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Data release

Nuage de données

Last data release

RELEASE 9  

Addition of GWAS data

Addition of RNA-seq data

* Update of clinical/phenotypic data

Scientific data and knowledge are common goods and should be shared within an appropriate framework. BQC19 fully endorses the Wellcome Trust Foundation statement "Sharing research data and findings relevant to the novel coronavirus (COVID-19) outbreak".

 

Following approval of applications by the BQC19 Access Committee, researchers can access BQC19 data. These data include clinical/phenotypic data of participants as well as data from the core analyses performed. Future return of experimental data generated from sample and data access will enrich the BQC19 data.

 

BQC19 uses Globus for data transfer. Due to the large volume of data, the Compute Canada interface is used as the data transfer mechanism. To access the data, you will be asked to be a Compute Canada user or a Globus user.

 

After obtaining the Material Transfer Agreement (MTA) signatures, access to the data will be given by the data management team via the Globus platform. This will enable download of the BQC19 data. However, it should be noted that some files are very large. They cannot be downloaded on a desktop or laptop computer. In addition, some files cannot be analyzed with conventional spreadsheets such as Excel or Google Spreadsheets, but must be analyzed with specialized megadata processing software.

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Available dataset per patient
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NOTE: A graph of the available dataset per visit will be available shortly.

1.*WARNING* At a download speed of 1MB/s, these files will take approximately two days to download.

 

2. *WARNING* - These files are *VERY* large. If you use these files, it is recommended to download them to a high performance computing cluster.  They currently reside in the Compute Canada infrastructure and Compute Canada is recommended as the platform to use if you will be performing analysis.

 

3.These files are meant to be opened with R (https://www.r-project.org/) using the SomaDataIO package  (https://github.com/SomaLogic/SomaDataIO).

 

4. *WARNING* - These files are *VERY* large.

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