Multi-phenotype Association Testing

Multi-Phenotype Association Testing is a statistical inference framework that extends univariate association testing by jointly analyzing multiple phenotypic traits to identify genetic variants associated with shared or distinct multivariate phenotypic patterns.

108

Publications

6.4K

Citations

511

Authors

266

Institutions

Publications per year

2017–2026

34

Authors

511

  1. WP
    Wei Pan

    University of Minnesota, United States

    6 publications · 316 citations

    6

    h-index

  2. XL
    Xihong Lin

    Harvard University, United States

    4 publications · 440 citations

    4

    h-index

  3. DR
    Debashree Ray

    Johns Hopkins University, United States

    4 publications · 286 citations

    4

    h-index

  4. HA
    Hugues Aschard

    Institut Pasteur, France

    3 publications · 67 citations

    3

    h-index

  5. SZ
    Shuanglin Zhang

    Michigan Technological University, United States

    3 publications · 80 citations

    3

    h-index

1–5 of 511

Venues

  1. Genetic Epidemiology

    22 publications · 1.7K citations

    18

    h-index

  2. Bioinformatics

    13 publications · 612 citations

    12

    h-index

  3. The American Journal of Human Genetics

    AJHG · 6 publications · 750 citations

    6

    h-index

  4. PLoS Genetics

    6 publications · 565 citations

    6

    h-index

  5. Genetics

    5 publications · 132 citations

    5

    h-index

1–5