Testing for an Unusual Distribution of Rare Variants

By Benjamin M. Neale, M. Rivas, Benjamin F. Voight, David Altshuler, B. Devlin, M. Orho-Melander, Sekar Kathiresan, Shaun Purcell, Kathryn Roeder, Mark J. Daly. PLoS Genetics, 2011

617 citations recorded by the source corpus.

Technological advances make it possible to use high-throughput sequencing as a primary discovery tool of medical genetics, specifically for assaying rare variation. Still this approach faces the analytic challenge that the influence of very rare variants can only be evaluated effectively as a group. A further complication is that any given rare variant could have no effect, could increase risk, or could be protective. We propose here the C-alpha test statistic as a novel approach for testing for the presence of this mixture of effects across a set of rare variants. Unlike existing burden tests, C-alpha, by testing the variance rather than the mean, maintains consistent power when the target set contains both risk and protective variants. Through simulations and analysis of case/control data, we demonstrate good power relative to existing methods that assess the burden of rare variants in individuals.

Subfields: Genetics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/01fa33e00712a8ab927457ee8e8bbef8f88bf38f

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Citations in the corpus

Optimal tests for rare variant effects in sequencing association studies. (2012, background): “[19] also showed that SKAT is a generalization of the classical C-alpha test [12, 13].”
Searching for missing heritability: Designing rare variant association studies (2014, background): “Methods such as overdispersion tests can also allow for both deleterious and protective alleles (50, 51).”
Rare-variant association analysis: study designs and statistical tests. (2014, background): “Speciﬁcally, instead of aggregating variants, variance-component tests, including the C-alpha test, 63 the sequence kernel association test (SKAT), 61,74 and the sum of squared score (SSU) test, 62 evaluate the distribution of the aggregated score test statistics (possibly with weights) of…”
Patterns and rates of exonic de novo mutations in autism spectrum disorders (2012, methodology): “We performed association tests using SKAT 17 , a generalization of C-alpha 18 .”
Dissecting the genetics of complex traits using summary association statistics (2016, background): “Overdispersion tests assume that rare variants in a candidate gene can impact a complex trait in either direction, and can be computed as weighted sums of squared single-variant test statistics 111,112 .”
The Next-Generation Sequencing Revolution and Its Impact on Genomics (2013, neutral): “…2010; Lin and Tang, 2011; Wu et al., 2011; Zhang et al., 2011]), variants with heterogeneous direction of effect (Han and Pan, 2010; Lin and Tang, 2011; Neale et al., 2011; Wu et al., 2011; Zhang et al., 2011), and selection of the ideal frequency cutoff for rare variants (Price et al., 2010a).”