Abstract
The limitations of genome-wide association (GWA) studies that are based on the common disease common variants (CDCV) hypothesis have motivated geneticists to test the hypothesis that rare variants contribute to the variation of common diseases, i.e., common disease/rare variants (CDRV). The newly developed high-throughput sequencing technologies have made the studies of rare variants practicable. Statistical approaches to test associations between a phenotype and rare variants are quickly developing. The central idea of these methods is to test a set of rare variants in a defined region or regions by collapsing or aggregating rare variants, thereby improving the statistical power. In this chapter, we introduce these methods as well as their applications in practice.
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Feng, T., Zhu, X. (2012). Detecting Rare Variants. In: Elston, R., Satagopan, J., Sun, S. (eds) Statistical Human Genetics. Methods in Molecular Biology, vol 850. Humana Press. https://doi.org/10.1007/978-1-61779-555-8_24
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DOI: https://doi.org/10.1007/978-1-61779-555-8_24
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