Summary-data Mendelian Randomization

Summary-Data Mendelian Randomization is a form of Mendelian randomization analysis that uses summarized genetic association data from genome-wide association studies, rather than individual-level data, to estimate causal effects between exposures and outcomes while minimizing data sharing burdens and computational requirements.

267

Publications

48.9K

Citations

1.9K

Authors

730

Institutions

Publications per year

2017–2026

249

Variants

Summary-level Mendelian Randomization

Authors

1.9K

  1. SB
    Stephen Burgess

    University of Cambridge, United Kingdom

    27 publications · 26.3K citations

    25

    h-index

  2. GD
    George Davey Smith

    University of Bristol, United Kingdom

    22 publications · 24.5K citations

    20

    h-index

  3. JB
    Jack Bowden

    University of Bristol, United Kingdom

    20 publications · 24.6K citations

    18

    h-index

  4. CM
    Cosetta Minelli

    Imperial College London, United Kingdom

    7 publications · 6.5K citations

    7

    h-index

  5. DG
    Dipender Gill

    Imperial College London, United Kingdom

    7 publications · 1.3K citations

    7

    h-index

1–5 of 1.9K

Venues

  1. International Journal of Epidemiology

    18 publications · 11.7K citations

    17

    h-index

  2. Frontiers in Genetics

    15 publications · 381 citations

    12

    h-index

  3. Frontiers in Immunology

    11 publications · 261 citations

    10

    h-index

  4. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 9 publications · 626 citations

    9

    h-index

  5. Frontiers in Endocrinology

    9 publications · 230 citations

    8

    h-index

1–5