Title |
Weighted pedigree-based statistics for testing the association of rare variants
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Published in |
BMC Genomics, November 2012
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DOI | 10.1186/1471-2164-13-667 |
Pubmed ID | |
Authors |
Yin Yao Shugart, Yun Zhu, Wei Guo, Momiao Xiong |
Abstract |
With the advent of next-generation sequencing (NGS) technologies, researchers are now generating a deluge of data on high dimensional genomic variations, whose analysis is likely to reveal rare variants involved in the complex etiology of disease. Standing in the way of such discoveries, however, is the fact that statistics for rare variants are currently designed for use with population-based data. In this paper, we introduce a pedigree-based statistic specifically designed to test for rare variants in family-based data. The additional power of pedigree-based statistics stems from the fact that while rare variants related to diseases or traits of interest occur only infrequently in populations, in families with multiple affected individuals, such variants are enriched. Note that while the proposed statistic can be applied with and without statistical weighting, our simulations show that its power increases when weighting (WSS and VT) are applied. |
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Germany | 1 | 20% |
Belgium | 1 | 20% |
Canada | 1 | 20% |
United States | 1 | 20% |
Demographic breakdown
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Members of the public | 2 | 40% |
Mendeley readers
Geographical breakdown
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Sweden | 1 | 3% |
Belgium | 1 | 3% |
Canada | 1 | 3% |
Unknown | 30 | 88% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 12 | 35% |
Student > Ph. D. Student | 6 | 18% |
Professor | 3 | 9% |
Professor > Associate Professor | 3 | 9% |
Student > Master | 2 | 6% |
Other | 5 | 15% |
Unknown | 3 | 9% |
Readers by discipline | Count | As % |
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Environmental Science | 2 | 6% |
Biochemistry, Genetics and Molecular Biology | 2 | 6% |
Mathematics | 2 | 6% |
Computer Science | 2 | 6% |
Other | 7 | 21% |
Unknown | 4 | 12% |