Decoding rare disease through 77,000 genomes

Genome sequencing. Despite continual progress in understanding the genetic etiology of human disease, more than half of rare disorders remain unsolved. Resolving the remaining etiologies in rare disease are a major focus of ongoing efforts in the field, including a shift towards standardized analysis of large-scale genome sequencing data from large patient cohorts. In a recent study, Greene and collaborators aimed to identify associations between genes and rare disease subgroups, leveraging genomes of 77,539 people including 29,741 probands. Here is a brief review on their publication in the context of etiological resolution in rare disease.

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The Great De-Siloing

Data sharing. Over time, genomic scientists have learned how to share. Large international cohorts and efforts of data deposition have led to large databases that can be used to answer big questions. However, silos of genomic data, such as massive sequencing studies performed on specialized cohorts, lay unconnected across research groups, academic institutions, and collaborators. Recently, we have been involved in several projects to de-silo rather than simply share genomic data, and we realized that there may be some aspects that apply to the genomics worlds more broadly. For example, what makes de-siloing different from data sharing? The goal of this post is to redefine these concepts and explain why we should be less concerned about data sharing and more concerned about data integration. Continue reading