scholarly journals TMOD-19. GABRIELLA MILLER KIDS FIRST DATA RESOURCE CENTER: LARGE-SCALE HARMONIZED CLINICAL AND GENOMIC DATA PLATFORM TO SUPPORT CHILDHOOD CANCER AND STRUCTURAL BIRTH DEFECT RESEARCH

2019 ◽  
Vol 21 (Supplement_2) ◽  
pp. ii125-ii125
Author(s):  
Allison Heath ◽  
Pichai Raman ◽  
Yuankun Zhu ◽  
Jena Lilly ◽  
Deanne Taylor ◽  
...  
2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii321-iii321
Author(s):  
Allison P Heath ◽  
Yuankun Zhu ◽  
Michele Mattioni ◽  
Bailey Farrow ◽  
Jena Lilly ◽  
...  

Abstract Since launching to the public in September 2018, the Gabriella Miller Kids First Data Resource Center (DRC) has made an increasing number of pediatric genomic studies available to the research community. Currently, 1.3 PBs of genomic and clinical data drawn from 12,000 participants are available across a variety of pediatric cancer and structural birth defect studies. The DRC has architected a secure, cloud-based platform with over 1,300 users that supports the ability of researchers to not only find, access, and reuse data, but also integrate, collaborate, and analyze data quickly at scale. Users can use integrations with platforms such as Cavatica for bioinformatics workflows and PedcBioPortal for cancer genomic visualizations. Additionally, a set of framework services, powered by Gen3, provide a foundation for interoperability with other large-scale data sources, platforms, and a growing ecosystem of analysis and visualization applications. These integrations allow users to search across both TARGET and Kids First clinical data in one location while allowing data governance to be maintained by the original approvers. The new “explore data” feature allows users to search across all studies in order to identify virtual cohorts. Within the portal, these cohorts can be saved and shared with collaborators for iterative refinement and analysis. With appropriate approvals, the associated genomic data can be accessed and analyzed seamlessly in Cavatica or other platforms with interoperable framework services. Additionally, gene searching capabilities will be available in 2020. Data is free to download and cloud credits are available for analysis support.


2019 ◽  
Author(s):  
Yuankun Zhu ◽  
Miguel Brown ◽  
Batsal Devkota ◽  
Bailey Farrow ◽  
Bogdan Gavrilovic ◽  
...  

2019 ◽  
Author(s):  
Yuankun Zhu ◽  
Miguel Brown ◽  
Batsal Devkota ◽  
Bailey Farrow ◽  
Bogdan Gavrilovic ◽  
...  

2008 ◽  
Vol 40 (7) ◽  
pp. 854-861 ◽  
Author(s):  
Jun Zhu ◽  
Bin Zhang ◽  
Erin N Smith ◽  
Becky Drees ◽  
Rachel B Brem ◽  
...  

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Xiujin Li ◽  
Hailiang Song ◽  
Zhe Zhang ◽  
Yunmao Huang ◽  
Qin Zhang ◽  
...  

Abstract Background With the emphasis on analysing genotype-by-environment interactions within the framework of genomic selection and genome-wide association analysis, there is an increasing demand for reliable tools that can be used to simulate large-scale genomic data in order to assess related approaches. Results We proposed a theory to simulate large-scale genomic data on genotype-by-environment interactions and added this new function to our developed tool GPOPSIM. Additionally, a simulated threshold trait with large-scale genomic data was also added. The validation of the simulated data indicated that GPOSPIM2.0 is an efficient tool for mimicking the phenotypic data of quantitative traits, threshold traits, and genetically correlated traits with large-scale genomic data while taking genotype-by-environment interactions into account. Conclusions This tool is useful for assessing genotype-by-environment interactions and threshold traits methods.


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