(Price et al. 2006)
detects and corrects for population stratification
in genome-wide association studies. The method, based on
principal components analysis, explicitly models ancestry
differences between cases and controls along continuous axes of
variation. The resulting correction is specific to a candidate marker's
variation in frequency across ancestral populations, minimizing spurious
associations while maximizing power to detect true associations. The approach
is powerful as well as fast, and can easily be applied to disease studies with
hundreds of thousands of markers.
As of December 2006, EIGENSTRAT is implemented as part of the
EIGENSOFT package. Source code, documentation and executables
for the EIGENSOFT package are available at the
Reich lab software page.