Title |
Pathway analysis of genome-wide data improves warfarin dose prediction
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Published in |
BMC Genomics, May 2013
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DOI | 10.1186/1471-2164-14-s3-s11 |
Pubmed ID | |
Authors |
Roxana Daneshjou, Nicholas P Tatonetti, Konrad J Karczewski, Hersh Sagreiya, Stephane Bourgeois, Katarzyna Drozda, James K Burmester, Tatsuhiko Tsunoda, Yusuke Nakamura, Michiaki Kubo, Matthew Tector, Nita A Limdi, Larisa H Cavallari, Minoli Perera, Julie A Johnson, Teri E Klein, Russ B Altman |
Abstract |
Many genome-wide association studies focus on associating single loci with target phenotypes. However, in the setting of rare variation, accumulating sufficient samples to assess these associations can be difficult. Moreover, multiple variations in a gene or a set of genes within a pathway may all contribute to the phenotype, suggesting that the aggregation of variations found over the gene or pathway may be useful for improving the power to detect associations. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 3 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 67% |
Scientists | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Malaysia | 1 | 2% |
Germany | 1 | 2% |
Saudi Arabia | 1 | 2% |
Unknown | 40 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 9 | 21% |
Student > Master | 9 | 21% |
Student > Ph. D. Student | 6 | 14% |
Professor | 5 | 12% |
Other | 4 | 9% |
Other | 6 | 14% |
Unknown | 4 | 9% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 9 | 21% |
Biochemistry, Genetics and Molecular Biology | 8 | 19% |
Agricultural and Biological Sciences | 8 | 19% |
Pharmacology, Toxicology and Pharmaceutical Science | 4 | 9% |
Computer Science | 2 | 5% |
Other | 8 | 19% |
Unknown | 4 | 9% |