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
Variants
Skat
112
Optimal tests for rare variant effects in sequencing association studies
S. Lee, Michael C. Wu, Xinyi Lin · Biostatistics · 2012 · 745 citations · Full text
Excessive burden of lysosomal storage disorder gene variants in Parkinson’s disease
Laurie Robak, Iris E. Jansen, Jeroen van Rooij et al. · Brain · 2017 · 451 citations · Full text
1–5 of 112
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The University of Texas Health Science Center at Houston, United States
6 publications · 215 citations
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Eunice Kennedy Shriver National Institute of Child Health and Human Development, United States
6 publications · 215 citations
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5
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1–5 of 1.2K
460
Harvard University
Cambridge, United States
13 h-index
37 publications
11.7K citations
University of Michigan
Ann Arbor, United States
13 h-index
26 publications
3.2K citations
The University of Texas Health Science Center at Houston
Houston, United States
13 h-index
24 publications
617 citations
University of Washington
Seattle, United States
11 h-index
34 publications
996 citations
National Institutes of Health
Bethesda, United States
10 h-index
42 publications
1.4K citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
9 h-index
16 publications
6.2K citations
Fred Hutch Cancer Center
Seattle, United States
8 h-index
18 publications
486 citations

University of Minnesota
Minneapolis, United States
8 h-index
22 publications
595 citations
1–8 of 460
25 publications · 1.2K citations
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5 publications · 86 citations
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AJHG · 5 publications · 3.1K citations
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4 publications · 94 citations
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4 publications · 129 citations
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