Fine-mapping from summary data with the “Sum of Single Effects” model

In recent work, Wang et al introduced the "Sum of Single Effects" (SuSiE) model, and showed that it provides a simple and efficient approach to fine-mapping genetic variants from individual-level data. Here we present new methods for fitting the SuSiE model to summary data, for example to single-SNP z-scores from an association study and linkage disequilibrium (LD) values estimated from a suitable reference panel. To develop these new methods, we first describe a simple, generic strategy for extending any individual-level data method to deal with summary data. The key idea is to replace the usual regression likelihood with an analogous likelihood based on summary data. We show that existing fine-mapping…

• GA
  Gordon and Betty Moore Foundation
• UO
  University of Chicago
• TF
  Thompson Family Foundation
• NI
  National Institutes of Health

  Awards: R01HG002585, U01AG072572
• MR
  Medical Research Council

  Award: MC_PC_17228
• NI
  National Institute on Aging

  Award: U01AG072572
• NH
  National Human Genome Research Institute

  Award: R01HG002585