The UK's 100,000 Genome Project reaches the halfway stage - New Gersy

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The UK's 100,000 Genome Project reaches the halfway stage



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Genomics England is using a non-relational database to power the data science behind its ambitious 100,000 Genomics Project.

The organisation, which is owned by the UK's Department of Health and Social Care, runs the project, which is sequencing 100,000 whole genomes from patients with rare diseases, along with their families, and also patients with common cancers.
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The project has currently reached its halfway purpose, with over fifty,000 genomes sequenced. By the top of 2018, the 100,000 genomes project are complete, with quite twenty petabytes of knowledge keep on the project's infrastructure.

The aim is to harness the ability of whole order sequencing technology to rework the approach folks square measure cared for, through the event of latest and more practical individualised treatments for patients.

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Patients' genomic information is combined with their clinical information to alter interpretation and analysis. This information is additionally receptive researchers and clinicians finding out however best to use genetic science in attention.
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The amount of knowledge being processed is big. in step with MongoDB, the project is sequencing on the average one,000 genomes per week that is manufacturing regarding 10TB of knowledge per day. 

To manage this advanced and sensitive information set, genetic science European nation uses MongoDB Enterprise Advanced as a part of its computing platform.

"Managing clinical and genomic information at this scale and complexness has conferred attention-grabbing challenges," same Augusto Rendon, director of bioinformatics at genetic science European nation. 

"Adopting MongoDB has been important to obtaining the a hundred,000 Genomes Project off the bottom. it's provided US with nice flexibility to store and analyse these advanced information sets along."



According to MongoDB the project's information platforms were designed from the bottom up. Why MongoDB? The document info was chosen for 3 core reasons, the corporate same. the primary was the informationbase's "native ability to handle a large style of data sorts, even those information structures that weren't thought-about at the start of the project."

This should build it less complicated for developers and information scientists to evolve information models and develop computer code solutions.

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The second reason was performance at scale. It became clear that there would be a massive and constantly growing dataset "that would need to seamlessly scale across underlying compute resources", the company said. 

Not only would the data set be big and complex, but the researchers would need to easily explore the data and not have long waits for simple queries.




The third driver was MongoDB's features such as end-to-end encryption and fine-grained access control to data.

The 100,000 Genomes Project dataset is sensitive: as well as the full genetic makeup of a patient, it also includes their clinical features and lifetime health data. Instead, de-identified data is analysed within a secure, monitored environment. Obviously, this makes encryption and data security vital.


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