Gene-based Association Analysis

Gene-Based Association Analysis is a statistical method in rare variant association studies that aggregates the effects of multiple variants within a gene to test for association with a phenotype, distinguishing it from variant-level or region-based approaches by focusing on the gene as the fundamental unit of analysis.

315

Publications

18.2K

Citations

3.7K

Authors

1.2K

Institutions

Publications per year

2017–2026

161

Variants

Gene-based Association Testing

Authors

3.7K

  1. PC
    Pak C. Sham

    University of Hong Kong, Hong Kong SAR China

    7 publications · 933 citations

    7

    h-index

  2. NG
    Nicholas G. Martin

    QIMR Berghofer Medical Research Institute, Australia

    6 publications · 1.1K citations

    6

    h-index

  3. MB
    Michael Boehnke

    University of Michigan, United States

    6 publications · 360 citations

    6

    h-index

  4. EB
    Eric Boerwinkle

    The University of Texas Health Science Center at Houston, United States

    6 publications · 194 citations

    6

    h-index

  5. DL
    Dan L. Nicolae

    University of Chicago, United States

    5 publications · 2.7K citations

    5

    h-index

1–5 of 3.7K

Venues

  1. PLoS ONE

    36 publications · 1.2K citations

    22

    h-index

  2. Scientific Reports

    15 publications · 684 citations

    13

    h-index

  3. Frontiers in Genetics

    13 publications · 400 citations

    11

    h-index

  4. Bioinformatics

    10 publications · 1.5K citations

    10

    h-index

  5. PLoS Genetics

    9 publications · 808 citations

    9

    h-index

1–5