Optimal tests for rare variant effects in sequencing association studies.

By Seunggeun Lee, Michael C. Wu, Xihong Lin. Biostatistics, 2012

697 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/aaa62985b1b259999e32646d0ea2b36cd9007379

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In Genetics

Citations in the corpus

Optimal unified approach for rare-variant association testing with application to small-sample case-control whole-exome sequencing studies. (2012, methodology): “Following the same argument in Lee et al.(2011),19 it can be shown that Qρ is equivalent as (1− ρ)κ1 + ψ(ρ)κ2, (A.4) where κ1 = (1− ρ)ỹ′(I−M)ZZ′(I−M)ỹ + 2(1 − ρ)ỹ′(I−M)ZZ′Mỹ and κ2 = ỹ ′z̄z̄′ỹ/z̄′z̄.”
PERCH: a unified framework for disease gene prioritization (2017, methodology): “Nevertheless, the output scores of the proposed framework can also be used as variant weights in other rare-variant association tests such as SSU [Basu and Pan, 2011] and SKAT-O [Lee et al., 2012], which are more robust with respect to the percentage of causal variants and the presence of protective”
The Next-Generation Sequencing Revolution and Its Impact on Genomics (2013, positive): “Although the initial version of SKAT lost power in cases in which all variants in a gene have the same direction of effect, the newer SKAT-O (Lee et al., 2012a) test combines a test handling bidirectional effects and a test handling unidirectional effects to achieve excellent power in either case.”
Rare-variant association analysis: study designs and statistical tests. (2014, background): “Lee et al. 64,77 proposed a linear combination of SKAT and burden test statistics: where the parameter r can be interpreted as a pairwise correlation among the genetic-effect coefﬁcients b j in Equation 1.”