Performs genome-wide association analyses using the FarmCPU model. Briefly, FarmCPU tests the significance of associations between genetic markers and phenotypes using the general linear model framework. After single-marker regression, FarmCPU divides the genome into bins and identifies a set of optimal markers to use as covariates in the next iteration. This approach, similar to that of the multi-locus mixed model, increases power and decreases the false discovery rate.
|License||MIT + file LICENSE|
|Package repository||View on GitHub|
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