Single-variant Testing

Single-Variant Testing is a statistical inference method in rare variant analysis that evaluates the association between individual genetic variants and a phenotype by testing each variant separately, distinguishing it from aggregated or multi-variant approaches through its focus on single nucleotide-level effects.

42

Publications

2.3K

Citations

790

Authors

222

Institutions

Publications per year

2017–2026

19

Variants

Single-variant AnalysisSingle-variant Association Testing

Authors

790

  1. DD
    Daniel D. Kinnamon

    The Ohio State University, United States

    2 publications · 112 citations

    2

    h-index

  2. XS
    Xiaotong Shen

    University of Minnesota, United States

    2 publications · 77 citations

    2

    h-index

  3. HW
    Hugh Watkins

    University of Oxford, United Kingdom

    2 publications · 116 citations

    2

    h-index

  4. EB
    Eric Boerwinkle

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

    2 publications · 63 citations

    2

    h-index

  5. JP
    Jonathan P. Tyrer

    University of Cambridge, United Kingdom

    2 publications · 50 citations

    2

    h-index

1–5 of 790

Venues

  1. Genetic Epidemiology

    5 publications · 144 citations

    5

    h-index

  2. PLoS ONE

    3 publications · 84 citations

    3

    h-index

  3. Human Molecular Genetics

    2 publications · 84 citations

    2

    h-index

  4. Bioinformatics

    2 publications · 135 citations

    2

    h-index

  5. Scientific Reports

    2 publications · 66 citations

    2

    h-index

1–5