting data for each tag and generate the corresponding guideline- based pathogenicity assessment for the allele. Future improvements include automating parts of the calculation, such as population frequency comparison in conjunction with the Ancestry Working Group described in Resource. We have also devoted considerable effort, and will expand upon software, to support dissemination of Actionability Recommendations. Finally, we describe, in (great) detail, the Software Environment Infrastructure and design philosophy behind architecture and decisions made in the proposal.
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