Data-sharing on the variant level to improve genetic diagnosis and discovery

The challenges

One of the challenges that the genetic community faces nowadays is the data bottleneck resulting from inefficient and unstandardized gathering of individual laboratory findings, with most information siloed in restricted databases. Even with the rise in WES and WGS accessibility over the past few years and the consequential exponential increase of genomic data, experts agree that without appropriate analytical tools to safely and accurately share phenotypic and genotypic information among the community, the interpretation and classification of novel variants simply cannot advance at the required speed.

Overcoming the limitations with collaboration

To overcome these limitations, databases that focus on sharing real-world evidence of cases with rare phenotypes are gaining more ground in the professional community. Following the MatchMaker Exchange example, which aims to connect exome, genome, and phenotype databases at the gene level, Franklin, along with DECIPHER, MyGene2/Geno2MP, and VariantMatcher, have joined an initiative to facilitate collaboration and data-sharing for genomic variants.

  1. Providing a more precise classification of variants of uncertain significance (VUS)

Franklin’s impact

Franklin is no stranger to the huge impact data-sharing can have on the genetics field. The development of tools to facilitate responsible, practical, and comprehensive sharing of genomic data among experts is one of the key pillars of the platform, and a mission we take very seriously at Genoox. Supporting multiple genetic applications such as rare diseases, oncology, and carrier screening, Franklin not only collects in-depth variant evidence and automates ACMG-based classification for several variant types, but also provides dedicated features that allow users to share de-identified evidence and insights with the rest of the community.

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Franklin by Genoox

Franklin by Genoox

The world’s largest, most diverse real-world genetic evidence database. We believe that community data-sharing is the future of genomics