Sequence Kernel Association Testing

Sequence Kernel Association Testing is a statistical method that belongs to the class of kernel-based association tests, distinguished by its use of aggregated genetic variant data within a genomic region to assess the collective effect of rare and common alleles on a phenotypic trait.

112

Publications

7.9K

Citations

1.2K

Authors

460

Institutions

Publications per year

2017–2026

52

Authors

1.2K

  1. MC
    Michael C. Wu

    Fred Hutch Cancer Center, United States

    8 publications · 3.6K citations

    8

    h-index

  2. SL
    Seunggeun Lee

    University of Michigan, United States

    7 publications · 3.3K citations

    7

    h-index

  3. MX
    Momiao Xiong

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

    6 publications · 215 citations

    6

    h-index

  4. RF
    Ruzong Fan

    Eunice Kennedy Shriver National Institute of Child Health and Human Development, United States

    6 publications · 215 citations

    6

    h-index

  5. XL
    Xihong Lin

    Harvard University, United States

    5 publications · 3.3K citations

    5

    h-index

1–5 of 1.2K

Venues

  1. Genetic Epidemiology

    25 publications · 1.2K citations

    16

    h-index

  2. PLoS ONE

    5 publications · 86 citations

    5

    h-index

  3. The American Journal of Human Genetics

    AJHG · 5 publications · 3.1K citations

    5

    h-index

  4. Annals of Human Genetics

    4 publications · 94 citations

    4

    h-index

  5. Frontiers in Genetics

    4 publications · 129 citations

    4

    h-index

1–5