Detecting associations of rare variants with common diseases: collapsing or haplotyping?
نویسندگان
چکیده
منابع مشابه
Detecting associations of rare variants with common diseases: collapsing or haplotyping?
In recent years, a myriad of new statistical methods have been proposed for detecting associations of rare single-nucleotide variants (SNVs) with common diseases. These methods can be generally classified as 'collapsing' or 'haplotyping' based. The former is the predominant class, composed of most of the rare variant association methods proposed to date. However, recent works have suggested tha...
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Although whole-genome association studies using tagSNPs are a powerful approach for detecting common variants, they are underpowered for detecting associations with rare variants. Recent studies have demonstrated that common diseases can be due to functional variants with a wide spectrum of allele frequencies, ranging from rare to common. An effective way to identify rare variants is through di...
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Current Genome-Wide Association Studies (GWAS) have successfully detected many genetic variants contributing to common diseases but not rare ones. Here two haplotypebased methods are proposed for detecting rare variants contributing a common disease. One method is a haplotypebased truncated product method (HTPM), for which we borrow a p-value combination method from testing for the multiple hyp...
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Genome wide association (GWA) studies, which test for association between common genetic markers and a disease phenotype, have shown varying degrees of success. While many factors could potentially confound GWA studies, we focus on the possibility that multiple, rare variants (RVs) may act in concert to influence disease etiology. Here, we describe an algorithm for RV analysis, RareCover. The a...
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Accurate identification of haplotypes in sequenced human genomes can provide invaluable information about population demography and fine-scale correlations along the genome, thus empowering both population genomic and medical association studies. Yet phasing unrelated individuals remains a challenging problem. Incorporating available data from high throughput sequencing into traditional statist...
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ژورنال
عنوان ژورنال: Briefings in Bioinformatics
سال: 2015
ISSN: 1467-5463,1477-4054
DOI: 10.1093/bib/bbu050