Title |
Prioritization and functional assessment of noncoding variants associated with complex diseases
|
---|---|
Published in |
Genome Medicine, July 2018
|
DOI | 10.1186/s13073-018-0565-y |
Pubmed ID | |
Authors |
Lin Zhou, Fangqing Zhao |
Abstract |
Unraveling functional noncoding variants associated with complex diseases is still a great challenge. We present a novel algorithm, Prioritization And Functional Assessment (PAFA), that prioritizes and assesses the functionality of genetic variants by introducing population differentiation measures and recalibrating training variants. Comprehensive evaluations demonstrate that PAFA exhibits much higher sensitivity and specificity in prioritizing noncoding risk variants than existing methods. PAFA achieves improved performance in distinguishing both common and rare recurrent variants from non-recurrent variants by integrating multiple annotations and metrics. An integrated platform was developed, providing comprehensive functional annotations for noncoding variants by integrating functional genomic data, which can be accessed at http://159.226.67.237:8080/pafa . |
X Demographics
Geographical breakdown
Country | Count | As % |
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Colombia | 1 | 14% |
United Kingdom | 1 | 14% |
China | 1 | 14% |
Unknown | 4 | 57% |
Demographic breakdown
Type | Count | As % |
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Scientists | 4 | 57% |
Members of the public | 3 | 43% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 76 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 20 | 26% |
Researcher | 16 | 21% |
Student > Master | 6 | 8% |
Student > Postgraduate | 5 | 7% |
Student > Bachelor | 3 | 4% |
Other | 7 | 9% |
Unknown | 19 | 25% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 33 | 43% |
Medicine and Dentistry | 8 | 11% |
Agricultural and Biological Sciences | 5 | 7% |
Nursing and Health Professions | 2 | 3% |
Computer Science | 2 | 3% |
Other | 4 | 5% |
Unknown | 22 | 29% |