Title |
Effectively identifying regulatory hotspots while capturing expression heterogeneity in gene expression studies
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Published in |
Genome Biology, April 2014
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DOI | 10.1186/gb-2014-15-4-r61 |
Pubmed ID | |
Authors |
Jong Wha J Joo, Jae Hoon Sul, Buhm Han, Chun Ye, Eleazar Eskin |
Abstract |
Expression quantitative trait loci (eQTL) mapping is a tool that can systematically identify genetic variation affecting gene expression. eQTL mapping studies have shown that certain genomic locations, referred to as regulatory hotspots, may affect the expression levels of many genes. Recently, studies have shown that various confounding factors may induce spurious regulatory hotspots. Here, we introduce a novel statistical method that effectively eliminates spurious hotspots while retaining genuine hotspots. Applied to simulated and real datasets, we validate that our method achieves greater sensitivity while retaining low false discovery rates compared to previous methods. |
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Country | Count | As % |
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United Kingdom | 3 | 27% |
United States | 3 | 27% |
Spain | 1 | 9% |
Uzbekistan | 1 | 9% |
Unknown | 3 | 27% |
Demographic breakdown
Type | Count | As % |
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Scientists | 5 | 45% |
Members of the public | 5 | 45% |
Science communicators (journalists, bloggers, editors) | 1 | 9% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 5 | 9% |
Unknown | 51 | 91% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 21 | 38% |
Researcher | 18 | 32% |
Professor | 5 | 9% |
Professor > Associate Professor | 3 | 5% |
Student > Master | 2 | 4% |
Other | 4 | 7% |
Unknown | 3 | 5% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 28 | 50% |
Biochemistry, Genetics and Molecular Biology | 10 | 18% |
Computer Science | 5 | 9% |
Mathematics | 4 | 7% |
Environmental Science | 2 | 4% |
Other | 2 | 4% |
Unknown | 5 | 9% |