Supporting data for "BLINK: A Package for the Next Level of Genome-Wide Association Studies with Both Individuals and Markers in the Millions"

Dataset type: Software
Data released on November 27, 2018

Huang M; Liu X; Zhou Y; Summers RM; Zhang Z (2018): Supporting data for "BLINK: A Package for the Next Level of Genome-Wide Association Studies with Both Individuals and Markers in the Millions" GigaScience Database. http://dx.doi.org/10.5524/100536

DOI10.5524/100536

Big datasets, accumulated from biomedical and agronomic studies, provide the potential to identify genes controlling complex human diseases and agriculturally important traits through genome-wide association studies (GWAS). However, big datasets also lead to extreme computational challenges, especially when sophisticated statistical models are employed to simultaneously reduce false positives and false negatives. The newly developed Fixed and random model Circulating Probability Unification (FarmCPU) method uses a bin method under the assumption that Quantitative Trait Nucleotides (QTNs) are evenly distributed throughout the genome. The estimated QTNs are used to separate a mixed linear model into a computationally efficient fixed effect model (FEM) and a computationally expensive random effect model (REM), which are then used iteratively. To completely eliminate the computationally expensive REM, we replaced REM with FEM by using Bayesian Information Criteria. To eliminate the requirement that QTNs be evenly distributed throughout the genome, we replaced the bin method with linkage disequilibrium information. The new method is called Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK). Both real and simulated data analyses demonstrated that BLINK improves statistical power compared to FarmCPU, in addition to remarkably reducing computing time. Now, a dataset with one-half million markers and one million individuals can be analyzed within five hours, instead of one week using FarmCPU.

Additional details

Read the peer-reviewed publication(s):


Additional information:

https://github.com/YaoZhou89/BLINK

https://github.com/Menggg/BLINK





File NameSample IDData TypeFile FormatSizeRelease Date 
Tabular DataUNKNOWN19.17 MB2018-11-26
SNPsUNKNOWN56.43 MB2018-11-26
SNPsUNKNOWN5.46 MB2018-11-26
Tabular DataUNKNOWN40.91 KB2018-11-26
SNPsUNKNOWN19.7 KB2018-11-26
Tabular DataUNKNOWN258.04 KB2018-11-26
Tabular DataTEXT9.28 MB2018-11-26
Tabular DataTEXT1.77 KB2018-11-26
Tabular DataTEXT1.77 KB2018-11-26
GitHub archivearchive7.69 MB2018-11-26
Displaying 1-10 of 264 File(s).
Funding body Awardee Award ID Comments
Washington Grain Commission Z Zhang 126593
National Institute of Food and Agriculture Z Zhang 2018-70005-28792
National Institute of Food and Agriculture A Carter and Z Zhang 2016-68004-24770
Date Action
November 27, 2018 Dataset publish
November 28, 2018 Funder updated : National Institute of Food and Agriculture
November 28, 2018 Funder updated : National Institute of Food and Agriculture
December 3, 2018 Manuscript Link added : 10.1093/gigascience/giy154
February 3, 2019 External Link removed : https://github.com/YaoZhou89/BLINK
February 3, 2019 External Link removed : https://github.com/Menggg/BLINK
February 3, 2019 External Link added : https://github.com/YaoZhou89/BLINK
February 3, 2019 External Link added : https://github.com/Menggg/BLINK