Permutation-based Correction

Permutation-Based Correction is a statistical method for adjusting significance thresholds in multiple hypothesis testing by generating empirical null distributions through repeated random reassignments of observed data labels, thereby preserving the dependency structure among tests while controlling family-wise error or false discovery rates.

52

Publications

11.9K

Citations

144

Authors

110

Institutions

Publications per year

2017–2026

14

Authors

144

  1. TE
    Thomas E. Nichols

    University of Oxford, United Kingdom

    4 publications · 466 citations

    4

    h-index

  2. XG
    Xiaoyi Gao

    Washington University in St. Louis, United States

    3 publications · 1.4K citations

    3

    h-index

  3. BH
    Buhm Han

    Broad Institute, United States

    3 publications · 300 citations

    3

    h-index

  4. EE
    Eleazar Eskin

    University of California, Los Angeles, United States

    3 publications · 300 citations

    3

    h-index

  5. AM
    Anderson M. Winkler

    University of Oxford, United Kingdom

    3 publications · 140 citations

    3

    h-index

1–5 of 144

Venues

  1. Bioinformatics

    6 publications · 485 citations

    6

    h-index

  2. Genetic Epidemiology

    5 publications · 1.7K citations

    5

    h-index

  3. NeuroImage

    5 publications · 594 citations

    5

    h-index

  4. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 3 publications · 42 citations

    3

    h-index

  5. BMC Bioinformatics

    3 publications · 160 citations

    3

    h-index

1–5