BLINK is a Genome Wide Association Study (GWAS) Method (Giga Science, 2019), standing for Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK). BLINK is an enhanced version of FarmCPU GWAS method (PLoS Genetics, 2016), which stands for “Fixed and random model Circulating Probability Unification”. Both of them use iterations to select a set of markers associated with a trait of interest. These associated markers are fitted as covariates for testing markers across genome, one at a time. The association tests do not use kinship to eliminate its confounding effects to mask causal genes. The set of associated markers are optimized specifically for the particular trait, they have better control on false positives than the kinship approach as it stay the same across traits. The difference between FarmCPU and BLINK is that FarmCPU requires that genes underlying the trait are distributed equally across genome and BLINK eliminates the requirement and consequently has high statistical power. BLINK also replaces the REstricted Maximum Likelihood (REML) in a mixed linear model in FarmCPU with Bayesian Information Content (BIC) in a fixed effect model to boost computing speed.

BLINK method was implemented in both R and C languages. The R version was developed by Dr. Yao Zhao (Email: yao.zhou@genetics.ac.cn) and can be accessed as stand-alone version on GitHub, or through GAPIT. The C version was developed by Dr. Meng Huang (Email: meng.huang.cn@gmail.com). Bit operations were used in the C version. As a result, BLINK C version is not only faster than BLINK and FarmCPU R versions, but also faster than PLINK. The C package is available at GitHub, containing executable program that is free to analyze datasets under 50 million data points (number of individuals x number of markers). Releases of limitation on the data points, or Licenses for BLINK C source code are available at the Office of Commercialization at Washington State University.