Current Projects

The GSLL is pursuing a number of lines of research related to validating the use of statistical learning methods with genome-wide data. Projects include

  • developing corrections for bias in variable importance measures
  • testing the power of statistical learning algorithms to detect functional SNPs
  • assessing methods for analyzing multivariate phenotypes
  • validating candidate SNPs discovered in applied analyses


The GSLL works closely with collarborators from around the world, including close partnerships with