Methods for detecting associations with rare variants for common diseases: application to analysis of sequence data.

By Bingshan Li, Suzanne M. Leal. American Journal of Human Genetics, 2008

1,578 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/2351e5fe0f1be7fbbee0c9a6e704ab929ace51de

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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): “Examples of the burden tests include the cohort allelic sum test (CAST) [8], the combined multivariate and collapsing method (CMC) [9], and non-parametric weighted sum test (WST) [10], which imposes weights when collapsing rare variants.”
Capturing the mutational landscape of the beta-lactamase TEM-1 (2013, background): “More importantly, it may pave the way to some accurate prediction of the effect of individual mutations on gene activity, a task of increasing importance in the identification of the genetic determinants of complex diseases based on rare variants (8, 9).”
Exome sequencing as a tool for Mendelian disease gene discovery (2011, positive): “To address this issue, analysis strategies have been developed to assess the collective effects of rare variants across a gene or across multiple genes 86–89 .”
Meta-analysis methods for genome-wide association studies and beyond (2013, background): “Several approaches for the aggregate analysis of multiple low-frequency or rare variants across a locus that may exhibit heterogeneity have been proposed 95–102 .”
Pooled association tests for rare variants in exon-resequencing studies. (2010, background): “832 The American Journal of Human Genetics 86, 832–838, June 11, A recently proposed approach is to pick a fixed allelefrequency threshold and perform an association test on the set of variants below that threshold, giving them each equal weight (more generally, variants can be collapsed into multip”
Optimal tests for rare variant effects in sequencing association studies. (2012, methodology): “For example, the Combined Multivariate and Collapsing (CMC) method [6] collapses information on all rare variants within a region by counting the number of rare alleles.”
Common vs. Rare Allele Hypotheses for Complex Diseases (2009, positive): “Statistical methods for carrying out such hypothesis tests are in their infancy, but will be crucial for advancing the CDRV hypothesis [16,34,35].”
Estimation of effect size distribution from genome-wide association studies and implications for future discoveries (2010, positive): “Our method can be applied to studies that test rare variants in regions across the genom”
The Next-Generation Sequencing Revolution and Its Impact on Genomics (2013, positive): “…detecting association of rare variation with phenotype (Chen et al., 2013; Han and Pan, 2010; Ionita-Laza et al., 2013; Lee et al., 2012a, 2012b; Li and Leal, 2008; Liu and Leal, 2010; Madsen and Browning, 2009; Neale et al., 2011; Oualkacha et al., 2013; Price et al., 2010a; Wu et al., 2011;…”
RVTESTS: an efficient and comprehensive tool for rare variant association analysis using sequence data (2016, background): “These tests range from the simple burden test, which assumes rare variants in the gene region have similar effect sizes (Li and Leal, 2008), to sequence-kernel association tests that can handle scenarios where variants in the same gene region affect the phenotype in opposite directions (Wu et al.,…”