Title |
PhenoVar: a phenotype-driven approach in clinical genomics for the diagnosis of polymalformative syndromes
|
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Published in |
BMC Medical Genomics, May 2014
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DOI | 10.1186/1755-8794-7-22 |
Pubmed ID | |
Authors |
Yannis J Trakadis, Caroline Buote, Jean-François Therriault, Pierre-Étienne Jacques, Hugo Larochelle, Sébastien Lévesque |
Abstract |
We propose a phenotype-driven analysis of encrypted exome data to facilitate the widespread implementation of exome sequencing as a clinical genetic screening test.Twenty test-patients with varied syndromes were selected from the literature. For each patient, the mutation, phenotypic data, and genetic diagnosis were available. Next, control exome-files, each modified to include one of these twenty mutations, were assigned to the corresponding test-patients. These data were used by a geneticist blinded to the diagnoses to test the efficiency of our software, PhenoVar. The score assigned by PhenoVar to any genetic diagnosis listed in OMIM (Online Mendelian Inheritance in Man) took into consideration both the patient's phenotype and all variations present in the corresponding exome. The physician did not have access to the individual mutations. PhenoVar filtered the search using a cut-off phenotypic match threshold to prevent undesired discovery of incidental findings and ranked the OMIM entries according to diagnostic score. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Scientists | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United Kingdom | 1 | 2% |
France | 1 | 2% |
Unknown | 44 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 11 | 24% |
Student > Master | 7 | 15% |
Student > Bachelor | 5 | 11% |
Professor > Associate Professor | 5 | 11% |
Student > Ph. D. Student | 3 | 7% |
Other | 5 | 11% |
Unknown | 10 | 22% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 9 | 20% |
Medicine and Dentistry | 9 | 20% |
Agricultural and Biological Sciences | 8 | 17% |
Engineering | 4 | 9% |
Computer Science | 4 | 9% |
Other | 1 | 2% |
Unknown | 11 | 24% |