A Groupwise Association Test for Rare Mutations Using a Weighted Sum Statistic
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Open Access
- 13 February 2009
- journal article
- research article
- Published by Public Library of Science (PLoS) in PLoS Genetics
- Vol. 5 (2) , e1000384
- https://doi.org/10.1371/journal.pgen.1000384
Abstract
Resequencing is an emerging tool for identification of rare disease-associated mutations. Rare mutations are difficult to tag with SNP genotyping, as genotyping studies are designed to detect common variants. However, studies have shown that genetic heterogeneity is a probable scenario for common diseases, in which multiple rare mutations together explain a large proportion of the genetic basis for the disease. Thus, we propose a weighted-sum method to jointly analyse a group of mutations in order to test for groupwise association with disease status. For example, such a group of mutations may result from resequencing a gene. We compare the proposed weighted-sum method to alternative methods and show that it is powerful for identifying disease-associated genes, both on simulated and Encode data. Using the weighted-sum method, a resequencing study can identify a disease-associated gene with an overall population attributable risk (PAR) of 2%, even when each individual mutation has much lower PAR, using 1,000 to 7,000 affected and unaffected individuals, depending on the underlying genetic model. This study thus demonstrates that resequencing studies can identify important genetic associations, provided that specialised analysis methods, such as the weighted-sum method, are used. Resequencing is an emerging tool for the identification of rare disease-associated mutations. Recent studies have shown that groups of multiple rare mutations together can explain a large proportion of the genetic basis for some diseases. Therefore, we propose a new statistical method for analysing a group of mutations in order to test for groupwise association with disease status. We compare the proposed weighted-sum method to alternative methods and show that it is powerful for identifying disease-associated groups of mutations, both on computer-simulated and real data. By using computer simulations, we further show that resequencing a few thousand individuals is sufficient to perform a genome-wide study of all human genes, if the proposed method is used. This study thus demonstrates that resequencing studies can identify important genetic associations, provided that specialised analysis methods, such as the proposed weighted-sum method, are used.Keywords
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