Gene-based Association Testing

Gene-Based Association Testing is a statistical method in genome-wide association studies that aggregates genetic variants within a gene region to test for collective associations with a phenotype, distinguishing it from single-variant approaches by evaluating the joint effect of multiple variants within a biologically defined gene unit.

183

Publications

12.5K

Citations

1.8K

Authors

700

Institutions

Publications per year

2017–2026

86

Variants

Gene-based Association Analysis

Authors

1.8K

  1. MJ
    Mark J. Daly

    Broad Institute, United States

    6 publications · 684 citations

    6

    h-index

  2. PC
    Pak C. Sham

    University of Hong Kong, Hong Kong SAR China

    5 publications · 1.1K citations

    5

    h-index

  3. BM
    Benjamin M. Neale

    Broad Institute, United States

    5 publications · 1.3K citations

    5

    h-index

  4. GR
    Gonçalo R. Abecasis

    University of Michigan, United States

    5 publications · 366 citations

    5

    h-index

  5. MB
    Michael Boehnke

    University of Michigan, United States

    5 publications · 237 citations

    5

    h-index

1–5 of 1.8K

Venues

  1. PLoS ONE

    15 publications · 491 citations

    12

    h-index

  2. The American Journal of Human Genetics

    AJHG · 12 publications · 2.5K citations

    11

    h-index

  3. Bioinformatics

    13 publications · 1.7K citations

    11

    h-index

  4. Genetic Epidemiology

    11 publications · 695 citations

    11

    h-index

  5. PLoS Genetics

    9 publications · 718 citations

    9

    h-index

1–5