کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
2811726 1569266 2010 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Leveraging Genetic Variability across Populations for the Identification of Causal Variants
موضوعات مرتبط
علوم زیستی و بیوفناوری بیوشیمی، ژنتیک و زیست شناسی مولکولی ژنتیک
پیش نمایش صفحه اول مقاله
Leveraging Genetic Variability across Populations for the Identification of Causal Variants
چکیده انگلیسی

Genome-wide association studies have been performed extensively in the last few years, resulting in many new discoveries of genomic regions that are associated with complex traits. It is often the case that a SNP found to be associated with the condition is not the causal SNP, but a proxy to it as a result of linkage disequilibrium. For the identification of the actual causal SNP, fine-mapping follow-up is performed, either with the use of dense genotyping or by sequencing of the region. In either case, if the causal SNP is in high linkage disequilibrium with other SNPs, the fine-mapping procedure will require a very large sample size for the identification of the causal SNP. Here, we show that by leveraging genetic variability across populations, we significantly increase the localization success rate (LSR) for a causal SNP in a follow-up study that involves multiple populations as compared to a study that involves only one population. Thus, the average power for detection of the causal variant will be higher in a joint analysis than that in studies in which only one population is analyzed at a time. On the basis of this observation, we developed a framework to efficiently search for a follow-up study design: our framework searches for the best combination of populations from a pool of available populations to maximize the LSR for detection of a causal variant. This framework and its accompanying software can be used to considerably enhance the power of fine-mapping studies.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: - Volume 86, Issue 1, 8 January 2010, Pages 23–33
نویسندگان
, , , , ,