Genome-Wide Association Studies: From Polymorphism to Personalized Medicine. Edited by Krishnarao Appasani; Forewords by Stephen W. Scherer and Peter M. Visscher. Cambridge and New York: Cambridge University Press. $185.00. xxxi + 391 p. + 24 pl.; ill.; index. ISBN: 978-1-107-04276-6. 2016.

2018 ◽  
Vol 93 (1) ◽  
pp. 50-50
Author(s):  
Jinliang Yang
Keyword(s):  
New York ◽  
Personalized Medicine ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Cambridge University ◽  
Genome Wide

scholarly journals SAIGE-BRUSH: an efficient, user-friendly and low cost cloud implementation for genome-wide association studies

2021 ◽  
Author(s):  
Tonya M Brunetti ◽  
Nikita Pozdeyev ◽  
Michelle Daya ◽  
Kathleen C Barnes ◽  
Nicholas Rafaels ◽  
...  
Keyword(s):  
Personalized Medicine ◽  
Data Collection ◽  
Association Studies ◽  
Low Cost ◽  
Genome Wide Association ◽  
Data Sets ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
User Friendly ◽  
Cloud Implementation

SAIGE-Biobank Re-Usable SAIGE Helper (SAIGE-BRUSH) allows users with little computational expertise to utilize SAIGE for GWAS with parallelization and data collection on biobank data sets. This implementation requires no installation and has additional features not programmed within the original SAIGE framework, such as concurrency, reproducibility, reusability, scalability, association analysis results filtering and output plots. This is all achieved without writing any code from the user. This implementation is currently being utilized by the Biobank at the Colorado Center for Personalized Medicine (CCPM) on Google Cloud but is flexible for a number of architectures available to genetic analysts. Availability: This open source implementation is freely available at https://github.com/tbrunetti/SAIGE-BRUSH and is licensed under the MIT License. Contact: Chris Gignoux at [email protected] & Nick Rafaels at [email protected] Supplemental Material: For detailed user documentation, please visit https://saige-brush.readthedocs.io/en/latest/

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