Credible Set Construction

Credible Set Construction is a statistical method in genetic fine-mapping that identifies a minimal set of genetic variants, ranked by posterior probability, such that the causal variant is contained within the set with a specified high probability, thereby distinguishing it from alternative variant prioritization approaches by its probabilistic guarantee of causal inclusion.

44

Publications

4.7K

Citations

363

Authors

223

Institutions

Publications per year

2017–2026

21

Authors

363

  1. AI
    Atsushi Inoue

    North Carolina State University, United States

    2 publications · 244 citations

    2

    h-index

  2. CP
    Christian P. Robert

    Université Paris Dauphine-PSL, France

    2 publications · 78 citations

    2

    h-index

  3. AS
    Abhishek Sarkar

    University of Chicago, United States

    2 publications · 1.2K citations

    2

    h-index

  4. JF
    Johan F. Kaashoek

    Erasmus University Rotterdam, Netherlands

    2 publications · 158 citations

    2

    h-index

  5. DT
    David T. Frazier

    Monash University, Australia

    2 publications · 78 citations

    2

    h-index

1–5 of 363

Venues

  1. The Annals of Statistics

    5 publications · 385 citations

    5

    h-index

  2. Journal of Statistical Planning and Inference

    3 publications · 73 citations

    3

    h-index

  3. Nature Communications

    3 publications · 226 citations

    3

    h-index

  4. 2

    h-index

  5. Bayesian Analysis

    2 publications · 176 citations

    2

    h-index

1–5