Mixed-model Association Analysis

Mixed-Model Association Analysis is a statistical method that, within the context of trait architecture, identifies genetic associations by incorporating both fixed effects for marker-specific contributions and random effects to account for population structure and relatedness, thereby distinguishing it from simpler association models that ignore such confounding factors.

160

Publications

23.6K

Citations

1K

Authors

394

Institutions

Publications per year

2017–2026

51

Variants

Mixed Linear Model Association AnalysisMixed Model Association MappingMlm Association Analysis

Authors

1K

  1. NZ
    Noah Zaitlen

    University of California, San Francisco, United States

    4 publications · 3.1K citations

    4

    h-index

  2. OD
    O. Distl

    University of Veterinary Medicine Hannover, Foundation, Germany

    4 publications · 170 citations

    4

    h-index

  3. PM
    Peter M. Visscher

    The University of Queensland, Australia

    4 publications · 1.8K citations

    4

    h-index

  4. JY
    Jian Yang

    The University of Queensland, Australia

    4 publications · 1.8K citations

    4

    h-index

  5. EE
    Eleazar Eskin

    University of California, Los Angeles, United States

    4 publications · 2.1K citations

    4

    h-index

1–5 of 1K

Venues

  1. PLoS ONE

    9 publications · 354 citations

    9

    h-index

  2. Genetics

    8 publications · 3.1K citations

    8

    h-index

  3. Nature Genetics

    7 publications · 13.4K citations

    7

    h-index

  4. Bioinformatics

    5 publications · 151 citations

    5

    h-index

  5. BMC Genomics

    5 publications · 354 citations

    5

    h-index

1–5